WASP: a Web-based Allele-Specific PCR assay designing tool for detecting SNPs and mutations
Wangkumhang, Pongsakorn; Chaichoompu, Kridsadakorn; Ngamphiw, Chumpol; Ruangrit, Uttapong; Chanprasert, Juntima; Assawamakin, Anunchai; Tongsima, Sissades
2007-01-01
Background Allele-specific (AS) Polymerase Chain Reaction is a convenient and inexpensive method for genotyping Single Nucleotide Polymorphisms (SNPs) and mutations. It is applied in many recent studies including population genetics, molecular genetics and pharmacogenomics. Using known AS primer design tools to create primers leads to cumbersome process to inexperience users since information about SNP/mutation must be acquired from public databases prior to the design. Furthermore, most of these tools do not offer the mismatch enhancement to designed primers. The available web applications do not provide user-friendly graphical input interface and intuitive visualization of their primer results. Results This work presents a web-based AS primer design application called WASP. This tool can efficiently design AS primers for human SNPs as well as mutations. To assist scientists with collecting necessary information about target polymorphisms, this tool provides a local SNP database containing over 10 million SNPs of various populations from public domain databases, namely NCBI dbSNP, HapMap and JSNP respectively. This database is tightly integrated with the tool so that users can perform the design for existing SNPs without going off the site. To guarantee specificity of AS primers, the proposed system incorporates a primer specificity enhancement technique widely used in experiment protocol. In particular, WASP makes use of different destabilizing effects by introducing one deliberate 'mismatch' at the penultimate (second to last of the 3'-end) base of AS primers to improve the resulting AS primers. Furthermore, WASP offers graphical user interface through scalable vector graphic (SVG) draw that allow users to select SNPs and graphically visualize designed primers and their conditions. Conclusion WASP offers a tool for designing AS primers for both SNPs and mutations. By integrating the database for known SNPs (using gene ID or rs number), this tool facilitates the awkward process of getting flanking sequences and other related information from public SNP databases. It takes into account the underlying destabilizing effect to ensure the effectiveness of designed primers. With user-friendly SVG interface, WASP intuitively presents resulting designed primers, which assist users to export or to make further adjustment to the design. This software can be freely accessed at . PMID:17697334
SNP-VISTA: An interactive SNP visualization tool
Shah, Nameeta; Teplitsky, Michael V; Minovitsky, Simon; Pennacchio, Len A; Hugenholtz, Philip; Hamann, Bernd; Dubchak, Inna L
2005-01-01
Background Recent advances in sequencing technologies promise to provide a better understanding of the genetics of human disease as well as the evolution of microbial populations. Single Nucleotide Polymorphisms (SNPs) are established genetic markers that aid in the identification of loci affecting quantitative traits and/or disease in a wide variety of eukaryotic species. With today's technological capabilities, it has become possible to re-sequence a large set of appropriate candidate genes in individuals with a given disease in an attempt to identify causative mutations. In addition, SNPs have been used extensively in efforts to study the evolution of microbial populations, and the recent application of random shotgun sequencing to environmental samples enables more extensive SNP analysis of co-occurring and co-evolving microbial populations. The program is available at [1]. Results We have developed and present two modifications of an interactive visualization tool, SNP-VISTA, to aid in the analyses of the following types of data: A. Large-scale re-sequence data of disease-related genes for discovery of associated and/or causative alleles (GeneSNP-VISTA). B. Massive amounts of ecogenomics data for studying homologous recombination in microbial populations (EcoSNP-VISTA). The main features and capabilities of SNP-VISTA are: 1) mapping of SNPs to gene structure; 2) classification of SNPs, based on their location in the gene, frequency of occurrence in samples and allele composition; 3) clustering, based on user-defined subsets of SNPs, highlighting haplotypes as well as recombinant sequences; 4) integration of protein evolutionary conservation visualization; and 5) display of automatically calculated recombination points that are user-editable. Conclusion The main strength of SNP-VISTA is its graphical interface and use of visual representations, which support interactive exploration and hence better understanding of large-scale SNP data by the user. PMID:16336665
Wu, Yubao; Zhu, Xiaofeng; Chen, Jian; Zhang, Xiang
2013-11-01
Epistasis (gene-gene interaction) detection in large-scale genetic association studies has recently drawn extensive research interests as many complex traits are likely caused by the joint effect of multiple genetic factors. The large number of possible interactions poses both statistical and computational challenges. A variety of approaches have been developed to address the analytical challenges in epistatic interaction detection. These methods usually output the identified genetic interactions and store them in flat file formats. It is highly desirable to develop an effective visualization tool to further investigate the detected interactions and unravel hidden interaction patterns. We have developed EINVis, a novel visualization tool that is specifically designed to analyze and explore genetic interactions. EINVis displays interactions among genetic markers as a network. It utilizes a circular layout (specially, a tree ring view) to simultaneously visualize the hierarchical interactions between single nucleotide polymorphisms (SNPs), genes, and chromosomes, and the network structure formed by these interactions. Using EINVis, the user can distinguish marginal effects from interactions, track interactions involving more than two markers, visualize interactions at different levels, and detect proxy SNPs based on linkage disequilibrium. EINVis is an effective and user-friendly free visualization tool for analyzing and exploring genetic interactions. It is publicly available with detailed documentation and online tutorial on the web at http://filer.case.edu/yxw407/einvis/. © 2013 WILEY PERIODICALS, INC.
GenomeGems: evaluation of genetic variability from deep sequencing data
2012-01-01
Background Detection of disease-causing mutations using Deep Sequencing technologies possesses great challenges. In particular, organizing the great amount of sequences generated so that mutations, which might possibly be biologically relevant, are easily identified is a difficult task. Yet, for this assignment only limited automatic accessible tools exist. Findings We developed GenomeGems to gap this need by enabling the user to view and compare Single Nucleotide Polymorphisms (SNPs) from multiple datasets and to load the data onto the UCSC Genome Browser for an expanded and familiar visualization. As such, via automatic, clear and accessible presentation of processed Deep Sequencing data, our tool aims to facilitate ranking of genomic SNP calling. GenomeGems runs on a local Personal Computer (PC) and is freely available at http://www.tau.ac.il/~nshomron/GenomeGems. Conclusions GenomeGems enables researchers to identify potential disease-causing SNPs in an efficient manner. This enables rapid turnover of information and leads to further experimental SNP validation. The tool allows the user to compare and visualize SNPs from multiple experiments and to easily load SNP data onto the UCSC Genome browser for further detailed information. PMID:22748151
VCS: Tool for Visualizing Copy Number Variation and Single Nucleotide Polymorphism.
Kim, HyoYoung; Sung, Samsun; Cho, Seoae; Kim, Tae-Hun; Seo, Kangseok; Kim, Heebal
2014-12-01
Copy number variation (CNV) or single nucleotide phlyorphism (SNP) is useful genetic resource to aid in understanding complex phenotypes or deseases susceptibility. Although thousands of CNVs and SNPs are currently avaliable in the public databases, they are somewhat difficult to use for analyses without visualization tools. We developed a web-based tool called the VCS (visualization of CNV or SNP) to visualize the CNV or SNP detected. The VCS tool can assist to easily interpret a biological meaning from the numerical value of CNV and SNP. The VCS provides six visualization tools: i) the enrichment of genome contents in CNV; ii) the physical distribution of CNV or SNP on chromosomes; iii) the distribution of log2 ratio of CNVs with criteria of interested; iv) the number of CNV or SNP per binning unit; v) the distribution of homozygosity of SNP genotype; and vi) cytomap of genes within CNV or SNP region.
A tool for selecting SNPs for association studies based on observed linkage disequilibrium patterns.
De La Vega, Francisco M; Isaac, Hadar I; Scafe, Charles R
2006-01-01
The design of genetic association studies using single-nucleotide polymorphisms (SNPs) requires the selection of subsets of the variants providing high statistical power at a reasonable cost. SNPs must be selected to maximize the probability that a causative mutation is in linkage disequilibrium (LD) with at least one marker genotyped in the study. The HapMap project performed a genome-wide survey of genetic variation with about a million SNPs typed in four populations, providing a rich resource to inform the design of association studies. A number of strategies have been proposed for the selection of SNPs based on observed LD, including construction of metric LD maps and the selection of haplotype tagging SNPs. Power calculations are important at the study design stage to ensure successful results. Integrating these methods and annotations can be challenging: the algorithms required to implement these methods are complex to deploy, and all the necessary data and annotations are deposited in disparate databases. Here, we present the SNPbrowser Software, a freely available tool to assist in the LD-based selection of markers for association studies. This stand-alone application provides fast query capabilities and swift visualization of SNPs, gene annotations, power, haplotype blocks, and LD map coordinates. Wizards implement several common SNP selection workflows including the selection of optimal subsets of SNPs (e.g. tagging SNPs). Selected SNPs are screened for their conversion potential to either TaqMan SNP Genotyping Assays or the SNPlex Genotyping System, two commercially available genotyping platforms, expediting the set-up of genetic studies with an increased probability of success.
Solano-Román, Antonio; Alfaro-Arias, Verónica; Cruz-Castillo, Carlos; Orozco-Solano, Allan
2018-03-15
VizGVar was designed to meet the growing need of the research community for improved genomic and proteomic data viewers that benefit from better information visualization. We implemented a new information architecture and applied user centered design principles to provide a new improved way of visualizing genetic information and protein data related to human disease. VizGVar connects the entire database of Ensembl protein motifs, domains, genes and exons with annotated SNPs and somatic variations from PharmGKB and COSMIC. VizGVar precisely represents genetic variations and their respective location by colored curves to designate different types of variations. The structured hierarchy of biological data is reflected in aggregated patterns through different levels, integrating several layers of information at once. VizGVar provides a new interactive, web-based JavaScript visualization of somatic mutations and protein variation, enabling fast and easy discovery of clinically relevant variation patterns. VizGVar is accessible at http://vizport.io/vizgvar; http://vizport.io/vizgvar/doc/. asolano@broadinstitute.org or allan.orozcosolano@ucr.ac.cr.
Ferret: a user-friendly Java tool to extract data from the 1000 Genomes Project.
Limou, Sophie; Taverner, Andrew M; Winkler, Cheryl A
2016-07-15
The 1000 Genomes (1KG) Project provides a near-comprehensive resource on human genetic variation in worldwide reference populations. 1KG variants can be accessed through a browser and through the raw and annotated data that are regularly released on an ftp server. We developed Ferret, a user-friendly Java tool, to easily extract genetic variation information from these large and complex data files. From a locus, gene(s) or SNP(s) of interest, Ferret retrieves genotype data for 1KG SNPs and indels, and computes allelic frequencies for 1KG populations and optionally, for the Exome Sequencing Project populations. By converting the 1KG data into files that can be imported into popular pre-existing tools (e.g. PLINK and HaploView), Ferret offers a straightforward way, even for non-bioinformatics specialists, to manipulate, explore and merge 1KG data with the user's dataset, as well as visualize linkage disequilibrium pattern, infer haplotypes and design tagSNPs. Ferret tool and source code are publicly available at http://limousophie35.github.io/Ferret/ ferret@nih.gov Supplementary data are available at Bioinformatics online. Published by Oxford University Press 2016. This work is written by US Government employees and is in the public domain in the US.
SNP-VISTA: An Interactive SNPs Visualization Tool
DOE Office of Scientific and Technical Information (OSTI.GOV)
Shah, Nameeta; Teplitsky, Michael V.; Pennacchio, Len A.
2005-07-05
Recent advances in sequencing technologies promise better diagnostics for many diseases as well as better understanding of evolution of microbial populations. Single Nucleotide Polymorphisms(SNPs) are established genetic markers that aid in the identification of loci affecting quantitative traits and/or disease in a wide variety of eukaryotic species. With today's technological capabilities, it is possible to re-sequence a large set of appropriate candidate genes in individuals with a given disease and then screen for causative mutations.In addition, SNPs have been used extensively in efforts to study the evolution of microbial populations, and the recent application of random shotgun sequencing to environmentalmore » samples makes possible more extensive SNP analysis of co-occurring and co-evolving microbial populations. The program is available at http://genome.lbl.gov/vista/snpvista.« less
Ning, Shangwei; Yue, Ming; Wang, Peng; Liu, Yue; Zhi, Hui; Zhang, Yan; Zhang, Jizhou; Gao, Yue; Guo, Maoni; Zhou, Dianshuang; Li, Xin; Li, Xia
2017-01-04
We describe LincSNP 2.0 (http://bioinfo.hrbmu.edu.cn/LincSNP), an updated database that is used specifically to store and annotate disease-associated single nucleotide polymorphisms (SNPs) in human long non-coding RNAs (lncRNAs) and their transcription factor binding sites (TFBSs). In LincSNP 2.0, we have updated the database with more data and several new features, including (i) expanding disease-associated SNPs in human lncRNAs; (ii) identifying disease-associated SNPs in lncRNA TFBSs; (iii) updating LD-SNPs from the 1000 Genomes Project; and (iv) collecting more experimentally supported SNP-lncRNA-disease associations. Furthermore, we developed three flexible online tools to retrieve and analyze the data. Linc-Mart is a convenient way for users to customize their own data. Linc-Browse is a tool for all data visualization. Linc-Score predicts the associations between lncRNA and disease. In addition, we provided users a newly designed, user-friendly interface to search and download all the data in LincSNP 2.0 and we also provided an interface to submit novel data into the database. LincSNP 2.0 is a continually updated database and will serve as an important resource for investigating the functions and mechanisms of lncRNAs in human diseases. © The Author(s) 2016. Published by Oxford University Press on behalf of Nucleic Acids Research.
HapMap filter 1.0: a tool to preprocess the HapMap genotypic data for association studies.
Zhang, Wei; Duan, Shiwei; Dolan, M Eileen
2008-05-13
The International HapMap Project provides a resource of genotypic data on single nucleotide polymorphisms (SNPs), which can be used in various association studies to identify the genetic determinants for phenotypic variations. Prior to the association studies, the HapMap dataset should be preprocessed in order to reduce the computation time and control the multiple testing problem. The less informative SNPs including those with very low genotyping rate and SNPs with rare minor allele frequencies to some extent in one or more population are removed. Some research designs only use SNPs in a subset of HapMap cell lines. Although the HapMap website and other association software packages have provided some basic tools for optimizing these datasets, a fast and user-friendly program to generate the output for filtered genotypic data would be beneficial for association studies. Here, we present a flexible, straight-forward bioinformatics program that can be useful in preparing the HapMap genotypic data for association studies by specifying cell lines and two common filtering criteria: minor allele frequencies and genotyping rate. The software was developed for Microsoft Windows and written in C++. The Windows executable and source code in Microsoft Visual C++ are available at Google Code (http://hapmap-filter-v1.googlecode.com/) or upon request. Their distribution is subject to GNU General Public License v3.
CsSNP: A Web-Based Tool for the Detecting of Comparative Segments SNPs.
Wang, Yi; Wang, Shuangshuang; Zhou, Dongjie; Yang, Shuai; Xu, Yongchao; Yang, Chao; Yang, Long
2016-07-01
SNP (single nucleotide polymorphism) is a popular tool for the study of genetic diversity, evolution, and other areas. Therefore, it is necessary to develop a convenient, utility, robust, rapid, and open source detecting-SNP tool for all researchers. Since the detection of SNPs needs special software and series steps including alignment, detection, analysis and present, the study of SNPs is limited for nonprofessional users. CsSNP (Comparative segments SNP, http://biodb.sdau.edu.cn/cssnp/ ) is a freely available web tool based on the Blat, Blast, and Perl programs to detect comparative segments SNPs and to show the detail information of SNPs. The results are filtered and presented in the statistics figure and a Gbrowse map. This platform contains the reference genomic sequences and coding sequences of 60 plant species, and also provides new opportunities for the users to detect SNPs easily. CsSNP is provided a convenient tool for nonprofessional users to find comparative segments SNPs in their own sequences, and give the users the information and the analysis of SNPs, and display these data in a dynamic map. It provides a new method to detect SNPs and may accelerate related studies.
LD2SNPing: linkage disequilibrium plotter and RFLP enzyme mining for tag SNPs
Chang, Hsueh-Wei; Chuang, Li-Yeh; Chang, Yan-Jhu; Cheng, Yu-Huei; Hung, Yu-Chen; Chen, Hsiang-Chi; Yang, Cheng-Hong
2009-01-01
Background Linkage disequilibrium (LD) mapping is commonly used to evaluate markers for genome-wide association studies. Most types of LD software focus strictly on LD analysis and visualization, but lack supporting services for genotyping. Results We developed a freeware called LD2SNPing, which provides a complete package of mining tools for genotyping and LD analysis environments. The software provides SNP ID- and gene-centric online retrievals for SNP information and tag SNP selection from dbSNP/NCBI and HapMap, respectively. Restriction fragment length polymorphism (RFLP) enzyme information for SNP genotype is available to all SNP IDs and tag SNPs. Single and multiple SNP inputs are possible in order to perform LD analysis by online retrieval from HapMap and NCBI. An LD statistics section provides D, D', r2, δQ, ρ, and the P values of the Hardy-Weinberg Equilibrium for each SNP marker, and Chi-square and likelihood-ratio tests for the pair-wise association of two SNPs in LD calculation. Finally, 2D and 3D plots, as well as plain-text output of the results, can be selected. Conclusion LD2SNPing thus provides a novel visualization environment for multiple SNP input, which facilitates SNP association studies. The software, user manual, and tutorial are freely available at . PMID:19500380
Suciu, Maria C.; Telenius, Jelena
2017-01-01
In the era of genome-wide association studies (GWAS) and personalized medicine, predicting the impact of single nucleotide polymorphisms (SNPs) in regulatory elements is an important goal. Current approaches to determine the potential of regulatory SNPs depend on inadequate knowledge of cell-specific DNA binding motifs. Here, we present Sasquatch, a new computational approach that uses DNase footprint data to estimate and visualize the effects of noncoding variants on transcription factor binding. Sasquatch performs a comprehensive k-mer-based analysis of DNase footprints to determine any k-mer's potential for protein binding in a specific cell type and how this may be changed by sequence variants. Therefore, Sasquatch uses an unbiased approach, independent of known transcription factor binding sites and motifs. Sasquatch only requires a single DNase-seq data set per cell type, from any genotype, and produces consistent predictions from data generated by different experimental procedures and at different sequence depths. Here we demonstrate the effectiveness of Sasquatch using previously validated functional SNPs and benchmark its performance against existing approaches. Sasquatch is available as a versatile webtool incorporating publicly available data, including the human ENCODE collection. Thus, Sasquatch provides a powerful tool and repository for prioritizing likely regulatory SNPs in the noncoding genome. PMID:28904015
Genovar: a detection and visualization tool for genomic variants.
Jung, Kwang Su; Moon, Sanghoon; Kim, Young Jin; Kim, Bong-Jo; Park, Kiejung
2012-05-08
Along with single nucleotide polymorphisms (SNPs), copy number variation (CNV) is considered an important source of genetic variation associated with disease susceptibility. Despite the importance of CNV, the tools currently available for its analysis often produce false positive results due to limitations such as low resolution of array platforms, platform specificity, and the type of CNV. To resolve this problem, spurious signals must be separated from true signals by visual inspection. None of the previously reported CNV analysis tools support this function and the simultaneous visualization of comparative genomic hybridization arrays (aCGH) and sequence alignment. The purpose of the present study was to develop a useful program for the efficient detection and visualization of CNV regions that enables the manual exclusion of erroneous signals. A JAVA-based stand-alone program called Genovar was developed. To ascertain whether a detected CNV region is a novel variant, Genovar compares the detected CNV regions with previously reported CNV regions using the Database of Genomic Variants (DGV, http://projects.tcag.ca/variation) and the Single Nucleotide Polymorphism Database (dbSNP). The current version of Genovar is capable of visualizing genomic data from sources such as the aCGH data file and sequence alignment format files. Genovar is freely accessible and provides a user-friendly graphic user interface (GUI) to facilitate the detection of CNV regions. The program also provides comprehensive information to help in the elimination of spurious signals by visual inspection, making Genovar a valuable tool for reducing false positive CNV results. http://genovar.sourceforge.net/.
Schwessinger, Ron; Suciu, Maria C; McGowan, Simon J; Telenius, Jelena; Taylor, Stephen; Higgs, Doug R; Hughes, Jim R
2017-10-01
In the era of genome-wide association studies (GWAS) and personalized medicine, predicting the impact of single nucleotide polymorphisms (SNPs) in regulatory elements is an important goal. Current approaches to determine the potential of regulatory SNPs depend on inadequate knowledge of cell-specific DNA binding motifs. Here, we present Sasquatch, a new computational approach that uses DNase footprint data to estimate and visualize the effects of noncoding variants on transcription factor binding. Sasquatch performs a comprehensive k -mer-based analysis of DNase footprints to determine any k -mer's potential for protein binding in a specific cell type and how this may be changed by sequence variants. Therefore, Sasquatch uses an unbiased approach, independent of known transcription factor binding sites and motifs. Sasquatch only requires a single DNase-seq data set per cell type, from any genotype, and produces consistent predictions from data generated by different experimental procedures and at different sequence depths. Here we demonstrate the effectiveness of Sasquatch using previously validated functional SNPs and benchmark its performance against existing approaches. Sasquatch is available as a versatile webtool incorporating publicly available data, including the human ENCODE collection. Thus, Sasquatch provides a powerful tool and repository for prioritizing likely regulatory SNPs in the noncoding genome. © 2017 Schwessinger et al.; Published by Cold Spring Harbor Laboratory Press.
SNPversity: a web-based tool for visualizing diversity
Schott, David A; Vinnakota, Abhinav G; Portwood, John L; Andorf, Carson M
2018-01-01
Abstract Many stand-alone desktop software suites exist to visualize single nucleotide polymorphism (SNP) diversity, but web-based software that can be easily implemented and used for biological databases is absent. SNPversity was created to answer this need by building an open-source visualization tool that can be implemented on a Unix-like machine and served through a web browser that can be accessible worldwide. SNPversity consists of a HDF5 database back-end for SNPs, a data exchange layer powered by TASSEL libraries that represent data in JSON format, and an interface layer using PHP to visualize SNP information. SNPversity displays data in real-time through a web browser in grids that are color-coded according to a given SNP’s allelic status and mutational state. SNPversity is currently available at MaizeGDB, the maize community’s database, and will be soon available at GrainGenes, the clade-oriented database for Triticeae and Avena species, including wheat, barley, rye, and oat. The code and documentation are uploaded onto github, and they are freely available to the public. We expect that the tool will be highly useful for other biological databases with a similar need to display SNP diversity through their web interfaces. Database URL: https://www.maizegdb.org/snpversity PMID:29688387
UCbase 2.0: ultraconserved sequences database (2014 update)
Lomonaco, Vincenzo; Martoglia, Riccardo; Mandreoli, Federica; Anderlucci, Laura; Emmett, Warren; Bicciato, Silvio; Taccioli, Cristian
2014-01-01
UCbase 2.0 (http://ucbase.unimore.it) is an update, extension and evolution of UCbase, a Web tool dedicated to the analysis of ultraconserved sequences (UCRs). UCRs are 481 sequences >200 bases sharing 100% identity among human, mouse and rat genomes. They are frequently located in genomic regions known to be involved in cancer or differentially expressed in human leukemias and carcinomas. UCbase 2.0 is a platform-independent Web resource that includes the updated version of the human genome annotation (hg19), information linking disorders to chromosomal coordinates based on the Systematized Nomenclature of Medicine classification, a query tool to search for Single Nucleotide Polymorphisms (SNPs) and a new text box to directly interrogate the database using a MySQL interface. To facilitate the interactive visual interpretation of UCR chromosomal positioning, UCbase 2.0 now includes a graph visualization interface directly linked to UCSC genome browser. Database URL: http://ucbase.unimore.it PMID:24951797
CircosVCF: circos visualization of whole-genome sequence variations stored in VCF files.
Drori, E; Levy, D; Smirin-Yosef, P; Rahimi, O; Salmon-Divon, M
2017-05-01
Visualization of whole-genomic variations in a meaningful manner assists researchers in gaining new insights into the underlying data, especially when it comes in the context of whole genome comparisons. CircosVCF is a web based visualization tool for genome-wide variant data described in VCF files, using circos plots. The user friendly interface of CircosVCF supports an interactive design of the circles in the plot, and the integration of additional information such as experimental data or annotations. The provided visualization capabilities give a broad overview of the genomic relationships between genomes, and allow identification of specific meaningful SNPs regions. CircosVCF was implemented in JavaScript and is available at http://www.ariel.ac.il/research/fbl/software. malisa@ariel.ac.il. Supplementary data are available at Bioinformatics online. © The Author 2017. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com
An integrated SNP mining and utilization (ISMU) pipeline for next generation sequencing data.
Azam, Sarwar; Rathore, Abhishek; Shah, Trushar M; Telluri, Mohan; Amindala, BhanuPrakash; Ruperao, Pradeep; Katta, Mohan A V S K; Varshney, Rajeev K
2014-01-01
Open source single nucleotide polymorphism (SNP) discovery pipelines for next generation sequencing data commonly requires working knowledge of command line interface, massive computational resources and expertise which is a daunting task for biologists. Further, the SNP information generated may not be readily used for downstream processes such as genotyping. Hence, a comprehensive pipeline has been developed by integrating several open source next generation sequencing (NGS) tools along with a graphical user interface called Integrated SNP Mining and Utilization (ISMU) for SNP discovery and their utilization by developing genotyping assays. The pipeline features functionalities such as pre-processing of raw data, integration of open source alignment tools (Bowtie2, BWA, Maq, NovoAlign and SOAP2), SNP prediction (SAMtools/SOAPsnp/CNS2snp and CbCC) methods and interfaces for developing genotyping assays. The pipeline outputs a list of high quality SNPs between all pairwise combinations of genotypes analyzed, in addition to the reference genome/sequence. Visualization tools (Tablet and Flapjack) integrated into the pipeline enable inspection of the alignment and errors, if any. The pipeline also provides a confidence score or polymorphism information content value with flanking sequences for identified SNPs in standard format required for developing marker genotyping (KASP and Golden Gate) assays. The pipeline enables users to process a range of NGS datasets such as whole genome re-sequencing, restriction site associated DNA sequencing and transcriptome sequencing data at a fast speed. The pipeline is very useful for plant genetics and breeding community with no computational expertise in order to discover SNPs and utilize in genomics, genetics and breeding studies. The pipeline has been parallelized to process huge datasets of next generation sequencing. It has been developed in Java language and is available at http://hpc.icrisat.cgiar.org/ISMU as a standalone free software.
Bakken, Trygve E; Roddey, J Cooper; Djurovic, Srdjan; Akshoomoff, Natacha; Amaral, David G; Bloss, Cinnamon S; Casey, B J; Chang, Linda; Ernst, Thomas M; Gruen, Jeffrey R; Jernigan, Terry L; Kaufmann, Walter E; Kenet, Tal; Kennedy, David N; Kuperman, Joshua M; Murray, Sarah S; Sowell, Elizabeth R; Rimol, Lars M; Mattingsdal, Morten; Melle, Ingrid; Agartz, Ingrid; Andreassen, Ole A; Schork, Nicholas J; Dale, Anders M; Weiner, Michael; Aisen, Paul; Petersen, Ronald; Jack, Clifford R; Jagust, William; Trojanowki, John Q; Toga, Arthur W; Beckett, Laurel; Green, Robert C; Saykin, Andrew J; Morris, John; Liu, Enchi; Montine, Tom; Gamst, Anthony; Thomas, Ronald G; Donohue, Michael; Walter, Sarah; Gessert, Devon; Sather, Tamie; Harvey, Danielle; Kornak, John; Dale, Anders; Bernstein, Matthew; Felmlee, Joel; Fox, Nick; Thompson, Paul; Schuff, Norbert; Alexander, Gene; DeCarli, Charles; Bandy, Dan; Koeppe, Robert A; Foster, Norm; Reiman, Eric M; Chen, Kewei; Mathis, Chet; Cairns, Nigel J; Taylor-Reinwald, Lisa; Trojanowki, J Q; Shaw, Les; Lee, Virginia M Y; Korecka, Magdalena; Crawford, Karen; Neu, Scott; Foroud, Tatiana M; Potkin, Steven; Shen, Li; Kachaturian, Zaven; Frank, Richard; Snyder, Peter J; Molchan, Susan; Kaye, Jeffrey; Quinn, Joseph; Lind, Betty; Dolen, Sara; Schneider, Lon S; Pawluczyk, Sonia; Spann, Bryan M; Brewer, James; Vanderswag, Helen; Heidebrink, Judith L; Lord, Joanne L; Johnson, Kris; Doody, Rachelle S; Villanueva-Meyer, Javier; Chowdhury, Munir; Stern, Yaakov; Honig, Lawrence S; Bell, Karen L; Morris, John C; Ances, Beau; Carroll, Maria; Leon, Sue; Mintun, Mark A; Schneider, Stacy; Marson, Daniel; Griffith, Randall; Clark, David; Grossman, Hillel; Mitsis, Effie; Romirowsky, Aliza; deToledo-Morrell, Leyla; Shah, Raj C; Duara, Ranjan; Varon, Daniel; Roberts, Peggy; Albert, Marilyn; Onyike, Chiadi; Kielb, Stephanie; Rusinek, Henry; de Leon, Mony J; Glodzik, Lidia; De Santi, Susan; Doraiswamy, P Murali; Petrella, Jeffrey R; Coleman, R Edward; Arnold, Steven E; Karlawish, Jason H; Wolk, David; Smith, Charles D; Jicha, Greg; Hardy, Peter; Lopez, Oscar L; Oakley, MaryAnn; Simpson, Donna M; Porsteinsson, Anton P; Goldstein, Bonnie S; Martin, Kim; Makino, Kelly M; Ismail, M Saleem; Brand, Connie; Mulnard, Ruth A; Thai, Gaby; Mc-Adams-Ortiz, Catherine; Womack, Kyle; Mathews, Dana; Quiceno, Mary; Diaz-Arrastia, Ramon; King, Richard; Weiner, Myron; Martin-Cook, Kristen; DeVous, Michael; Levey, Allan I; Lah, James J; Cellar, Janet S; Burns, Jeffrey M; Anderson, Heather S; Swerdlow, Russell H; Apostolova, Liana; Lu, Po H; Bartzokis, George; Silverman, Daniel H S; Graff-Radford, Neill R; Parfitt, Francine; Johnson, Heather; Farlow, Martin R; Hake, Ann Marie; Matthews, Brandy R; Herring, Scott; van Dyck, Christopher H; Carson, Richard E; MacAvoy, Martha G; Chertkow, Howard; Bergman, Howard; Hosein, Chris; Black, Sandra; Stefanovic, Bojana; Caldwell, Curtis; Ging-Yuek; Hsiung, Robin; Feldman, Howard; Mudge, Benita; Assaly, Michele; Kertesz, Andrew; Rogers, John; Trost, Dick; Bernick, Charles; Munic, Donna; Kerwin, Diana; Mesulam, Marek-Marsel; Lipowski, Kristina; Wu, Chuang-Kuo; Johnson, Nancy; Sadowsky, Carl; Martinez, Walter; Villena, Teresa; Turner, Raymond Scott; Johnson, Kathleen; Reynolds, Brigid; Sperling, Reisa A; Johnson, Keith A; Marshall, Gad; Frey, Meghan; Yesavage, Jerome; Taylor, Joy L; Lane, Barton; Rosen, Allyson; Tinklenberg, Jared; Sabbagh, Marwan; Belden, Christine; Jacobson, Sandra; Kowall, Neil; Killiany, Ronald; Budson, Andrew E; Norbash, Alexander; Johnson, Patricia Lynn; Obisesan, Thomas O; Wolday, Saba; Bwayo, Salome K; Lerner, Alan; Hudson, Leon; Ogrocki, Paula; Fletcher, Evan; Carmichael, Owen; Olichney, John; Kittur, Smita; Borrie, Michael; Lee, T-Y; Bartha, Rob; Johnson, Sterling; Asthana, Sanjay; Carlsson, Cynthia M; Potkin, Steven G; Preda, Adrian; Nguyen, Dana; Tariot, Pierre; Fleisher, Adam; Reeder, Stephanie; Bates, Vernice; Capote, Horacio; Rainka, Michelle; Scharre, Douglas W; Kataki, Maria; Zimmerman, Earl A; Celmins, Dzintra; Brown, Alice D; Pearlson, Godfrey D; Blank, Karen; Anderson, Karen; Santulli, Robert B; Schwartz, Eben S; Sink, Kaycee M; Williamson, Jeff D; Garg, Pradeep; Watkins, Franklin; Ott, Brian R; Querfurth, Henry; Tremont, Geoffrey; Salloway, Stephen; Malloy, Paul; Correia, Stephen; Rosen, Howard J; Miller, Bruce L; Mintzer, Jacobo; Longmire, Crystal Flynn; Spicer, Kenneth; Finger, Elizabether; Rachinsky, Irina; Drost, Dick; Jernigan, Terry; McCabe, Connor; Grant, Ellen; Ernst, Thomas; Kuperman, Josh; Chung, Yoon; Murray, Sarah; Bloss, Cinnamon; Darst, Burcu; Pritchett, Lexi; Saito, Ashley; Amaral, David; DiNino, Mishaela; Eyngorina, Bella; Sowell, Elizabeth; Houston, Suzanne; Soderberg, Lindsay; Kaufmann, Walter; van Zijl, Peter; Rizzo-Busack, Hilda; Javid, Mohsin; Mehta, Natasha; Ruberry, Erika; Powers, Alisa; Rosen, Bruce; Gebhard, Nitzah; Manigan, Holly; Frazier, Jean; Kennedy, David; Yakutis, Lauren; Hill, Michael; Gruen, Jeffrey; Bosson-Heenan, Joan; Carlson, Heatherly
2012-03-06
Visual cortical surface area varies two- to threefold between human individuals, is highly heritable, and has been correlated with visual acuity and visual perception. However, it is still largely unknown what specific genetic and environmental factors contribute to normal variation in the area of visual cortex. To identify SNPs associated with the proportional surface area of visual cortex, we performed a genome-wide association study followed by replication in two independent cohorts. We identified one SNP (rs6116869) that replicated in both cohorts and had genome-wide significant association (P(combined) = 3.2 × 10(-8)). Furthermore, a metaanalysis of imputed SNPs in this genomic region identified a more significantly associated SNP (rs238295; P = 6.5 × 10(-9)) that was in strong linkage disequilibrium with rs6116869. These SNPs are located within 4 kb of the 5' UTR of GPCPD1, glycerophosphocholine phosphodiesterase GDE1 homolog (Saccharomyces cerevisiae), which in humans, is more highly expressed in occipital cortex compared with the remainder of cortex than 99.9% of genes genome-wide. Based on these findings, we conclude that this common genetic variation contributes to the proportional area of human visual cortex. We suggest that identifying genes that contribute to normal cortical architecture provides a first step to understanding genetic mechanisms that underlie visual perception.
UCbase 2.0: ultraconserved sequences database (2014 update).
Lomonaco, Vincenzo; Martoglia, Riccardo; Mandreoli, Federica; Anderlucci, Laura; Emmett, Warren; Bicciato, Silvio; Taccioli, Cristian
2014-01-01
UCbase 2.0 (http://ucbase.unimore.it) is an update, extension and evolution of UCbase, a Web tool dedicated to the analysis of ultraconserved sequences (UCRs). UCRs are 481 sequences >200 bases sharing 100% identity among human, mouse and rat genomes. They are frequently located in genomic regions known to be involved in cancer or differentially expressed in human leukemias and carcinomas. UCbase 2.0 is a platform-independent Web resource that includes the updated version of the human genome annotation (hg19), information linking disorders to chromosomal coordinates based on the Systematized Nomenclature of Medicine classification, a query tool to search for Single Nucleotide Polymorphisms (SNPs) and a new text box to directly interrogate the database using a MySQL interface. To facilitate the interactive visual interpretation of UCR chromosomal positioning, UCbase 2.0 now includes a graph visualization interface directly linked to UCSC genome browser. Database URL: http://ucbase.unimore.it. © The Author(s) 2014. Published by Oxford University Press.
In silico SNP analysis of the breast cancer antigen NY-BR-1.
Kosaloglu, Zeynep; Bitzer, Julia; Halama, Niels; Huang, Zhiqin; Zapatka, Marc; Schneeweiss, Andreas; Jäger, Dirk; Zörnig, Inka
2016-11-18
Breast cancer is one of the most common malignancies with increasing incidences every year and a leading cause of death among women. Although early stage breast cancer can be effectively treated, there are limited numbers of treatment options available for patients with advanced and metastatic disease. The novel breast cancer associated antigen NY-BR-1 was identified by SEREX analysis and is expressed in the majority (>70%) of breast tumors as well as metastases, in normal breast tissue, in testis and occasionally in prostate tissue. The biological function and regulation of NY-BR-1 is up to date unknown. We performed an in silico analysis on the genetic variations of the NY-BR-1 gene using data available in public SNP databases and the tools SIFT, Polyphen and Provean to find possible functional SNPs. Additionally, we considered the allele frequency of the found damaging SNPs and also analyzed data from an in-house sequencing project of 55 breast cancer samples for recurring SNPs, recorded in dbSNP. Over 2800 SNPs are recorded in the dbSNP and NHLBI ESP databases for the NY-BR-1 gene. Of these, 65 (2.07%) are synonymous SNPs, 191 (6.09%) are non-synoymous SNPs, and 2430 (77.48%) are noncoding intronic SNPs. As a result, 69 non-synoymous SNPs were predicted to be damaging by at least two, and 16 SNPs were predicted as damaging by all three of the used tools. The SNPs rs200639888, rs367841401 and rs377750885 were categorized as highly damaging by all three tools. Eight damaging SNPs are located in the ankyrin repeat domain (ANK), a domain known for its frequent involvement in protein-protein interactions. No distinctive features could be observed in the allele frequency of the analyzed SNPs. Considering these results we expect to gain more insights into the variations of the NY-BR-1 gene and their possible impact on giving rise to splice variants and therefore influence the function of NY-BR-1 in healthy tissue as well as in breast cancer.
Screening large-scale association study data: exploiting interactions using random forests.
Lunetta, Kathryn L; Hayward, L Brooke; Segal, Jonathan; Van Eerdewegh, Paul
2004-12-10
Genome-wide association studies for complex diseases will produce genotypes on hundreds of thousands of single nucleotide polymorphisms (SNPs). A logical first approach to dealing with massive numbers of SNPs is to use some test to screen the SNPs, retaining only those that meet some criterion for further study. For example, SNPs can be ranked by p-value, and those with the lowest p-values retained. When SNPs have large interaction effects but small marginal effects in a population, they are unlikely to be retained when univariate tests are used for screening. However, model-based screens that pre-specify interactions are impractical for data sets with thousands of SNPs. Random forest analysis is an alternative method that produces a single measure of importance for each predictor variable that takes into account interactions among variables without requiring model specification. Interactions increase the importance for the individual interacting variables, making them more likely to be given high importance relative to other variables. We test the performance of random forests as a screening procedure to identify small numbers of risk-associated SNPs from among large numbers of unassociated SNPs using complex disease models with up to 32 loci, incorporating both genetic heterogeneity and multi-locus interaction. Keeping other factors constant, if risk SNPs interact, the random forest importance measure significantly outperforms the Fisher Exact test as a screening tool. As the number of interacting SNPs increases, the improvement in performance of random forest analysis relative to Fisher Exact test for screening also increases. Random forests perform similarly to the univariate Fisher Exact test as a screening tool when SNPs in the analysis do not interact. In the context of large-scale genetic association studies where unknown interactions exist among true risk-associated SNPs or SNPs and environmental covariates, screening SNPs using random forest analyses can significantly reduce the number of SNPs that need to be retained for further study compared to standard univariate screening methods.
regSNPs: a strategy for prioritizing regulatory single nucleotide substitutions
Teng, Mingxiang; Ichikawa, Shoji; Padgett, Leah R.; Wang, Yadong; Mort, Matthew; Cooper, David N.; Koller, Daniel L.; Foroud, Tatiana; Edenberg, Howard J.; Econs, Michael J.; Liu, Yunlong
2012-01-01
Motivation: One of the fundamental questions in genetics study is to identify functional DNA variants that are responsible to a disease or phenotype of interest. Results from large-scale genetics studies, such as genome-wide association studies (GWAS), and the availability of high-throughput sequencing technologies provide opportunities in identifying causal variants. Despite the technical advances, informatics methodologies need to be developed to prioritize thousands of variants for potential causative effects. Results: We present regSNPs, an informatics strategy that integrates several established bioinformatics tools, for prioritizing regulatory SNPs, i.e. the SNPs in the promoter regions that potentially affect phenotype through changing transcription of downstream genes. Comparing to existing tools, regSNPs has two distinct features. It considers degenerative features of binding motifs by calculating the differences on the binding affinity caused by the candidate variants and integrates potential phenotypic effects of various transcription factors. When tested by using the disease-causing variants documented in the Human Gene Mutation Database, regSNPs showed mixed performance on various diseases. regSNPs predicted three SNPs that can potentially affect bone density in a region detected in an earlier linkage study. Potential effects of one of the variants were validated using luciferase reporter assay. Contact: yunliu@iupui.edu Supplementary information: Supplementary data are available at Bioinformatics online PMID:22611130
Hall, Barry G
2014-01-01
SNP-association studies are a starting point for identifying genes that may be responsible for specific phenotypes, such as disease traits. The vast bulk of tools for SNP-association studies are directed toward SNPs in the human genome, and I am unaware of any tools designed specifically for such studies in bacterial or viral genomes. The PPFS (Predict Phenotypes From SNPs) package described here is an add-on to kSNP , a program that can identify SNPs in a data set of hundreds of microbial genomes. PPFS identifies those SNPs that are non-randomly associated with a phenotype based on the χ² probability, then uses those diagnostic SNPs for two distinct, but related, purposes: (1) to predict the phenotypes of strains whose phenotypes are unknown, and (2) to identify those diagnostic SNPs that are most likely to be causally related to the phenotype. In the example illustrated here, from a set of 68 E. coli genomes, for 67 of which the pathogenicity phenotype was known, there were 418,500 SNPs. Using the phenotypes of 36 of those strains, PPFS identified 207 diagnostic SNPs. The diagnostic SNPs predicted the phenotypes of all of the genomes with 97% accuracy. It then identified 97 SNPs whose probability of being causally related to the pathogenic phenotype was >0.999. In a second example, from a set of 116 E. coli genome sequences, using the phenotypes of 65 strains PPFS identified 101 SNPs that predicted the source host (human or non-human) with 90% accuracy.
An Integrated SNP Mining and Utilization (ISMU) Pipeline for Next Generation Sequencing Data
Azam, Sarwar; Rathore, Abhishek; Shah, Trushar M.; Telluri, Mohan; Amindala, BhanuPrakash; Ruperao, Pradeep; Katta, Mohan A. V. S. K.; Varshney, Rajeev K.
2014-01-01
Open source single nucleotide polymorphism (SNP) discovery pipelines for next generation sequencing data commonly requires working knowledge of command line interface, massive computational resources and expertise which is a daunting task for biologists. Further, the SNP information generated may not be readily used for downstream processes such as genotyping. Hence, a comprehensive pipeline has been developed by integrating several open source next generation sequencing (NGS) tools along with a graphical user interface called Integrated SNP Mining and Utilization (ISMU) for SNP discovery and their utilization by developing genotyping assays. The pipeline features functionalities such as pre-processing of raw data, integration of open source alignment tools (Bowtie2, BWA, Maq, NovoAlign and SOAP2), SNP prediction (SAMtools/SOAPsnp/CNS2snp and CbCC) methods and interfaces for developing genotyping assays. The pipeline outputs a list of high quality SNPs between all pairwise combinations of genotypes analyzed, in addition to the reference genome/sequence. Visualization tools (Tablet and Flapjack) integrated into the pipeline enable inspection of the alignment and errors, if any. The pipeline also provides a confidence score or polymorphism information content value with flanking sequences for identified SNPs in standard format required for developing marker genotyping (KASP and Golden Gate) assays. The pipeline enables users to process a range of NGS datasets such as whole genome re-sequencing, restriction site associated DNA sequencing and transcriptome sequencing data at a fast speed. The pipeline is very useful for plant genetics and breeding community with no computational expertise in order to discover SNPs and utilize in genomics, genetics and breeding studies. The pipeline has been parallelized to process huge datasets of next generation sequencing. It has been developed in Java language and is available at http://hpc.icrisat.cgiar.org/ISMU as a standalone free software. PMID:25003610
SNPranker 2.0: a gene-centric data mining tool for diseases associated SNP prioritization in GWAS.
Merelli, Ivan; Calabria, Andrea; Cozzi, Paolo; Viti, Federica; Mosca, Ettore; Milanesi, Luciano
2013-01-01
The capability of correlating specific genotypes with human diseases is a complex issue in spite of all advantages arisen from high-throughput technologies, such as Genome Wide Association Studies (GWAS). New tools for genetic variants interpretation and for Single Nucleotide Polymorphisms (SNPs) prioritization are actually needed. Given a list of the most relevant SNPs statistically associated to a specific pathology as result of a genotype study, a critical issue is the identification of genes that are effectively related to the disease by re-scoring the importance of the identified genetic variations. Vice versa, given a list of genes, it can be of great importance to predict which SNPs can be involved in the onset of a particular disease, in order to focus the research on their effects. We propose a new bioinformatics approach to support biological data mining in the analysis and interpretation of SNPs associated to pathologies. This system can be employed to design custom genotyping chips for disease-oriented studies and to re-score GWAS results. The proposed method relies (1) on the data integration of public resources using a gene-centric database design, (2) on the evaluation of a set of static biomolecular annotations, defined as features, and (3) on the SNP scoring function, which computes SNP scores using parameters and weights set by users. We employed a machine learning classifier to set default feature weights and an ontological annotation layer to enable the enrichment of the input gene set. We implemented our method as a web tool called SNPranker 2.0 (http://www.itb.cnr.it/snpranker), improving our first published release of this system. A user-friendly interface allows the input of a list of genes, SNPs or a biological process, and to customize the features set with relative weights. As result, SNPranker 2.0 returns a list of SNPs, localized within input and ontologically enriched genes, combined with their prioritization scores. Different databases and resources are already available for SNPs annotation, but they do not prioritize or re-score SNPs relying on a-priori biomolecular knowledge. SNPranker 2.0 attempts to fill this gap through a user-friendly integrated web resource. End users, such as researchers in medical genetics and epidemiology, may find in SNPranker 2.0 a new tool for data mining and interpretation able to support SNPs analysis. Possible scenarios are GWAS data re-scoring, SNPs selection for custom genotyping arrays and SNPs/diseases association studies.
snpTree--a web-server to identify and construct SNP trees from whole genome sequence data.
Leekitcharoenphon, Pimlapas; Kaas, Rolf S; Thomsen, Martin Christen Frølund; Friis, Carsten; Rasmussen, Simon; Aarestrup, Frank M
2012-01-01
The advances and decreasing economical cost of whole genome sequencing (WGS), will soon make this technology available for routine infectious disease epidemiology. In epidemiological studies, outbreak isolates have very little diversity and require extensive genomic analysis to differentiate and classify isolates. One of the successfully and broadly used methods is analysis of single nucletide polymorphisms (SNPs). Currently, there are different tools and methods to identify SNPs including various options and cut-off values. Furthermore, all current methods require bioinformatic skills. Thus, we lack a standard and simple automatic tool to determine SNPs and construct phylogenetic tree from WGS data. Here we introduce snpTree, a server for online-automatic SNPs analysis. This tool is composed of different SNPs analysis suites, perl and python scripts. snpTree can identify SNPs and construct phylogenetic trees from WGS as well as from assembled genomes or contigs. WGS data in fastq format are aligned to reference genomes by BWA while contigs in fasta format are processed by Nucmer. SNPs are concatenated based on position on reference genome and a tree is constructed from concatenated SNPs using FastTree and a perl script. The online server was implemented by HTML, Java and python script.The server was evaluated using four published bacterial WGS data sets (V. cholerae, S. aureus CC398, S. Typhimurium and M. tuberculosis). The evaluation results for the first three cases was consistent and concordant for both raw reads and assembled genomes. In the latter case the original publication involved extensive filtering of SNPs, which could not be repeated using snpTree. The snpTree server is an easy to use option for rapid standardised and automatic SNP analysis in epidemiological studies also for users with limited bioinformatic experience. The web server is freely accessible at http://www.cbs.dtu.dk/services/snpTree-1.0/.
SNPServer: a real-time SNP discovery tool.
Savage, David; Batley, Jacqueline; Erwin, Tim; Logan, Erica; Love, Christopher G; Lim, Geraldine A C; Mongin, Emmanuel; Barker, Gary; Spangenberg, German C; Edwards, David
2005-07-01
SNPServer is a real-time flexible tool for the discovery of SNPs (single nucleotide polymorphisms) within DNA sequence data. The program uses BLAST, to identify related sequences, and CAP3, to cluster and align these sequences. The alignments are parsed to the SNP discovery software autoSNP, a program that detects SNPs and insertion/deletion polymorphisms (indels). Alternatively, lists of related sequences or pre-assembled sequences may be entered for SNP discovery. SNPServer and autoSNP use redundancy to differentiate between candidate SNPs and sequence errors. For each candidate SNP, two measures of confidence are calculated, the redundancy of the polymorphism at a SNP locus and the co-segregation of the candidate SNP with other SNPs in the alignment. SNPServer is available at http://hornbill.cspp.latrobe.edu.au/snpdiscovery.html.
Discovery of 20,000 RAD-SNPs and development of a 52-SNP array for monitoring river otters
Jeffrey B. Stetz; Seth Smith; Michael A. Sawaya; Alan B. Ramsey; Stephen J. Amish; Michael K. Schwartz; Gordon Luikart
2016-01-01
Many North American river otter (Lontra canadensis) populations are threatened or recovering but are difficult to study because they occur at low densities, it is difficult to visually identify individuals, and they inhabit aquatic environments that accelerate degradation of biological samples. Single nucleotide polymorphisms (SNPs) can improve our ability to...
Manickam, Madhumathi; Ravanan, Palaniyandi; Singh, Pratibha; Talwar, Priti
2014-01-01
Gaucher's disease (GD) is an autosomal recessive disorder caused by the deficiency of glucocerebrosidase, a lysosomal enzyme that catalyses the hydrolysis of the glycolipid glucocerebroside to ceramide and glucose. Polymorphisms in GBA gene have been associated with the development of Gaucher disease. We hypothesize that prediction of SNPs using multiple state of the art software tools will help in increasing the confidence in identification of SNPs involved in GD. Enzyme replacement therapy is the only option for GD. Our goal is to use several state of art SNP algorithms to predict/address harmful SNPs using comparative studies. In this study seven different algorithms (SIFT, MutPred, nsSNP Analyzer, PANTHER, PMUT, PROVEAN, and SNPs&GO) were used to predict the harmful polymorphisms. Among the seven programs, SIFT found 47 nsSNPs as deleterious, MutPred found 46 nsSNPs as harmful. nsSNP Analyzer program found 43 out of 47 nsSNPs are disease causing SNPs whereas PANTHER found 32 out of 47 as highly deleterious, 22 out of 47 are classified as pathological mutations by PMUT, 44 out of 47 were predicted to be deleterious by PROVEAN server, all 47 shows the disease related mutations by SNPs&GO. Twenty two nsSNPs were commonly predicted by all the seven different algorithms. The common 22 targeted mutations are F251L, C342G, W312C, P415R, R463C, D127V, A309V, G46E, G202E, P391L, Y363C, Y205C, W378C, I402T, S366R, F397S, Y418C, P401L, G195E, W184R, R48W, and T43R.
Yang, Peng; Wu, Min; Guo, Jing; Kwoh, Chee Keong; Przytycka, Teresa M; Zheng, Jie
2014-02-17
As a fundamental genomic element, meiotic recombination hotspot plays important roles in life sciences. Thus uncovering its regulatory mechanisms has broad impact on biomedical research. Despite the recent identification of the zinc finger protein PRDM9 and its 13-mer binding motif as major regulators for meiotic recombination hotspots, other regulators remain to be discovered. Existing methods for finding DNA sequence motifs of recombination hotspots often rely on the enrichment of co-localizations between hotspots and short DNA patterns, which ignore the cross-individual variation of recombination rates and sequence polymorphisms in the population. Our objective in this paper is to capture signals encoded in genetic variations for the discovery of recombination-associated DNA motifs. Recently, an algorithm called "LDsplit" has been designed to detect the association between single nucleotide polymorphisms (SNPs) and proximal meiotic recombination hotspots. The association is measured by the difference of population recombination rates at a hotspot between two alleles of a candidate SNP. Here we present an open source software tool of LDsplit, with integrative data visualization for recombination hotspots and their proximal SNPs. Applying LDsplit on SNPs inside an established 7-mer motif bound by PRDM9 we observed that SNP alleles preserving the original motif tend to have higher recombination rates than the opposite alleles that disrupt the motif. Running on SNP windows around hotspots each containing an occurrence of the 7-mer motif, LDsplit is able to guide the established motif finding algorithm of MEME to recover the 7-mer motif. In contrast, without LDsplit the 7-mer motif could not be identified. LDsplit is a software tool for the discovery of cis-regulatory DNA sequence motifs stimulating meiotic recombination hotspots by screening and narrowing down to hotspot associated SNPs. It is the first computational method that utilizes the genetic variation of recombination hotspots among individuals, opening a new avenue for motif finding. Tested on an established motif and simulated datasets, LDsplit shows promise to discover novel DNA motifs for meiotic recombination hotspots.
2014-01-01
Background As a fundamental genomic element, meiotic recombination hotspot plays important roles in life sciences. Thus uncovering its regulatory mechanisms has broad impact on biomedical research. Despite the recent identification of the zinc finger protein PRDM9 and its 13-mer binding motif as major regulators for meiotic recombination hotspots, other regulators remain to be discovered. Existing methods for finding DNA sequence motifs of recombination hotspots often rely on the enrichment of co-localizations between hotspots and short DNA patterns, which ignore the cross-individual variation of recombination rates and sequence polymorphisms in the population. Our objective in this paper is to capture signals encoded in genetic variations for the discovery of recombination-associated DNA motifs. Results Recently, an algorithm called “LDsplit” has been designed to detect the association between single nucleotide polymorphisms (SNPs) and proximal meiotic recombination hotspots. The association is measured by the difference of population recombination rates at a hotspot between two alleles of a candidate SNP. Here we present an open source software tool of LDsplit, with integrative data visualization for recombination hotspots and their proximal SNPs. Applying LDsplit on SNPs inside an established 7-mer motif bound by PRDM9 we observed that SNP alleles preserving the original motif tend to have higher recombination rates than the opposite alleles that disrupt the motif. Running on SNP windows around hotspots each containing an occurrence of the 7-mer motif, LDsplit is able to guide the established motif finding algorithm of MEME to recover the 7-mer motif. In contrast, without LDsplit the 7-mer motif could not be identified. Conclusions LDsplit is a software tool for the discovery of cis-regulatory DNA sequence motifs stimulating meiotic recombination hotspots by screening and narrowing down to hotspot associated SNPs. It is the first computational method that utilizes the genetic variation of recombination hotspots among individuals, opening a new avenue for motif finding. Tested on an established motif and simulated datasets, LDsplit shows promise to discover novel DNA motifs for meiotic recombination hotspots. PMID:24533858
SNPit: a federated data integration system for the purpose of functional SNP annotation.
Shen, Terry H; Carlson, Christopher S; Tarczy-Hornoch, Peter
2009-08-01
Genome wide association studies can potentially identify the genetic causes behind the majority of human diseases. With the advent of more advanced genotyping techniques, there is now an explosion of data gathered on single nucleotide polymorphisms (SNPs). The need exists for an integrated system that can provide up-to-date functional annotation information on SNPs. We have developed the SNP Integration Tool (SNPit) system to address this need. Built upon a federated data integration system, SNPit provides current information on a comprehensive list of SNP data sources. Additional logical inference analysis was included through an inference engine plug in. The SNPit web servlet is available online for use. SNPit allows users to go to one source for up-to-date information on the functional annotation of SNPs. A tool that can help to integrate and analyze the potential functional significance of SNPs is important for understanding the results from genome wide association studies.
The coffee genome hub: a resource for coffee genomes
Dereeper, Alexis; Bocs, Stéphanie; Rouard, Mathieu; Guignon, Valentin; Ravel, Sébastien; Tranchant-Dubreuil, Christine; Poncet, Valérie; Garsmeur, Olivier; Lashermes, Philippe; Droc, Gaëtan
2015-01-01
The whole genome sequence of Coffea canephora, the perennial diploid species known as Robusta, has been recently released. In the context of the C. canephora genome sequencing project and to support post-genomics efforts, we developed the Coffee Genome Hub (http://coffee-genome.org/), an integrative genome information system that allows centralized access to genomics and genetics data and analysis tools to facilitate translational and applied research in coffee. We provide the complete genome sequence of C. canephora along with gene structure, gene product information, metabolism, gene families, transcriptomics, syntenic blocks, genetic markers and genetic maps. The hub relies on generic software (e.g. GMOD tools) for easy querying, visualizing and downloading research data. It includes a Genome Browser enhanced by a Community Annotation System, enabling the improvement of automatic gene annotation through an annotation editor. In addition, the hub aims at developing interoperability among other existing South Green tools managing coffee data (phylogenomics resources, SNPs) and/or supporting data analyses with the Galaxy workflow manager. PMID:25392413
Zhao, Nan; Han, Jing Ginger; Shyu, Chi-Ren; Korkin, Dmitry
2014-01-01
Single nucleotide polymorphisms (SNPs) are among the most common types of genetic variation in complex genetic disorders. A growing number of studies link the functional role of SNPs with the networks and pathways mediated by the disease-associated genes. For example, many non-synonymous missense SNPs (nsSNPs) have been found near or inside the protein-protein interaction (PPI) interfaces. Determining whether such nsSNP will disrupt or preserve a PPI is a challenging task to address, both experimentally and computationally. Here, we present this task as three related classification problems, and develop a new computational method, called the SNP-IN tool (non-synonymous SNP INteraction effect predictor). Our method predicts the effects of nsSNPs on PPIs, given the interaction's structure. It leverages supervised and semi-supervised feature-based classifiers, including our new Random Forest self-learning protocol. The classifiers are trained based on a dataset of comprehensive mutagenesis studies for 151 PPI complexes, with experimentally determined binding affinities of the mutant and wild-type interactions. Three classification problems were considered: (1) a 2-class problem (strengthening/weakening PPI mutations), (2) another 2-class problem (mutations that disrupt/preserve a PPI), and (3) a 3-class classification (detrimental/neutral/beneficial mutation effects). In total, 11 different supervised and semi-supervised classifiers were trained and assessed resulting in a promising performance, with the weighted f-measure ranging from 0.87 for Problem 1 to 0.70 for the most challenging Problem 3. By integrating prediction results of the 2-class classifiers into the 3-class classifier, we further improved its performance for Problem 3. To demonstrate the utility of SNP-IN tool, it was applied to study the nsSNP-induced rewiring of two disease-centered networks. The accurate and balanced performance of SNP-IN tool makes it readily available to study the rewiring of large-scale protein-protein interaction networks, and can be useful for functional annotation of disease-associated SNPs. SNIP-IN tool is freely accessible as a web-server at http://korkinlab.org/snpintool/. PMID:24784581
LEAP: biomarker inference through learning and evaluating association patterns.
Jiang, Xia; Neapolitan, Richard E
2015-03-01
Single nucleotide polymorphism (SNP) high-dimensional datasets are available from Genome Wide Association Studies (GWAS). Such data provide researchers opportunities to investigate the complex genetic basis of diseases. Much of genetic risk might be due to undiscovered epistatic interactions, which are interactions in which combination of several genes affect disease. Research aimed at discovering interacting SNPs from GWAS datasets proceeded in two directions. First, tools were developed to evaluate candidate interactions. Second, algorithms were developed to search over the space of candidate interactions. Another problem when learning interacting SNPs, which has not received much attention, is evaluating how likely it is that the learned SNPs are associated with the disease. A complete system should provide this information as well. We develop such a system. Our system, called LEAP, includes a new heuristic search algorithm for learning interacting SNPs, and a Bayesian network based algorithm for computing the probability of their association. We evaluated the performance of LEAP using 100 1,000-SNP simulated datasets, each of which contains 15 SNPs involved in interactions. When learning interacting SNPs from these datasets, LEAP outperformed seven others methods. Furthermore, only SNPs involved in interactions were found to be probable. We also used LEAP to analyze real Alzheimer's disease and breast cancer GWAS datasets. We obtained interesting and new results from the Alzheimer's dataset, but limited results from the breast cancer dataset. We conclude that our results support that LEAP is a useful tool for extracting candidate interacting SNPs from high-dimensional datasets and determining their probability. © 2015 The Authors. *Genetic Epidemiology published by Wiley Periodicals, Inc.
EvoSNP-DB: A database of genetic diversity in East Asian populations.
Kim, Young Uk; Kim, Young Jin; Lee, Jong-Young; Park, Kiejung
2013-08-01
Genome-wide association studies (GWAS) have become popular as an approach for the identification of large numbers of phenotype-associated variants. However, differences in genetic architecture and environmental factors mean that the effect of variants can vary across populations. Understanding population genetic diversity is valuable for the investigation of possible population specific and independent effects of variants. EvoSNP-DB aims to provide information regarding genetic diversity among East Asian populations, including Chinese, Japanese, and Korean. Non-redundant SNPs (1.6 million) were genotyped in 54 Korean trios (162 samples) and were compared with 4 million SNPs from HapMap phase II populations. EvoSNP-DB provides two user interfaces for data query and visualization, and integrates scores of genetic diversity (Fst and VarLD) at the level of SNPs, genes, and chromosome regions. EvoSNP-DB is a web-based application that allows users to navigate and visualize measurements of population genetic differences in an interactive manner, and is available online at [http://biomi.cdc.go.kr/EvoSNP/].
VizPrimer: a web server for visualized PCR primer design based on known gene structure.
Zhou, Yang; Qu, Wubin; Lu, Yiming; Zhang, Yanchun; Wang, Xiaolei; Zhao, Dongsheng; Yang, Yi; Zhang, Chenggang
2011-12-15
The visualization of gene structure plays an important role in polymerase chain reaction (PCR) primer design, especially for eukaryotic genes with a number of splice variants that users need to distinguish between via PCR. Here, we describe a visualized web server for primer design named VizPrimer. It utilizes the new information technology (IT) tools, HTML5 to display gene structure and JavaScript to interact with the users. In VizPrimer, the users can focus their attention on the gene structure and primer design strategy, without wasting time calculating the exon positions of splice variants or manually configuring complicated parameters. In addition, VizPrimer is also suitable for the design of PCR primers for amplifying open reading frames and detecting single nucleotide polymorphisms (SNPs). VizPrimer is freely available at http://biocompute.bmi.ac.cn/CZlab/VizPrimer/. The web server supported browsers: Chrome (≥5.0), Firefox (≥3.0), Safari (≥4.0) and Opera (≥10.0). zhangcg@bmi.ac.cn; yangyi528@vip.sina.com.
SNPit: a federated data integration system for the purpose of functional SNP annotation
Shen, Terry H; Carlson, Christopher S; Tarczy-Hornoch, Peter
2009-01-01
Genome wide association studies can potentially identify the genetic causes behind the majority of human diseases. With the advent of more advanced genotyping techniques, there is now an explosion of data gathered on single nucleotide polymorphisms (SNPs). The need exists for an integrated system that can provide up-to-date functional annotation information on SNPs. We have developed the SNP Integration Tool (SNPit) system to address this need. Built upon a federated data integration system, SNPit provides current information on a comprehensive list of SNP data sources. Additional logical inference analysis was included through an inference engine plug in. The SNPit web servlet is available online for use. SNPit allows users to go to one source for up-to-date information on the functional annotation of SNPs. A tool that can help to integrate and analyze the potential functional significance of SNPs is important for understanding the results from genome wide association studies. PMID:19327864
High throughput SNP discovery and genotyping in hexaploid wheat.
Rimbert, Hélène; Darrier, Benoît; Navarro, Julien; Kitt, Jonathan; Choulet, Frédéric; Leveugle, Magalie; Duarte, Jorge; Rivière, Nathalie; Eversole, Kellye; Le Gouis, Jacques; Davassi, Alessandro; Balfourier, François; Le Paslier, Marie-Christine; Berard, Aurélie; Brunel, Dominique; Feuillet, Catherine; Poncet, Charles; Sourdille, Pierre; Paux, Etienne
2018-01-01
Because of their abundance and their amenability to high-throughput genotyping techniques, Single Nucleotide Polymorphisms (SNPs) are powerful tools for efficient genetics and genomics studies, including characterization of genetic resources, genome-wide association studies and genomic selection. In wheat, most of the previous SNP discovery initiatives targeted the coding fraction, leaving almost 98% of the wheat genome largely unexploited. Here we report on the use of whole-genome resequencing data from eight wheat lines to mine for SNPs in the genic, the repetitive and non-repetitive intergenic fractions of the wheat genome. Eventually, we identified 3.3 million SNPs, 49% being located on the B-genome, 41% on the A-genome and 10% on the D-genome. We also describe the development of the TaBW280K high-throughput genotyping array containing 280,226 SNPs. Performance of this chip was examined by genotyping a set of 96 wheat accessions representing the worldwide diversity. Sixty-nine percent of the SNPs can be efficiently scored, half of them showing a diploid-like clustering. The TaBW280K was proven to be a very efficient tool for diversity analyses, as well as for breeding as it can discriminate between closely related elite varieties. Finally, the TaBW280K array was used to genotype a population derived from a cross between Chinese Spring and Renan, leading to the construction a dense genetic map comprising 83,721 markers. The results described here will provide the wheat community with powerful tools for both basic and applied research.
CAS-viewer: web-based tool for splicing-guided integrative analysis of multi-omics cancer data.
Han, Seonggyun; Kim, Dongwook; Kim, Youngjun; Choi, Kanghoon; Miller, Jason E; Kim, Dokyoon; Lee, Younghee
2018-04-20
The Cancer Genome Atlas (TCGA) project is a public resource that provides transcriptomic, DNA sequence, methylation, and clinical data for 33 cancer types. Transforming the large size and high complexity of TCGA cancer genome data into integrated knowledge can be useful to promote cancer research. Alternative splicing (AS) is a key regulatory mechanism of genes in human cancer development and in the interaction with epigenetic factors. Therefore, AS-guided integration of existing TCGA data sets will make it easier to gain insight into the genetic architecture of cancer risk and related outcomes. There are already existing tools analyzing and visualizing alternative mRNA splicing patterns for large-scale RNA-seq experiments. However, these existing web-based tools are limited to the analysis of individual TCGA data sets at a time, such as only transcriptomic information. We implemented CAS-viewer (integrative analysis of Cancer genome data based on Alternative Splicing), a web-based tool leveraging multi-cancer omics data from TCGA. It illustrates alternative mRNA splicing patterns along with methylation, miRNAs, and SNPs, and then provides an analysis tool to link differential transcript expression ratio to methylation, miRNA, and splicing regulatory elements for 33 cancer types. Moreover, one can analyze AS patterns with clinical data to identify potential transcripts associated with different survival outcome for each cancer. CAS-viewer is a web-based application for transcript isoform-driven integration of multi-omics data in multiple cancer types and will aid in the visualization and possible discovery of biomarkers for cancer by integrating multi-omics data from TCGA.
VarDetect: a nucleotide sequence variation exploratory tool
Ngamphiw, Chumpol; Kulawonganunchai, Supasak; Assawamakin, Anunchai; Jenwitheesuk, Ekachai; Tongsima, Sissades
2008-01-01
Background Single nucleotide polymorphisms (SNPs) are the most commonly studied units of genetic variation. The discovery of such variation may help to identify causative gene mutations in monogenic diseases and SNPs associated with predisposing genes in complex diseases. Accurate detection of SNPs requires software that can correctly interpret chromatogram signals to nucleotides. Results We present VarDetect, a stand-alone nucleotide variation exploratory tool that automatically detects nucleotide variation from fluorescence based chromatogram traces. Accurate SNP base-calling is achieved using pre-calculated peak content ratios, and is enhanced by rules which account for common sequence reading artifacts. The proposed software tool is benchmarked against four other well-known SNP discovery software tools (PolyPhred, novoSNP, Genalys and Mutation Surveyor) using fluorescence based chromatograms from 15 human genes. These chromatograms were obtained from sequencing 16 two-pooled DNA samples; a total of 32 individual DNA samples. In this comparison of automatic SNP detection tools, VarDetect achieved the highest detection efficiency. Availability VarDetect is compatible with most major operating systems such as Microsoft Windows, Linux, and Mac OSX. The current version of VarDetect is freely available at . PMID:19091032
Singh, Kh Dhanachandra; Karthikeyan, Muthusamy
2014-12-01
The renin-angiotensin-aldosterone system (RAAS) plays a key role in the regulation of blood pressure (BP). Mutations on the genes that encode components of the RAAS have played a significant role in genetic susceptibility to hypertension and have been intensively scrutinized. The identification of such probably causal mutations not only provides insight into the RAAS but may also serve as antihypertensive therapeutic targets and diagnostic markers. The methods for analyzing the SNPs from the huge dataset of SNPs, containing both functional and neutral SNPs is challenging by the experimental approach on every SNPs to determine their biological significance. To explore the functional significance of genetic mutation (SNPs), we adopted combined sequence and sequence-structure-based SNP analysis algorithm. Out of 3864 SNPs reported in dbSNP, we found 108 missense SNPs in the coding region and remaining in the non-coding region. In this study, we are reporting only those SNPs in coding region to be deleterious when three or more tools are predicted to be deleterious and which have high RMSD from the native structure. Based on these analyses, we have identified two SNPs of REN gene, eight SNPs of AGT gene, three SNPs of ACE gene, two SNPs of AT1R gene, three SNPs of CYP11B2 gene and three SNPs of CMA1 gene in the coding region were found to be deleterious. Further this type of study will be helpful in reducing the cost and time for identification of potential SNP and also helpful in selecting potential SNP for experimental study out of SNP pool.
LS-SNP/PDB: annotated non-synonymous SNPs mapped to Protein Data Bank structures.
Ryan, Michael; Diekhans, Mark; Lien, Stephanie; Liu, Yun; Karchin, Rachel
2009-06-01
LS-SNP/PDB is a new WWW resource for genome-wide annotation of human non-synonymous (amino acid changing) SNPs. It serves high-quality protein graphics rendered with UCSF Chimera molecular visualization software. The system is kept up-to-date by an automated, high-throughput build pipeline that systematically maps human nsSNPs onto Protein Data Bank structures and annotates several biologically relevant features. LS-SNP/PDB is available at (http://ls-snp.icm.jhu.edu/ls-snp-pdb) and via links from protein data bank (PDB) biology and chemistry tabs, UCSC Genome Browser Gene Details and SNP Details pages and PharmGKB Gene Variants Downloads/Cross-References pages.
Valdisser, Paula Arielle M R; Pappas, Georgios J; de Menezes, Ivandilson P P; Müller, Bárbara S F; Pereira, Wendell J; Narciso, Marcelo G; Brondani, Claudio; Souza, Thiago L P O; Borba, Tereza C O; Vianello, Rosana P
2016-06-01
Researchers have made great advances into the development and application of genomic approaches for common beans, creating opportunities to driving more real and applicable strategies for sustainable management of the genetic resource towards plant breeding. This work provides useful polymorphic single-nucleotide polymorphisms (SNPs) for high-throughput common bean genotyping developed by RAD (restriction site-associated DNA) sequencing. The RAD tags were generated from DNA pooled from 12 common bean genotypes, including breeding lines of different gene pools and market classes. The aligned sequences identified 23,748 putative RAD-SNPs, of which 3357 were adequate for genotyping; 1032 RAD-SNPs with the highest ADT (assay design tool) score are presented in this article. The RAD-SNPs were structurally annotated in different coding (47.00 %) and non-coding (53.00 %) sequence components of genes. A subset of 384 RAD-SNPs with broad genome distribution was used to genotype a diverse panel of 95 common bean germplasms and revealed a successful amplification rate of 96.6 %, showing 73 % of polymorphic SNPs within the Andean group and 83 % in the Mesoamerican group. A slightly increased He (0.161, n = 21) value was estimated for the Andean gene pool, compared to the Mesoamerican group (0.156, n = 74). For the linkage disequilibrium (LD) analysis, from a group of 580 SNPs (289 RAD-SNPs and 291 BARC-SNPs) genotyped for the same set of genotypes, 70.2 % were in LD, decreasing to 0.10 %in the Andean group and 0.77 % in the Mesoamerican group. Haplotype patterns spanning 310 Mb of the genome (60 %) were characterized in samples from different origins. However, the haplotype frameworks were under-represented for the Andean (7.85 %) and Mesoamerican (5.55 %) gene pools separately. In conclusion, RAD sequencing allowed the discovery of hundreds of useful SNPs for broad genetic analysis of common bean germplasm. From now, this approach provides an excellent panel of molecular tools for whole genome analysis, allowing integrating and better exploring the common bean breeding practices.
High throughput SNP discovery and genotyping in hexaploid wheat
Navarro, Julien; Kitt, Jonathan; Choulet, Frédéric; Leveugle, Magalie; Duarte, Jorge; Rivière, Nathalie; Eversole, Kellye; Le Gouis, Jacques; Davassi, Alessandro; Balfourier, François; Le Paslier, Marie-Christine; Berard, Aurélie; Brunel, Dominique; Feuillet, Catherine; Poncet, Charles; Sourdille, Pierre
2018-01-01
Because of their abundance and their amenability to high-throughput genotyping techniques, Single Nucleotide Polymorphisms (SNPs) are powerful tools for efficient genetics and genomics studies, including characterization of genetic resources, genome-wide association studies and genomic selection. In wheat, most of the previous SNP discovery initiatives targeted the coding fraction, leaving almost 98% of the wheat genome largely unexploited. Here we report on the use of whole-genome resequencing data from eight wheat lines to mine for SNPs in the genic, the repetitive and non-repetitive intergenic fractions of the wheat genome. Eventually, we identified 3.3 million SNPs, 49% being located on the B-genome, 41% on the A-genome and 10% on the D-genome. We also describe the development of the TaBW280K high-throughput genotyping array containing 280,226 SNPs. Performance of this chip was examined by genotyping a set of 96 wheat accessions representing the worldwide diversity. Sixty-nine percent of the SNPs can be efficiently scored, half of them showing a diploid-like clustering. The TaBW280K was proven to be a very efficient tool for diversity analyses, as well as for breeding as it can discriminate between closely related elite varieties. Finally, the TaBW280K array was used to genotype a population derived from a cross between Chinese Spring and Renan, leading to the construction a dense genetic map comprising 83,721 markers. The results described here will provide the wheat community with powerful tools for both basic and applied research. PMID:29293495
Mapping a Mutation in "Caenorhabditis elegans" Using a Polymerase Chain Reaction-Based Approach
ERIC Educational Resources Information Center
Myers, Edith M.
2014-01-01
Many single nucleotide polymorphisms (SNPs) have been identified within the "Caenorhabditis elegans" genome. SNPs present in the genomes of two isogenic "C. elegans" strains have been routinely used as a tool in forward genetics to map a mutation to a particular chromosome. This article describes a laboratory exercise in which…
GenPlay Multi-Genome, a tool to compare and analyze multiple human genomes in a graphical interface.
Lajugie, Julien; Fourel, Nicolas; Bouhassira, Eric E
2015-01-01
Parallel visualization of multiple individual human genomes is a complex endeavor that is rapidly gaining importance with the increasing number of personal, phased and cancer genomes that are being generated. It requires the display of variants such as SNPs, indels and structural variants that are unique to specific genomes and the introduction of multiple overlapping gaps in the reference sequence. Here, we describe GenPlay Multi-Genome, an application specifically written to visualize and analyze multiple human genomes in parallel. GenPlay Multi-Genome is ideally suited for the comparison of allele-specific expression and functional genomic data obtained from multiple phased genomes in a graphical interface with access to multiple-track operation. It also allows the analysis of data that have been aligned to custom genomes rather than to a standard reference and can be used as a variant calling format file browser and as a tool to compare different genome assembly, such as hg19 and hg38. GenPlay is available under the GNU public license (GPL-3) from http://genplay.einstein.yu.edu. The source code is available at https://github.com/JulienLajugie/GenPlay. © The Author 2014. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.
Development of a set of SNP markers present in expressed genes of the apple.
Chagné, David; Gasic, Ksenija; Crowhurst, Ross N; Han, Yuepeng; Bassett, Heather C; Bowatte, Deepa R; Lawrence, Timothy J; Rikkerink, Erik H A; Gardiner, Susan E; Korban, Schuyler S
2008-11-01
Molecular markers associated with gene coding regions are useful tools for bridging functional and structural genomics. Due to their high abundance in plant genomes, single nucleotide polymorphisms (SNPs) are present within virtually all genomic regions, including most coding sequences. The objective of this study was to develop a set of SNPs for the apple by taking advantage of the wealth of genomics resources available for the apple, including a large collection of expressed sequenced tags (ESTs). Using bioinformatics tools, a search for SNPs within an EST database of approximately 350,000 sequences developed from a variety of apple accessions was conducted. This resulted in the identification of a total of 71,482 putative SNPs. As the apple genome is reported to be an ancient polyploid, attempts were made to verify whether those SNPs detected in silico were attributable either to allelic polymorphisms or to gene duplication or paralogous or homeologous sequence variations. To this end, a set of 464 PCR primer pairs was designed, PCR was amplified using two subsets of plants, and the PCR products were sequenced. The SNPs retrieved from these sequences were then mapped onto apple genetic maps, including a newly constructed map of a Royal Gala x A689-24 cross and a Malling 9 x Robusta 5, map using a bin mapping strategy. The SNP genotyping was performed using the high-resolution melting (HRM) technique. A total of 93 new markers containing 210 coding SNPs were successfully mapped. This new set of SNP markers for the apple offers new opportunities for understanding the genetic control of important horticultural traits using quantitative trait loci (QTL) or linkage disequilibrium analysis. These also serve as useful markers for aligning physical and genetic maps, and as potential transferable markers across the Rosaceae family.
Novel and efficient tag SNPs selection algorithms.
Chen, Wen-Pei; Hung, Che-Lun; Tsai, Suh-Jen Jane; Lin, Yaw-Ling
2014-01-01
SNPs are the most abundant forms of genetic variations amongst species; the association studies between complex diseases and SNPs or haplotypes have received great attention. However, these studies are restricted by the cost of genotyping all SNPs; thus, it is necessary to find smaller subsets, or tag SNPs, representing the rest of the SNPs. In fact, the existing tag SNP selection algorithms are notoriously time-consuming. An efficient algorithm for tag SNP selection was presented, which was applied to analyze the HapMap YRI data. The experimental results show that the proposed algorithm can achieve better performance than the existing tag SNP selection algorithms; in most cases, this proposed algorithm is at least ten times faster than the existing methods. In many cases, when the redundant ratio of the block is high, the proposed algorithm can even be thousands times faster than the previously known methods. Tools and web services for haplotype block analysis integrated by hadoop MapReduce framework are also developed using the proposed algorithm as computation kernels.
SNP ID-info: SNP ID searching and visualization platform.
Yang, Cheng-Hong; Chuang, Li-Yeh; Cheng, Yu-Huei; Wen, Cheng-Hao; Chang, Phei-Lang; Chang, Hsueh-Wei
2008-09-01
Many association studies provide the relationship between single nucleotide polymorphisms (SNPs), diseases and cancers, without giving a SNP ID, however. Here, we developed the SNP ID-info freeware to provide the SNP IDs within inputting genetic and physical information of genomes. The program provides an "SNP-ePCR" function to generate the full-sequence using primers and template inputs. In "SNPosition," sequence from SNP-ePCR or direct input is fed to match the SNP IDs from SNP fasta-sequence. In "SNP search" and "SNP fasta" function, information of SNPs within the cytogenetic band, contig position, and keyword input are acceptable. Finally, the SNP ID neighboring environment for inputs is completely visualized in the order of contig position and marked with SNP and flanking hits. The SNP identification problems inherent in NCBI SNP BLAST are also avoided. In conclusion, the SNP ID-info provides a visualized SNP ID environment for multiple inputs and assists systematic SNP association studies. The server and user manual are available at http://bio.kuas.edu.tw/snpid-info.
Lepoittevin, Camille; Frigerio, Jean-Marc; Garnier-Géré, Pauline; Salin, Franck; Cervera, María-Teresa; Vornam, Barbara; Harvengt, Luc; Plomion, Christophe
2010-01-01
Background There is considerable interest in the high-throughput discovery and genotyping of single nucleotide polymorphisms (SNPs) to accelerate genetic mapping and enable association studies. This study provides an assessment of EST-derived and resequencing-derived SNP quality in maritime pine (Pinus pinaster Ait.), a conifer characterized by a huge genome size (∼23.8 Gb/C). Methodology/Principal Findings A 384-SNPs GoldenGate genotyping array was built from i/ 184 SNPs originally detected in a set of 40 re-sequenced candidate genes (in vitro SNPs), chosen on the basis of functionality scores, presence of neighboring polymorphisms, minor allele frequencies and linkage disequilibrium and ii/ 200 SNPs screened from ESTs (in silico SNPs) selected based on the number of ESTs used for SNP detection, the SNP minor allele frequency and the quality of SNP flanking sequences. The global success rate of the assay was 66.9%, and a conversion rate (considering only polymorphic SNPs) of 51% was achieved. In vitro SNPs showed significantly higher genotyping-success and conversion rates than in silico SNPs (+11.5% and +18.5%, respectively). The reproducibility was 100%, and the genotyping error rate very low (0.54%, dropping down to 0.06% when removing four SNPs showing elevated error rates). Conclusions/Significance This study demonstrates that ESTs provide a resource for SNP identification in non-model species, which do not require any additional bench work and little bio-informatics analysis. However, the time and cost benefits of in silico SNPs are counterbalanced by a lower conversion rate than in vitro SNPs. This drawback is acceptable for population-based experiments, but could be dramatic in experiments involving samples from narrow genetic backgrounds. In addition, we showed that both the visual inspection of genotyping clusters and the estimation of a per SNP error rate should help identify markers that are not suitable to the GoldenGate technology in species characterized by a large and complex genome. PMID:20543950
Allelic expression mapping across cellular lineages to establish impact of non-coding SNPs
Adoue, Veronique; Schiavi, Alicia; Light, Nicholas; Almlöf, Jonas Carlsson; Lundmark, Per; Ge, Bing; Kwan, Tony; Caron, Maxime; Rönnblom, Lars; Wang, Chuan; Chen, Shu-Huang; Goodall, Alison H; Cambien, Francois; Deloukas, Panos; Ouwehand, Willem H; Syvänen, Ann-Christine; Pastinen, Tomi
2014-01-01
Most complex disease-associated genetic variants are located in non-coding regions and are therefore thought to be regulatory in nature. Association mapping of differential allelic expression (AE) is a powerful method to identify SNPs with direct cis-regulatory impact (cis-rSNPs). We used AE mapping to identify cis-rSNPs regulating gene expression in 55 and 63 HapMap lymphoblastoid cell lines from a Caucasian and an African population, respectively, 70 fibroblast cell lines, and 188 purified monocyte samples and found 40–60% of these cis-rSNPs to be shared across cell types. We uncover a new class of cis-rSNPs, which disrupt footprint-derived de novo motifs that are predominantly bound by repressive factors and are implicated in disease susceptibility through overlaps with GWAS SNPs. Finally, we provide the proof-of-principle for a new approach for genome-wide functional validation of transcription factor–SNP interactions. By perturbing NFκB action in lymphoblasts, we identified 489 cis-regulated transcripts with altered AE after NFκB perturbation. Altogether, we perform a comprehensive analysis of cis-variation in four cell populations and provide new tools for the identification of functional variants associated to complex diseases. PMID:25326100
Wang, Lu-Yong; Fasulo, D
2006-01-01
Genome-wide association study for complex diseases will generate massive amount of single nucleotide polymorphisms (SNPs) data. Univariate statistical test (i.e. Fisher exact test) was used to single out non-associated SNPs. However, the disease-susceptible SNPs may have little marginal effects in population and are unlikely to retain after the univariate tests. Also, model-based methods are impractical for large-scale dataset. Moreover, genetic heterogeneity makes the traditional methods harder to identify the genetic causes of diseases. A more recent random forest method provides a more robust method for screening the SNPs in thousands scale. However, for more large-scale data, i.e., Affymetrix Human Mapping 100K GeneChip data, a faster screening method is required to screening SNPs in whole-genome large scale association analysis with genetic heterogeneity. We propose a boosting-based method for rapid screening in large-scale analysis of complex traits in the presence of genetic heterogeneity. It provides a relatively fast and fairly good tool for screening and limiting the candidate SNPs for further more complex computational modeling task.
Profiling deleterious non-synonymous SNPs of smoker's gene CYP1A1.
Ramesh, A Sai; Khan, Imran; Farhan, Md; Thiagarajan, Padma
2013-01-01
CYP1A1 gene belongs to the cytochrome P450 family and is known better as smokers' gene due to its hyperactivation as a consequence of long term smoking. The expression of CYP1A1 induces polycyclic aromatic hydrocarbon production in the lungs, which when over expressed, is known to cause smoking related diseases, such as cardiovascular pathologies, cancer, and diabetes. Single nucleotide polymorphisms (SNPs) are the simplest form of genetic variations that occur at a higher frequency, and are denoted as synonymous and non-synonymous SNPs on the basis of their effects on the amino acids. This study adopts a systematic in silico approach to predict the deleterious SNPs that are associated with disease conditions. It is inferred that four SNPs are highly deleterious, among which the SNP with rs17861094 is commonly predicted to be harmful by all tools. Hydrophobic (isoleucine) to hydrophilic (serine) amino acid variation was observed in the candidate gene. Hence, this investigation aims to characterize a candidate gene from 159 SNPs of CYP1A1.
SiNoPsis: Single Nucleotide Polymorphisms selection and promoter profiling.
Boloc, Daniel; Rodríguez, Natalia; Gassó, Patricia; Abril, Josep F; Bernardo, Miquel; Lafuente, Amalia; Mas, Sergi
2017-09-14
The selection of a Single Nucleotide Polymorphism (SNP) using bibliographic methods can be a very time-consuming task. Moreover, a SNP selected in this way may not be easily visualized in its genomic context by a standard user hoping to correlate it with other valuable information. Here we propose a web form built on top of Circos that can assist SNP-centred screening, based on their location in the genome and the regulatory modules they can disrupt. Its use may allow researchers to prioritize SNPs in genotyping and disease studies. SiNoPsis is bundled as a web portal. It focuses on the different structures involved in the genomic expression of a gene, especially those found in the core promoter upstream region. These structures include transcription factor binding sites (for promoter and enhancer signals), histones, and promoter flanking regions. Additionally, the tool provides eQTL and linkage disequilibrium (LD) properties for a given SNP query, yielding further clues about other indirectly associated SNPs. Possible disruptions of the aforementioned structures affecting gene transcription are reported using multiple resource databases. SiNoPsis has a simple user-friendly interface, which allows single queries by gene symbol, genomic coordinates, Ensembl gene identifiers, RefSeq transcript identifiers and SNPs. It is the only portal providing useful SNP selection based on regulatory modules and LD with functional variants in both textual and graphic modes (by properly defining the arguments and parameters needed to run Circos). SiNoPsis is freely available at https://compgen.bio.ub.edu/SiNoPsis /. © The Author (2017). Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oup.com
GrigoraSNPs: Optimized Analysis of SNPs for DNA Forensics.
Ricke, Darrell O; Shcherbina, Anna; Michaleas, Adam; Fremont-Smith, Philip
2018-04-16
High-throughput sequencing (HTS) of single nucleotide polymorphisms (SNPs) enables additional DNA forensic capabilities not attainable using traditional STR panels. However, the inclusion of sets of loci selected for mixture analysis, extended kinship, phenotype, biogeographic ancestry prediction, etc., can result in large panel sizes that are difficult to analyze in a rapid fashion. GrigoraSNP was developed to address the allele-calling bottleneck that was encountered when analyzing SNP panels with more than 5000 loci using HTS. GrigoraSNPs uses a MapReduce parallel data processing on multiple computational threads plus a novel locus-identification hashing strategy leveraging target sequence tags. This tool optimizes the SNP calling module of the DNA analysis pipeline with runtimes that scale linearly with the number of HTS reads. Results are compared with SNP analysis pipelines implemented with SAMtools and GATK. GrigoraSNPs removes a computational bottleneck for processing forensic samples with large HTS SNP panels. Published 2018. This article is a U.S. Government work and is in the public domain in the USA.
Dereeper, Alexis; Nicolas, Stéphane; Le Cunff, Loïc; Bacilieri, Roberto; Doligez, Agnès; Peros, Jean-Pierre; Ruiz, Manuel; This, Patrice
2011-05-05
High-throughput re-sequencing, new genotyping technologies and the availability of reference genomes allow the extensive characterization of Single Nucleotide Polymorphisms (SNPs) and insertion/deletion events (indels) in many plant species. The rapidly increasing amount of re-sequencing and genotyping data generated by large-scale genetic diversity projects requires the development of integrated bioinformatics tools able to efficiently manage, analyze, and combine these genetic data with genome structure and external data. In this context, we developed SNiPlay, a flexible, user-friendly and integrative web-based tool dedicated to polymorphism discovery and analysis. It integrates:1) a pipeline, freely accessible through the internet, combining existing softwares with new tools to detect SNPs and to compute different types of statistical indices and graphical layouts for SNP data. From standard sequence alignments, genotyping data or Sanger sequencing traces given as input, SNiPlay detects SNPs and indels events and outputs submission files for the design of Illumina's SNP chips. Subsequently, it sends sequences and genotyping data into a series of modules in charge of various processes: physical mapping to a reference genome, annotation (genomic position, intron/exon location, synonymous/non-synonymous substitutions), SNP frequency determination in user-defined groups, haplotype reconstruction and network, linkage disequilibrium evaluation, and diversity analysis (Pi, Watterson's Theta, Tajima's D).Furthermore, the pipeline allows the use of external data (such as phenotype, geographic origin, taxa, stratification) to define groups and compare statistical indices.2) a database storing polymorphisms, genotyping data and grapevine sequences released by public and private projects. It allows the user to retrieve SNPs using various filters (such as genomic position, missing data, polymorphism type, allele frequency), to compare SNP patterns between populations, and to export genotyping data or sequences in various formats. Our experiments on grapevine genetic projects showed that SNiPlay allows geneticists to rapidly obtain advanced results in several key research areas of plant genetic diversity. Both the management and treatment of large amounts of SNP data are rendered considerably easier for end-users through automation and integration. Current developments are taking into account new advances in high-throughput technologies.SNiPlay is available at: http://sniplay.cirad.fr/.
SNPassoc: an R package to perform whole genome association studies.
González, Juan R; Armengol, Lluís; Solé, Xavier; Guinó, Elisabet; Mercader, Josep M; Estivill, Xavier; Moreno, Víctor
2007-03-01
The popularization of large-scale genotyping projects has led to the widespread adoption of genetic association studies as the tool of choice in the search for single nucleotide polymorphisms (SNPs) underlying susceptibility to complex diseases. Although the analysis of individual SNPs is a relatively trivial task, when the number is large and multiple genetic models need to be explored it becomes necessary a tool to automate the analyses. In order to address this issue, we developed SNPassoc, an R package to carry out most common analyses in whole genome association studies. These analyses include descriptive statistics and exploratory analysis of missing values, calculation of Hardy-Weinberg equilibrium, analysis of association based on generalized linear models (either for quantitative or binary traits), and analysis of multiple SNPs (haplotype and epistasis analysis). Package SNPassoc is available at CRAN from http://cran.r-project.org. A tutorial is available on Bioinformatics online and in http://davinci.crg.es/estivill_lab/snpassoc.
Litos, Ioannis K; Ioannou, Penelope C; Christopoulos, Theodore K; Traeger-Synodinos, Jan; Kanavakis, Emmanuel
2009-06-15
DNA biosensors involve molecular recognition of the target sequence by hybridization with specific probes and detection by electrochemical, optical or gravimetric transduction. Disposable, dipstick-type biosensors have been developed recently, which enable visual detection of DNA without using instruments. In this context, we report a multianalyte DNA biosensor for visual genotyping of two single-nucleotide polymorphisms (SNPs). As a model, the biosensor was applied to the simultaneous genotyping of two SNPs, entailing the detection of four alleles. A PCR product that flanks both polymorphic sites is subjected to a single primer extension (PEXT) reaction employing four allele-specific primers, each containing a region complementary to an allele and a characteristic segment that enables subsequent capture on a test zone of the biosensor. The primers are extended with dNTPs and biotin-dUTP only if there is perfect complementarity with the interrogated sequence. The PEXT mixture is applied to the biosensor. As the developing buffer migrates along the strip, all the allele-specific primers are captured by immobilized oligonucleotides at the four test zones of the biosensor and detected by antibiotin-functionalized gold nanoparticles. As a result, the test zones are colored red if extension has occurred denoting the presence of the corresponding allele in the original sample. The excess nanoparticles are captured by immobilized biotinylated albumin at the control zone of the sensor forming another red zone that indicates the proper performance of the system. The assay was applied successfully to the genotyping of twenty clinical samples for two common SNPs of MBL2 gene.
Functional evaluation of genetic variants associated with endometriosis near GREB1.
Fung, Jenny N; Holdsworth-Carson, Sarah J; Sapkota, Yadav; Zhao, Zhen Zhen; Jones, Lincoln; Girling, Jane E; Paiva, Premila; Healey, Martin; Nyholt, Dale R; Rogers, Peter A W; Montgomery, Grant W
2015-05-01
Do DNA variants in the growth regulation by estrogen in breast cancer 1 (GREB1) region regulate endometrial GREB1 expression and increase the risk of developing endometriosis in women? We identified new single nucleotide polymorphisms (SNPs) with strong association with endometriosis at the GREB1 locus although we did not detect altered GREB1 expression in endometriosis patients with defined genotypes. Genome-wide association studies have identified the GREB1 region on chromosome 2p25.1 for increasing endometriosis risk. The differential expression of GREB1 has also been reported by others in association with endometriosis disease phenotype. Fine mapping studies comprehensively evaluated SNPs within the GREB1 region in a large-scale data set (>2500 cases and >4000 controls). Publicly available bioinformatics tools were employed to functionally annotate SNPs showing the strongest association signal with endometriosis risk. Endometrial GREB1 mRNA and protein expression was studied with respect to phases of the menstrual cycle (n = 2-45 per cycle stage) and expression quantitative trait loci (eQTL) analysis for significant SNPs were undertaken for GREB1 [mRNA (n = 94) and protein (n = 44) in endometrium]. Participants in this study are females who provided blood and/or endometrial tissue samples in a hospital setting. The key SNPs were genotyped using Sequenom MassARRAY. The functional roles and regulatory annotations for identified SNPs are predicted by various publicly available bioinformatics tools. Endometrial GREB1 expression work employed qRT-PCR, western blotting and immunohistochemistry studies. Fine mapping results identified a number of SNPs showing stronger association (0.004 < P < 0.032) with endometriosis risk than the original GWAS SNP (rs13394619) (P = 0.034). Some of these SNPs were predicted to have functional roles, for example, interaction with transcription factor motifs. The haplotype (a combination of alleles) formed by the risk alleles from two common SNPs showed significant association (P = 0.026) with endometriosis and epistasis analysis showed no evidence for interaction between the two SNPs, suggesting an additive effect of SNPs on endometriosis risk. In normal human endometrium, GREB1 protein expression was altered depending on the cycle stage (significantly different in late proliferative versus late secretory, P < 0.05) and cell type (glandular epithelium, not stromal cells). However, GREB1 expression in endometriosis cases versus controls and eQTL analyses did not reveal any significant changes. In silico prediction tools are generally based on cell lines different to our tissue and disease of interest. Functional annotations drawn from these analyses should be considered with this limitation in mind. We identified cell-specific and hormone-specific changes in GREB1 protein expression. The lack of a significant difference observed following our GREB1 expression studies may be the result of moderate power on mixed cell populations in the endometrial tissue samples. This study further implicates the GREB1 region on chromosome 2p25.1 and the GREB1 gene with involvement in endometriosis risk. More detailed functional studies are required to determine the role of the novel GREB1 transcripts in endometriosis pathophysiology. Funding for this work was provided by NHMRC Project Grants APP1012245, APP1026033, APP1049472 and APP1046880. There are no competing interests. © The Author 2015. Published by Oxford University Press on behalf of the European Society of Human Reproduction and Embryology. All rights reserved. For Permissions, please email: journals.permissions@oup.com.
The UCSC genome browser and associated tools
Haussler, David; Kent, W. James
2013-01-01
The UCSC Genome Browser (http://genome.ucsc.edu) is a graphical viewer for genomic data now in its 13th year. Since the early days of the Human Genome Project, it has presented an integrated view of genomic data of many kinds. Now home to assemblies for 58 organisms, the Browser presents visualization of annotations mapped to genomic coordinates. The ability to juxtapose annotations of many types facilitates inquiry-driven data mining. Gene predictions, mRNA alignments, epigenomic data from the ENCODE project, conservation scores from vertebrate whole-genome alignments and variation data may be viewed at any scale from a single base to an entire chromosome. The Browser also includes many other widely used tools, including BLAT, which is useful for alignments from high-throughput sequencing experiments. Private data uploaded as Custom Tracks and Data Hubs in many formats may be displayed alongside the rich compendium of precomputed data in the UCSC database. The Table Browser is a full-featured graphical interface, which allows querying, filtering and intersection of data tables. The Saved Session feature allows users to store and share customized views, enhancing the utility of the system for organizing multiple trains of thought. Binary Alignment/Map (BAM), Variant Call Format and the Personal Genome Single Nucleotide Polymorphisms (SNPs) data formats are useful for visualizing a large sequencing experiment (whole-genome or whole-exome), where the differences between the data set and the reference assembly may be displayed graphically. Support for high-throughput sequencing extends to compact, indexed data formats, such as BAM, bigBed and bigWig, allowing rapid visualization of large datasets from RNA-seq and ChIP-seq experiments via local hosting. PMID:22908213
The UCSC genome browser and associated tools.
Kuhn, Robert M; Haussler, David; Kent, W James
2013-03-01
The UCSC Genome Browser (http://genome.ucsc.edu) is a graphical viewer for genomic data now in its 13th year. Since the early days of the Human Genome Project, it has presented an integrated view of genomic data of many kinds. Now home to assemblies for 58 organisms, the Browser presents visualization of annotations mapped to genomic coordinates. The ability to juxtapose annotations of many types facilitates inquiry-driven data mining. Gene predictions, mRNA alignments, epigenomic data from the ENCODE project, conservation scores from vertebrate whole-genome alignments and variation data may be viewed at any scale from a single base to an entire chromosome. The Browser also includes many other widely used tools, including BLAT, which is useful for alignments from high-throughput sequencing experiments. Private data uploaded as Custom Tracks and Data Hubs in many formats may be displayed alongside the rich compendium of precomputed data in the UCSC database. The Table Browser is a full-featured graphical interface, which allows querying, filtering and intersection of data tables. The Saved Session feature allows users to store and share customized views, enhancing the utility of the system for organizing multiple trains of thought. Binary Alignment/Map (BAM), Variant Call Format and the Personal Genome Single Nucleotide Polymorphisms (SNPs) data formats are useful for visualizing a large sequencing experiment (whole-genome or whole-exome), where the differences between the data set and the reference assembly may be displayed graphically. Support for high-throughput sequencing extends to compact, indexed data formats, such as BAM, bigBed and bigWig, allowing rapid visualization of large datasets from RNA-seq and ChIP-seq experiments via local hosting.
Marcolino, Antonio C S; Porto, William F; Pires, Állan S; Franco, Octavio L; Alencar, Sérgio A
2016-12-07
The guanylate cyclase activator 2B, also known as uroguanylin, is part of the guanylin peptide family, which includes peptides such as guanylin and lymphoguanylin. The guanylin peptides could be related to sodium absorption inhibition and water secretion induction and their dysfunction may be related to various pathologies such as chronic renal failure, congestive heart failure and nephrotic syndrome. Besides, uroguanylin point mutations have been associated with essential hypertension. However, currently there are no studies on the impact of missense SNPs on uroguanylin structure. This study applied in silico SNP impact prediction tools to evaluate the impact of uroguanylin missense SNPs and to filter those considered as convergent deleterious, which were then further analyzed through long-term molecular dynamics simulations of 1μs of duration. The simulations suggested that all missense SNPs considered as convergent deleterious caused some kind of structural change to the uroguanylin peptide. Additionally, four of these SNPs were also shown to cause modifications in peptide flexibility, possibly resulting in functional changes. Copyright © 2016 Elsevier Ltd. All rights reserved.
Bioinformatic analyses to select phenotype affecting polymorphisms in HTR2C gene.
Piva, Francesco; Giulietti, Matteo; Baldelli, Luisa; Nardi, Bernardo; Bellantuono, Cesario; Armeni, Tatiana; Saccucci, Franca; Principato, Giovanni
2011-08-01
Single nucleotide polymorphisms (SNPs) in serotonin related genes influence mental disorders, responses to pharmacological and psychotherapeutic treatments. In planning association studies, researchers that want to investigate new SNPs have to select some among a large number of candidates. Our aim is to guide researchers in the selection of the most likely phenotype affecting polymorphisms. Here, we studied serotonin receptor 2C (HTR2C) SNPs because, till now, only relatively few of about 2000 are investigated. We used the most updated and assessed bioinformatic tools to predict which variations can give rise to biological effects among 2450 HTR2C SNPs. We suggest 48 SNPs that are worth considering in future association studies in the field of psychiatry, psychology and pharmacogenomics. Moreover, our analyses point out the biological level probably affected, such as transcription, splicing, miRNA regulation and protein structure, thus allowing to suggest future molecular investigations. Although few association studies are available in literature, their results are in agreement with our predictions, showing that our selection methods can help to guide future association studies. Copyright © 2011 John Wiley & Sons, Ltd.
SNPchiMp: a database to disentangle the SNPchip jungle in bovine livestock.
Nicolazzi, Ezequiel Luis; Picciolini, Matteo; Strozzi, Francesco; Schnabel, Robert David; Lawley, Cindy; Pirani, Ali; Brew, Fiona; Stella, Alessandra
2014-02-11
Currently, six commercial whole-genome SNP chips are available for cattle genotyping, produced by two different genotyping platforms. Technical issues need to be addressed to combine data that originates from the different platforms, or different versions of the same array generated by the manufacturer. For example: i) genome coordinates for SNPs may refer to different genome assemblies; ii) reference genome sequences are updated over time changing the positions, or even removing sequences which contain SNPs; iii) not all commercial SNP ID's are searchable within public databases; iv) SNPs can be coded using different formats and referencing different strands (e.g. A/B or A/C/T/G alleles, referencing forward/reverse, top/bottom or plus/minus strand); v) Due to new information being discovered, higher density chips do not necessarily include all the SNPs present in the lower density chips; and, vi) SNP IDs may not be consistent across chips and platforms. Most researchers and breed associations manage SNP data in real-time and thus require tools to standardise data in a user-friendly manner. Here we present SNPchiMp, a MySQL database linked to an open access web-based interface. Features of this interface include, but are not limited to, the following functions: 1) referencing the SNP mapping information to the latest genome assembly, 2) extraction of information contained in dbSNP for SNPs present in all commercially available bovine chips, and 3) identification of SNPs in common between two or more bovine chips (e.g. for SNP imputation from lower to higher density). In addition, SNPchiMp can retrieve this information on subsets of SNPs, accessing such data either via physical position on a supported assembly, or by a list of SNP IDs, rs or ss identifiers. This tool combines many different sources of information, that otherwise are time consuming to obtain and difficult to integrate. The SNPchiMp not only provides the information in a user-friendly format, but also enables researchers to perform a large number of operations with a few clicks of the mouse. This significantly reduces the time needed to execute the large number of operations required to manage SNP data.
Ramos, Antonio M.; Crooijmans, Richard P. M. A.; Affara, Nabeel A.; Amaral, Andreia J.; Archibald, Alan L.; Beever, Jonathan E.; Bendixen, Christian; Churcher, Carol; Clark, Richard; Dehais, Patrick; Hansen, Mark S.; Hedegaard, Jakob; Hu, Zhi-Liang; Kerstens, Hindrik H.; Law, Andy S.; Megens, Hendrik-Jan; Milan, Denis; Nonneman, Danny J.; Rohrer, Gary A.; Rothschild, Max F.; Smith, Tim P. L.; Schnabel, Robert D.; Van Tassell, Curt P.; Taylor, Jeremy F.; Wiedmann, Ralph T.; Schook, Lawrence B.; Groenen, Martien A. M.
2009-01-01
Background The dissection of complex traits of economic importance to the pig industry requires the availability of a significant number of genetic markers, such as single nucleotide polymorphisms (SNPs). This study was conducted to discover several hundreds of thousands of porcine SNPs using next generation sequencing technologies and use these SNPs, as well as others from different public sources, to design a high-density SNP genotyping assay. Methodology/Principal Findings A total of 19 reduced representation libraries derived from four swine breeds (Duroc, Landrace, Large White, Pietrain) and a Wild Boar population and three restriction enzymes (AluI, HaeIII and MspI) were sequenced using Illumina's Genome Analyzer (GA). The SNP discovery effort resulted in the de novo identification of over 372K SNPs. More than 549K SNPs were used to design the Illumina Porcine 60K+SNP iSelect Beadchip, now commercially available as the PorcineSNP60. A total of 64,232 SNPs were included on the Beadchip. Results from genotyping the 158 individuals used for sequencing showed a high overall SNP call rate (97.5%). Of the 62,621 loci that could be reliably scored, 58,994 were polymorphic yielding a SNP conversion success rate of 94%. The average minor allele frequency (MAF) for all scorable SNPs was 0.274. Conclusions/Significance Overall, the results of this study indicate the utility of using next generation sequencing technologies to identify large numbers of reliable SNPs. In addition, the validation of the PorcineSNP60 Beadchip demonstrated that the assay is an excellent tool that will likely be used in a variety of future studies in pigs. PMID:19654876
Freedman, Jennifer A; Wang, Yanru; Li, Xuechan; Liu, Hongliang; Moorman, Patricia G; George, Daniel J; Lee, Norman H; Hyslop, Terry; Wei, Qingyi; Patierno, Steven R
2018-05-03
Prostate cancer is a clinically and molecularly heterogeneous disease, with variation in outcomes only partially predicted by grade and stage. Additional tools to distinguish indolent from aggressive disease are needed. Phenotypic characteristics of stemness correlate with poor cancer prognosis. Given this correlation, we identified single nucleotide polymorphisms (SNPs) of stemness-related genes and examined their associations with prostate cancer survival. SNPs within stemness-related genes were analyzed for association with overall survival of prostate cancer in the Prostate, Lung, Colorectal and Ovarian Cancer Screening Trial. Significant SNPs predicted to be functional were selected for linkage disequilibrium analysis and combined and stratified analyses. Identified SNPs were evaluated for association with gene expression. SNPs of CD44 (rs9666607), ABCC1 (rs35605 and rs212091) and GDF15 (rs1058587) were associated with prostate cancer survival and predicted to be functional. A role for rs9666607 of CD44 and rs35605 of ABCC1 in RNA splicing regulation, rs212091 of ABCC1 in miRNA binding site activity and rs1058587 of GDF15 in causing an amino acid change was predicted. These SNPs represent potential novel prognostic markers for overall survival of prostate cancer and support a contribution of the stemness pathway to prostate cancer patient outcome.
Hüls, Anke; Ickstadt, Katja; Schikowski, Tamara; Krämer, Ursula
2017-06-12
For the analysis of gene-environment (GxE) interactions commonly single nucleotide polymorphisms (SNPs) are used to characterize genetic susceptibility, an approach that mostly lacks power and has poor reproducibility. One promising approach to overcome this problem might be the use of weighted genetic risk scores (GRS), which are defined as weighted sums of risk alleles of gene variants. The gold-standard is to use external weights from published meta-analyses. In this study, we used internal weights from the marginal genetic effects of the SNPs estimated by a multivariate elastic net regression and thereby provided a method that can be used if there are no external weights available. We conducted a simulation study for the detection of GxE interactions and compared power and type I error of single SNPs analyses with Bonferroni correction and corresponding analysis with unweighted and our weighted GRS approach in scenarios with six risk SNPs and an increasing number of highly correlated (up to 210) and noise SNPs (up to 840). Applying weighted GRS increased the power enormously in comparison to the common single SNPs approach (e.g. 94.2% vs. 35.4%, respectively, to detect a weak interaction with an OR ≈ 1.04 for six uncorrelated risk SNPs and n = 700 with a well-controlled type I error). Furthermore, weighted GRS outperformed the unweighted GRS, in particular in the presence of SNPs without any effect on the phenotype (e.g. 90.1% vs. 43.9%, respectively, when 20 noise SNPs were added to the six risk SNPs). This outperforming of the weighted GRS was confirmed in a real data application on lung inflammation in the SALIA cohort (n = 402). However, in scenarios with a high number of noise SNPs (>200 vs. 6 risk SNPs), larger sample sizes are needed to avoid an increased type I error, whereas a high number of correlated SNPs can be handled even in small samples (e.g. n = 400). In conclusion, weighted GRS with weights from the marginal genetic effects of the SNPs estimated by a multivariate elastic net regression were shown to be a powerful tool to detect gene-environment interactions in scenarios of high Linkage disequilibrium and noise.
Development of a single nucleotide polymorphism barcode to genotype Plasmodium vivax infections.
Baniecki, Mary Lynn; Faust, Aubrey L; Schaffner, Stephen F; Park, Daniel J; Galinsky, Kevin; Daniels, Rachel F; Hamilton, Elizabeth; Ferreira, Marcelo U; Karunaweera, Nadira D; Serre, David; Zimmerman, Peter A; Sá, Juliana M; Wellems, Thomas E; Musset, Lise; Legrand, Eric; Melnikov, Alexandre; Neafsey, Daniel E; Volkman, Sarah K; Wirth, Dyann F; Sabeti, Pardis C
2015-03-01
Plasmodium vivax, one of the five species of Plasmodium parasites that cause human malaria, is responsible for 25-40% of malaria cases worldwide. Malaria global elimination efforts will benefit from accurate and effective genotyping tools that will provide insight into the population genetics and diversity of this parasite. The recent sequencing of P. vivax isolates from South America, Africa, and Asia presents a new opportunity by uncovering thousands of novel single nucleotide polymorphisms (SNPs). Genotyping a selection of these SNPs provides a robust, low-cost method of identifying parasite infections through their unique genetic signature or barcode. Based on our experience in generating a SNP barcode for P. falciparum using High Resolution Melting (HRM), we have developed a similar tool for P. vivax. We selected globally polymorphic SNPs from available P. vivax genome sequence data that were located in putatively selectively neutral sites (i.e., intergenic, intronic, or 4-fold degenerate coding). From these candidate SNPs we defined a barcode consisting of 42 SNPs. We analyzed the performance of the 42-SNP barcode on 87 P. vivax clinical samples from parasite populations in South America (Brazil, French Guiana), Africa (Ethiopia) and Asia (Sri Lanka). We found that the P. vivax barcode is robust, as it requires only a small quantity of DNA (limit of detection 0.3 ng/μl) to yield reproducible genotype calls, and detects polymorphic genotypes with high sensitivity. The markers are informative across all clinical samples evaluated (average minor allele frequency > 0.1). Population genetic and statistical analyses show the barcode captures high degrees of population diversity and differentiates geographically distinct populations. Our 42-SNP barcode provides a robust, informative, and standardized genetic marker set that accurately identifies a genomic signature for P. vivax infections.
Development of a Single Nucleotide Polymorphism Barcode to Genotype Plasmodium vivax Infections
Baniecki, Mary Lynn; Faust, Aubrey L.; Schaffner, Stephen F.; Park, Daniel J.; Galinsky, Kevin; Daniels, Rachel F.; Hamilton, Elizabeth; Ferreira, Marcelo U.; Karunaweera, Nadira D.; Serre, David; Zimmerman, Peter A.; Sá, Juliana M.; Wellems, Thomas E.; Musset, Lise; Legrand, Eric; Melnikov, Alexandre; Neafsey, Daniel E.; Volkman, Sarah K.; Wirth, Dyann F.; Sabeti, Pardis C.
2015-01-01
Plasmodium vivax, one of the five species of Plasmodium parasites that cause human malaria, is responsible for 25–40% of malaria cases worldwide. Malaria global elimination efforts will benefit from accurate and effective genotyping tools that will provide insight into the population genetics and diversity of this parasite. The recent sequencing of P. vivax isolates from South America, Africa, and Asia presents a new opportunity by uncovering thousands of novel single nucleotide polymorphisms (SNPs). Genotyping a selection of these SNPs provides a robust, low-cost method of identifying parasite infections through their unique genetic signature or barcode. Based on our experience in generating a SNP barcode for P. falciparum using High Resolution Melting (HRM), we have developed a similar tool for P. vivax. We selected globally polymorphic SNPs from available P. vivax genome sequence data that were located in putatively selectively neutral sites (i.e., intergenic, intronic, or 4-fold degenerate coding). From these candidate SNPs we defined a barcode consisting of 42 SNPs. We analyzed the performance of the 42-SNP barcode on 87 P. vivax clinical samples from parasite populations in South America (Brazil, French Guiana), Africa (Ethiopia) and Asia (Sri Lanka). We found that the P. vivax barcode is robust, as it requires only a small quantity of DNA (limit of detection 0.3 ng/μl) to yield reproducible genotype calls, and detects polymorphic genotypes with high sensitivity. The markers are informative across all clinical samples evaluated (average minor allele frequency > 0.1). Population genetic and statistical analyses show the barcode captures high degrees of population diversity and differentiates geographically distinct populations. Our 42-SNP barcode provides a robust, informative, and standardized genetic marker set that accurately identifies a genomic signature for P. vivax infections. PMID:25781890
A SNP panel and online tool for checking genotype concordance through comparing QR codes.
Du, Yonghong; Martin, Joshua S; McGee, John; Yang, Yuchen; Liu, Eric Yi; Sun, Yingrui; Geihs, Matthias; Kong, Xuejun; Zhou, Eric Lingfeng; Li, Yun; Huang, Jie
2017-01-01
In the current precision medicine era, more and more samples get genotyped and sequenced. Both researchers and commercial companies expend significant time and resources to reduce the error rate. However, it has been reported that there is a sample mix-up rate of between 0.1% and 1%, not to mention the possibly higher mix-up rate during the down-stream genetic reporting processes. Even on the low end of this estimate, this translates to a significant number of mislabeled samples, especially over the projected one billion people that will be sequenced within the next decade. Here, we first describe a method to identify a small set of Single nucleotide polymorphisms (SNPs) that can uniquely identify a personal genome, which utilizes allele frequencies of five major continental populations reported in the 1000 genomes project and the ExAC Consortium. To make this panel more informative, we added four SNPs that are commonly used to predict ABO blood type, and another two SNPs that are capable of predicting sex. We then implement a web interface (http://qrcme.tech), nicknamed QRC (for QR code based Concordance check), which is capable of extracting the relevant ID SNPs from a raw genetic data, coding its genotype as a quick response (QR) code, and comparing QR codes to report the concordance of underlying genetic datasets. The resulting 80 fingerprinting SNPs represent a significant decrease in complexity and the number of markers used for genetic data labelling and tracking. Our method and web tool is easily accessible to both researchers and the general public who consider the accuracy of complex genetic data as a prerequisite towards precision medicine.
A SNP panel and online tool for checking genotype concordance through comparing QR codes
Du, Yonghong; Martin, Joshua S.; McGee, John; Yang, Yuchen; Liu, Eric Yi; Sun, Yingrui; Geihs, Matthias; Kong, Xuejun; Zhou, Eric Lingfeng; Li, Yun
2017-01-01
In the current precision medicine era, more and more samples get genotyped and sequenced. Both researchers and commercial companies expend significant time and resources to reduce the error rate. However, it has been reported that there is a sample mix-up rate of between 0.1% and 1%, not to mention the possibly higher mix-up rate during the down-stream genetic reporting processes. Even on the low end of this estimate, this translates to a significant number of mislabeled samples, especially over the projected one billion people that will be sequenced within the next decade. Here, we first describe a method to identify a small set of Single nucleotide polymorphisms (SNPs) that can uniquely identify a personal genome, which utilizes allele frequencies of five major continental populations reported in the 1000 genomes project and the ExAC Consortium. To make this panel more informative, we added four SNPs that are commonly used to predict ABO blood type, and another two SNPs that are capable of predicting sex. We then implement a web interface (http://qrcme.tech), nicknamed QRC (for QR code based Concordance check), which is capable of extracting the relevant ID SNPs from a raw genetic data, coding its genotype as a quick response (QR) code, and comparing QR codes to report the concordance of underlying genetic datasets. The resulting 80 fingerprinting SNPs represent a significant decrease in complexity and the number of markers used for genetic data labelling and tracking. Our method and web tool is easily accessible to both researchers and the general public who consider the accuracy of complex genetic data as a prerequisite towards precision medicine. PMID:28926565
Chen, Jinyun; Wu, Xifeng; Huang, Yujing; Chen, Wei; Brand, Randall E.; Killary, Ann M.; Sen, Subrata; Frazier, Marsha L.
2016-01-01
Biomarkers are critically needed for the early detection of pancreatic cancer (PC) are urgently needed. Our purpose was to identify a panel of genetic variants that, combined, can predict increased risk for early-onset PC and thereby identify individuals who should begin screening at an early age. Previously, we identified genes using a functional genomic approach that were aberrantly expressed in early pathways to PC tumorigenesis. We now report the discovery of single nucleotide polymorphisms (SNPs) in these genes associated with early age at diagnosis of PC using a two-phase study design. In silico and bioinformatics tools were used to examine functional relevance of the identified SNPs. Eight SNPs were consistently associated with age at diagnosis in the discovery phase, validation phase and pooled analysis. Further analysis of the joint effects of these 8 SNPs showed that, compared to participants carrying none of these unfavorable genotypes (median age at PC diagnosis 70 years), those carrying 1–2, 3–4, or 5 or more unfavorable genotypes had median ages at diagnosis of 64, 63, and 62 years, respectively (P = 3.0E–04). A gene-dosage effect was observed, with age at diagnosis inversely related to number of unfavorable genotypes (Ptrend = 1.0E–04). Using bioinformatics tools, we found that all of the 8 SNPs were predicted to play functional roles in the disruption of transcription factor and/or enhancer binding sites and most of them were expression quantitative trait loci (eQTL) of the target genes. The panel of genetic markers identified may serve as susceptibility markers for earlier PC diagnosis. PMID:27486767
2013-01-01
Background SNPs&GO is a method for the prediction of deleterious Single Amino acid Polymorphisms (SAPs) using protein functional annotation. In this work, we present the web server implementation of SNPs&GO (WS-SNPs&GO). The server is based on Support Vector Machines (SVM) and for a given protein, its input comprises: the sequence and/or its three-dimensional structure (when available), a set of target variations and its functional Gene Ontology (GO) terms. The output of the server provides, for each protein variation, the probabilities to be associated to human diseases. Results The server consists of two main components, including updated versions of the sequence-based SNPs&GO (recently scored as one of the best algorithms for predicting deleterious SAPs) and of the structure-based SNPs&GO3d programs. Sequence and structure based algorithms are extensively tested on a large set of annotated variations extracted from the SwissVar database. Selecting a balanced dataset with more than 38,000 SAPs, the sequence-based approach achieves 81% overall accuracy, 0.61 correlation coefficient and an Area Under the Curve (AUC) of the Receiver Operating Characteristic (ROC) curve of 0.88. For the subset of ~6,600 variations mapped on protein structures available at the Protein Data Bank (PDB), the structure-based method scores with 84% overall accuracy, 0.68 correlation coefficient, and 0.91 AUC. When tested on a new blind set of variations, the results of the server are 79% and 83% overall accuracy for the sequence-based and structure-based inputs, respectively. Conclusions WS-SNPs&GO is a valuable tool that includes in a unique framework information derived from protein sequence, structure, evolutionary profile, and protein function. WS-SNPs&GO is freely available at http://snps.biofold.org/snps-and-go. PMID:23819482
Congruence as a measurement of extended haplotype structure across the genome
2012-01-01
Background Historically, extended haplotypes have been defined using only a few data points, such as alleles for several HLA genes in the MHC. High-density SNP data, and the increasing affordability of whole genome SNP typing, creates the opportunity to define higher resolution extended haplotypes. This drives the need for new tools that support quantification and visualization of extended haplotypes as defined by as many as 2000 SNPs. Confronted with high-density SNP data across the major histocompatibility complex (MHC) for 2,300 complete families, compiled by the Type 1 Diabetes Genetics Consortium (T1DGC), we developed software for studying extended haplotypes. Methods The software, called ExHap (Extended Haplotype), uses a similarity measurement we term congruence to identify and quantify long-range allele identity. Using ExHap, we analyzed congruence in both the T1DGC data and family-phased data from the International HapMap Project. Results Congruent chromosomes from the T1DGC data have between 96.5% and 99.9% allele identity over 1,818 SNPs spanning 2.64 megabases of the MHC (HLA-DRB1 to HLA-A). Thirty-three of 132 DQ-DR-B-A defined haplotype groups have > 50% congruent chromosomes in this region. For example, 92% of chromosomes within the DR3-B8-A1 haplotype are congruent from HLA-DRB1 to HLA-A (99.8% allele identity). We also applied ExHap to all 22 autosomes for both CEU and YRI cohorts from the International HapMap Project, identifying multiple candidate extended haplotypes. Conclusions Long-range congruence is not unique to the MHC region. Patterns of allele identity on phased chromosomes provide a simple, straightforward approach to visually and quantitatively inspect complex long-range structural patterns in the genome. Such patterns aid the biologist in appreciating genetic similarities and differences across cohorts, and can lead to hypothesis generation for subsequent studies. PMID:22369243
Johansen, Morten Bo; Izarzugaza, Jose M. G.; Brunak, Søren; Petersen, Thomas Nordahl; Gupta, Ramneek
2013-01-01
We have developed a sequence conservation-based artificial neural network predictor called NetDiseaseSNP which classifies nsSNPs as disease-causing or neutral. Our method uses the excellent alignment generation algorithm of SIFT to identify related sequences and a combination of 31 features assessing sequence conservation and the predicted surface accessibility to produce a single score which can be used to rank nsSNPs based on their potential to cause disease. NetDiseaseSNP classifies successfully disease-causing and neutral mutations. In addition, we show that NetDiseaseSNP discriminates cancer driver and passenger mutations satisfactorily. Our method outperforms other state-of-the-art methods on several disease/neutral datasets as well as on cancer driver/passenger mutation datasets and can thus be used to pinpoint and prioritize plausible disease candidates among nsSNPs for further investigation. NetDiseaseSNP is publicly available as an online tool as well as a web service: http://www.cbs.dtu.dk/services/NetDiseaseSNP PMID:23935863
CGDSNPdb: a database resource for error-checked and imputed mouse SNPs.
Hutchins, Lucie N; Ding, Yueming; Szatkiewicz, Jin P; Von Smith, Randy; Yang, Hyuna; de Villena, Fernando Pardo-Manuel; Churchill, Gary A; Graber, Joel H
2010-07-06
The Center for Genome Dynamics Single Nucleotide Polymorphism Database (CGDSNPdb) is an open-source value-added database with more than nine million mouse single nucleotide polymorphisms (SNPs), drawn from multiple sources, with genotypes assigned to multiple inbred strains of laboratory mice. All SNPs are checked for accuracy and annotated for properties specific to the SNP as well as those implied by changes to overlapping protein-coding genes. CGDSNPdb serves as the primary interface to two unique data sets, the 'imputed genotype resource' in which a Hidden Markov Model was used to assess local haplotypes and the most probable base assignment at several million genomic loci in tens of strains of mice, and the Affymetrix Mouse Diversity Genotyping Array, a high density microarray with over 600,000 SNPs and over 900,000 invariant genomic probes. CGDSNPdb is accessible online through either a web-based query tool or a MySQL public login. Database URL: http://cgd.jax.org/cgdsnpdb/
Singh, Preety K; Mistry, Kinnari N; Chiramana, Haritha; Rank, Dharamshi N; Joshi, Chaitanya G
2018-05-20
Non-homologous end joining (NHEJ) pathway has pivotal role in repair of double-strand DNA breaks that may lead to carcinogenesis. XRCC4 is one of the essential proteins of this pathway and single-nucleotide polymorphisms (SNPs) of this gene are reported to be associated with cancer risks. In our study, we first used computational approaches to predict the damaging variants of XRCC4 gene. Tools predicted rs79561451 (S110P) nsSNP as the most deleterious SNP. Along with this SNP, we analysed other two SNPs (rs3734091 and rs6869366) to study their association with breast cancer in population of West India. Variant rs3734091 was found to be significantly associated with breast cancer while rs6869366 variant did not show any association. These SNPs may influence the susceptibility of individuals to breast cancer in this population. Copyright © 2018 Elsevier B.V. All rights reserved.
2013-01-01
Background Efficient screening of bacterial artificial chromosome (BAC) libraries with polymerase chain reaction (PCR)-based markers is feasible provided that a multidimensional pooling strategy is implemented. Single nucleotide polymorphisms (SNPs) can be screened in multiplexed format, therefore this marker type lends itself particularly well for medium- to high-throughput applications. Combining the power of multiplex-PCR assays with a multidimensional pooling system may prove to be especially challenging in a polyploid genome. In polyploid genomes two classes of SNPs need to be distinguished, polymorphisms between accessions (intragenomic SNPs) and those differentiating between homoeologous genomes (intergenomic SNPs). We have assessed whether the highly parallel Illumina GoldenGate® Genotyping Assay is suitable for the screening of a BAC library of the polyploid Brassica napus genome. Results A multidimensional screening platform was developed for a Brassica napus BAC library which is composed of almost 83,000 clones. Intragenomic and intergenomic SNPs were included in Illumina’s GoldenGate® Genotyping Assay and both SNP classes were used successfully for screening of the multidimensional BAC pools of the Brassica napus library. An optimized scoring method is proposed which is especially valuable for SNP calling of intergenomic SNPs. Validation of the genotyping results by independent methods revealed a success of approximately 80% for the multiplex PCR-based screening regardless of whether intra- or intergenomic SNPs were evaluated. Conclusions Illumina’s GoldenGate® Genotyping Assay can be efficiently used for screening of multidimensional Brassica napus BAC pools. SNP calling was specifically tailored for the evaluation of BAC pool screening data. The developed scoring method can be implemented independently of plant reference samples. It is demonstrated that intergenomic SNPs represent a powerful tool for BAC library screening of a polyploid genome. PMID:24010766
Klaften, Matthias; Hrabé de Angelis, Martin
2005-07-01
Genome-wide mapping in the identification of novel candidate genes has always been the standard method in genetics and genomics to correlate a clinically interesting phenotypic trait with a genotype. However, the performance of a mapping experiment using classical microsatellite approaches can be very time consuming. The high-throughput analysis of single-nucleotide polymorphisms (SNPs) has the potential of being the successor of microsatellite analysis routinely used for these mapping approaches, where one of the major obstacles is the design of the appropriate SNP marker set itself. Here we report on ARTS, an advanced retrieval tool for SNPs, which allows researchers to comb freely the public mouse dbSNP database for multiple reference and test strains. Several filters can be applied in order to improve the sensitivity and the specificity of the search results. By employing the panel generator function of this program, it is possible to abbreviate the extraction of reliable sequence data for a large marker panel including several different mouse strains from days to minutes. The concept of ARTS is easily adaptable to other species for which SNP databases are available, making it a versatile tool for the use of SNPs as markers for genotyping. The web interface is accessible at http://andromeda.gsf.de/arts.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Yang, Jing; Li, Yuan-Yuan; Shanghai Center for Bioinformation Technology, Shanghai 200235
2012-03-02
Highlights: Black-Right-Pointing-Pointer Proper dataset partition can improve the prediction of deleterious nsSNPs. Black-Right-Pointing-Pointer Partition according to original residue type at nsSNP is a good criterion. Black-Right-Pointing-Pointer Similar strategy is supposed promising in other machine learning problems. -- Abstract: Many non-synonymous SNPs (nsSNPs) are associated with diseases, and numerous machine learning methods have been applied to train classifiers for sorting disease-associated nsSNPs from neutral ones. The continuously accumulated nsSNP data allows us to further explore better prediction approaches. In this work, we partitioned the training data into 20 subsets according to either original or substituted amino acid type at the nsSNPmore » site. Using support vector machine (SVM), training classification models on each subset resulted in an overall accuracy of 76.3% or 74.9% depending on the two different partition criteria, while training on the whole dataset obtained an accuracy of only 72.6%. Moreover, the dataset was also randomly divided into 20 subsets, but the corresponding accuracy was only 73.2%. Our results demonstrated that partitioning the whole training dataset into subsets properly, i.e., according to the residue type at the nsSNP site, will improve the performance of the trained classifiers significantly, which should be valuable in developing better tools for predicting the disease-association of nsSNPs.« less
Fast and robust group-wise eQTL mapping using sparse graphical models.
Cheng, Wei; Shi, Yu; Zhang, Xiang; Wang, Wei
2015-01-16
Genome-wide expression quantitative trait loci (eQTL) studies have emerged as a powerful tool to understand the genetic basis of gene expression and complex traits. The traditional eQTL methods focus on testing the associations between individual single-nucleotide polymorphisms (SNPs) and gene expression traits. A major drawback of this approach is that it cannot model the joint effect of a set of SNPs on a set of genes, which may correspond to hidden biological pathways. We introduce a new approach to identify novel group-wise associations between sets of SNPs and sets of genes. Such associations are captured by hidden variables connecting SNPs and genes. Our model is a linear-Gaussian model and uses two types of hidden variables. One captures the set associations between SNPs and genes, and the other captures confounders. We develop an efficient optimization procedure which makes this approach suitable for large scale studies. Extensive experimental evaluations on both simulated and real datasets demonstrate that the proposed methods can effectively capture both individual and group-wise signals that cannot be identified by the state-of-the-art eQTL mapping methods. Considering group-wise associations significantly improves the accuracy of eQTL mapping, and the successful multi-layer regression model opens a new approach to understand how multiple SNPs interact with each other to jointly affect the expression level of a group of genes.
Genetic prediction of type 2 diabetes using deep neural network.
Kim, J; Kim, J; Kwak, M J; Bajaj, M
2018-04-01
Type 2 diabetes (T2DM) has strong heritability but genetic models to explain heritability have been challenging. We tested deep neural network (DNN) to predict T2DM using the nested case-control study of Nurses' Health Study (3326 females, 45.6% T2DM) and Health Professionals Follow-up Study (2502 males, 46.5% T2DM). We selected 96, 214, 399, and 678 single-nucleotide polymorphism (SNPs) through Fisher's exact test and L1-penalized logistic regression. We split each dataset randomly in 4:1 to train prediction models and test their performance. DNN and logistic regressions showed better area under the curve (AUC) of ROC curves than the clinical model when 399 or more SNPs included. DNN was superior than logistic regressions in AUC with 399 or more SNPs in male and 678 SNPs in female. Addition of clinical factors consistently increased AUC of DNN but failed to improve logistic regressions with 214 or more SNPs. In conclusion, we show that DNN can be a versatile tool to predict T2DM incorporating large numbers of SNPs and clinical information. Limitations include a relatively small number of the subjects mostly of European ethnicity. Further studies are warranted to confirm and improve performance of genetic prediction models using DNN in different ethnic groups. © 2017 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.
Peace, Cameron; Bassil, Nahla; Main, Dorrie; Ficklin, Stephen; Rosyara, Umesh R.; Stegmeir, Travis; Sebolt, Audrey; Gilmore, Barbara; Lawley, Cindy; Mockler, Todd C.; Bryant, Douglas W.; Wilhelm, Larry; Iezzoni, Amy
2012-01-01
High-throughput genome scans are important tools for genetic studies and breeding applications. Here, a 6K SNP array for use with the Illumina Infinium® system was developed for diploid sweet cherry (Prunus avium) and allotetraploid sour cherry (P. cerasus). This effort was led by RosBREED, a community initiative to enable marker-assisted breeding for rosaceous crops. Next-generation sequencing in diverse breeding germplasm provided 25 billion basepairs (Gb) of cherry DNA sequence from which were identified genome-wide SNPs for sweet cherry and for the two sour cherry subgenomes derived from sweet cherry (avium subgenome) and P. fruticosa (fruticosa subgenome). Anchoring to the peach genome sequence, recently released by the International Peach Genome Initiative, predicted relative physical locations of the 1.9 million putative SNPs detected, preliminarily filtered to 368,943 SNPs. Further filtering was guided by results of a 144-SNP subset examined with the Illumina GoldenGate® assay on 160 accessions. A 6K Infinium® II array was designed with SNPs evenly spaced genetically across the sweet and sour cherry genomes. SNPs were developed for each sour cherry subgenome by using minor allele frequency in the sour cherry detection panel to enrich for subgenome-specific SNPs followed by targeting to either subgenome according to alleles observed in sweet cherry. The array was evaluated using panels of sweet (n = 269) and sour (n = 330) cherry breeding germplasm. Approximately one third of array SNPs were informative for each crop. A total of 1825 polymorphic SNPs were verified in sweet cherry, 13% of these originally developed for sour cherry. Allele dosage was resolved for 2058 polymorphic SNPs in sour cherry, one third of these being originally developed for sweet cherry. This publicly available genomics resource represents a significant advance in cherry genome-scanning capability that will accelerate marker-locus-trait association discovery, genome structure investigation, and genetic diversity assessment in this diploid-tetraploid crop group. PMID:23284615
GESPA: classifying nsSNPs to predict disease association.
Khurana, Jay K; Reeder, Jay E; Shrimpton, Antony E; Thakar, Juilee
2015-07-25
Non-synonymous single nucleotide polymorphisms (nsSNPs) are the most common DNA sequence variation associated with disease in humans. Thus determining the clinical significance of each nsSNP is of great importance. Potential detrimental nsSNPs may be identified by genetic association studies or by functional analysis in the laboratory, both of which are expensive and time consuming. Existing computational methods lack accuracy and features to facilitate nsSNP classification for clinical use. We developed the GESPA (GEnomic Single nucleotide Polymorphism Analyzer) program to predict the pathogenicity and disease phenotype of nsSNPs. GESPA is a user-friendly software package for classifying disease association of nsSNPs. It allows flexibility in acceptable input formats and predicts the pathogenicity of a given nsSNP by assessing the conservation of amino acids in orthologs and paralogs and supplementing this information with data from medical literature. The development and testing of GESPA was performed using the humsavar, ClinVar and humvar datasets. Additionally, GESPA also predicts the disease phenotype associated with a nsSNP with high accuracy, a feature unavailable in existing software. GESPA's overall accuracy exceeds existing computational methods for predicting nsSNP pathogenicity. The usability of GESPA is enhanced by fast SQL-based cloud storage and retrieval of data. GESPA is a novel bioinformatics tool to determine the pathogenicity and phenotypes of nsSNPs. We anticipate that GESPA will become a useful clinical framework for predicting the disease association of nsSNPs. The program, executable jar file, source code, GPL 3.0 license, user guide, and test data with instructions are available at http://sourceforge.net/projects/gespa.
Comparative analysis of methods for detecting interacting loci
2011-01-01
Background Interactions among genetic loci are believed to play an important role in disease risk. While many methods have been proposed for detecting such interactions, their relative performance remains largely unclear, mainly because different data sources, detection performance criteria, and experimental protocols were used in the papers introducing these methods and in subsequent studies. Moreover, there have been very few studies strictly focused on comparison of existing methods. Given the importance of detecting gene-gene and gene-environment interactions, a rigorous, comprehensive comparison of performance and limitations of available interaction detection methods is warranted. Results We report a comparison of eight representative methods, of which seven were specifically designed to detect interactions among single nucleotide polymorphisms (SNPs), with the last a popular main-effect testing method used as a baseline for performance evaluation. The selected methods, multifactor dimensionality reduction (MDR), full interaction model (FIM), information gain (IG), Bayesian epistasis association mapping (BEAM), SNP harvester (SH), maximum entropy conditional probability modeling (MECPM), logistic regression with an interaction term (LRIT), and logistic regression (LR) were compared on a large number of simulated data sets, each, consistent with complex disease models, embedding multiple sets of interacting SNPs, under different interaction models. The assessment criteria included several relevant detection power measures, family-wise type I error rate, and computational complexity. There are several important results from this study. First, while some SNPs in interactions with strong effects are successfully detected, most of the methods miss many interacting SNPs at an acceptable rate of false positives. In this study, the best-performing method was MECPM. Second, the statistical significance assessment criteria, used by some of the methods to control the type I error rate, are quite conservative, thereby limiting their power and making it difficult to fairly compare them. Third, as expected, power varies for different models and as a function of penetrance, minor allele frequency, linkage disequilibrium and marginal effects. Fourth, the analytical relationships between power and these factors are derived, aiding in the interpretation of the study results. Fifth, for these methods the magnitude of the main effect influences the power of the tests. Sixth, most methods can detect some ground-truth SNPs but have modest power to detect the whole set of interacting SNPs. Conclusion This comparison study provides new insights into the strengths and limitations of current methods for detecting interacting loci. This study, along with freely available simulation tools we provide, should help support development of improved methods. The simulation tools are available at: http://code.google.com/p/simulation-tool-bmc-ms9169818735220977/downloads/list. PMID:21729295
Comparative analysis of methods for detecting interacting loci.
Chen, Li; Yu, Guoqiang; Langefeld, Carl D; Miller, David J; Guy, Richard T; Raghuram, Jayaram; Yuan, Xiguo; Herrington, David M; Wang, Yue
2011-07-05
Interactions among genetic loci are believed to play an important role in disease risk. While many methods have been proposed for detecting such interactions, their relative performance remains largely unclear, mainly because different data sources, detection performance criteria, and experimental protocols were used in the papers introducing these methods and in subsequent studies. Moreover, there have been very few studies strictly focused on comparison of existing methods. Given the importance of detecting gene-gene and gene-environment interactions, a rigorous, comprehensive comparison of performance and limitations of available interaction detection methods is warranted. We report a comparison of eight representative methods, of which seven were specifically designed to detect interactions among single nucleotide polymorphisms (SNPs), with the last a popular main-effect testing method used as a baseline for performance evaluation. The selected methods, multifactor dimensionality reduction (MDR), full interaction model (FIM), information gain (IG), Bayesian epistasis association mapping (BEAM), SNP harvester (SH), maximum entropy conditional probability modeling (MECPM), logistic regression with an interaction term (LRIT), and logistic regression (LR) were compared on a large number of simulated data sets, each, consistent with complex disease models, embedding multiple sets of interacting SNPs, under different interaction models. The assessment criteria included several relevant detection power measures, family-wise type I error rate, and computational complexity. There are several important results from this study. First, while some SNPs in interactions with strong effects are successfully detected, most of the methods miss many interacting SNPs at an acceptable rate of false positives. In this study, the best-performing method was MECPM. Second, the statistical significance assessment criteria, used by some of the methods to control the type I error rate, are quite conservative, thereby limiting their power and making it difficult to fairly compare them. Third, as expected, power varies for different models and as a function of penetrance, minor allele frequency, linkage disequilibrium and marginal effects. Fourth, the analytical relationships between power and these factors are derived, aiding in the interpretation of the study results. Fifth, for these methods the magnitude of the main effect influences the power of the tests. Sixth, most methods can detect some ground-truth SNPs but have modest power to detect the whole set of interacting SNPs. This comparison study provides new insights into the strengths and limitations of current methods for detecting interacting loci. This study, along with freely available simulation tools we provide, should help support development of improved methods. The simulation tools are available at: http://code.google.com/p/simulation-tool-bmc-ms9169818735220977/downloads/list.
Farris, M Heath; Scott, Andrew R; Texter, Pamela A; Bartlett, Marta; Coleman, Patricia; Masters, David
2018-04-11
Single nucleotide polymorphisms (SNPs) located within the human genome have been shown to have utility as markers of identity in the differentiation of DNA from individual contributors. Massively parallel DNA sequencing (MPS) technologies and human genome SNP databases allow for the design of suites of identity-linked target regions, amenable to sequencing in a multiplexed and massively parallel manner. Therefore, tools are needed for leveraging the genotypic information found within SNP databases for the discovery of genomic targets that can be evaluated on MPS platforms. The SNP island target identification algorithm (TIA) was developed as a user-tunable system to leverage SNP information within databases. Using data within the 1000 Genomes Project SNP database, human genome regions were identified that contain globally ubiquitous identity-linked SNPs and that were responsive to targeted resequencing on MPS platforms. Algorithmic filters were used to exclude target regions that did not conform to user-tunable SNP island target characteristics. To validate the accuracy of TIA for discovering these identity-linked SNP islands within the human genome, SNP island target regions were amplified from 70 contributor genomic DNA samples using the polymerase chain reaction. Multiplexed amplicons were sequenced using the Illumina MiSeq platform, and the resulting sequences were analyzed for SNP variations. 166 putative identity-linked SNPs were targeted in the identified genomic regions. Of the 309 SNPs that provided discerning power across individual SNP profiles, 74 previously undefined SNPs were identified during evaluation of targets from individual genomes. Overall, DNA samples of 70 individuals were uniquely identified using a subset of the suite of identity-linked SNP islands. TIA offers a tunable genome search tool for the discovery of targeted genomic regions that are scalable in the population frequency and numbers of SNPs contained within the SNP island regions. It also allows the definition of sequence length and sequence variability of the target region as well as the less variable flanking regions for tailoring to MPS platforms. As shown in this study, TIA can be used to discover identity-linked SNP islands within the human genome, useful for differentiating individuals by targeted resequencing on MPS technologies.
Assessing polar bear (Ursus maritimus) population structure in the Hudson Bay region using SNPs.
Viengkone, Michelle; Derocher, Andrew Edward; Richardson, Evan Shaun; Malenfant, René Michael; Miller, Joshua Moses; Obbard, Martyn E; Dyck, Markus G; Lunn, Nick J; Sahanatien, Vicki; Davis, Corey S
2016-12-01
Defining subpopulations using genetics has traditionally used data from microsatellite markers to investigate population structure; however, single-nucleotide polymorphisms (SNPs) have emerged as a tool for detection of fine-scale structure. In Hudson Bay, Canada, three polar bear ( Ursus maritimus ) subpopulations (Foxe Basin (FB), Southern Hudson Bay (SH), and Western Hudson Bay (WH)) have been delineated based on mark-recapture studies, radiotelemetry and satellite telemetry, return of marked animals in the subsistence harvest, and population genetics using microsatellites. We used SNPs to detect fine-scale population structure in polar bears from the Hudson Bay region and compared our results to the current designations using 414 individuals genotyped at 2,603 SNPs. Analyses based on discriminant analysis of principal components (DAPC) and STRUCTURE support the presence of four genetic clusters: (i) Western-including individuals sampled in WH, SH (excluding Akimiski Island in James Bay), and southern FB (south of Southampton Island); (ii) Northern-individuals sampled in northern FB (Baffin Island) and Davis Strait (DS) (Labrador coast); (iii) Southeast-individuals from SH (Akimiski Island in James Bay); and (iv) Northeast-individuals from DS (Baffin Island). Population structure differed from microsatellite studies and current management designations demonstrating the value of using SNPs for fine-scale population delineation in polar bears.
Larson, Wesley; Palti, Yniv; Gao, G.; Warheit, Kenneth I.; Seeb, James E.
2017-01-01
Natural-origin steelhead trout (Oncorhynchus mykiss (Walbaum, 1792)) in the Pacific Northwest, USA, are threatened by a number of factors including habitat destruction, disease, decline in marine survival, and a potential erosion of genetic viability due to introgression from hatchery strains. Our major goal was to use a recently developed SNP array containing ∼57 000 SNPs to identify a subset of SNPs that differentiate hatchery and natural-origin populations. We analyzed 35 765 polymorphic SNPs in nine populations of steelhead trout sampled from Puget Sound, Washington, USA. We then conducted two outlier tests and found 360 loci that were candidates for divergent selection between hatchery and natural-origin populations (mean FCT = 0.29, maximum = 0.65) and 595 SNPs that were candidates for selection among natural-origin populations (mean FST = 0.25, maximum = 0.51). Comparisons with a linkage map revealed that two chromosomes (Omy05 and Omy25) contained significantly more outliers than other chromosomes, suggesting that regions on Omy05 and Omy25 may be of adaptive significance. Our results highlight several advantages of the 57 000 SNP array as a tool for population and conservation genomics studies.
Zhang, Suhua; Bian, Yingnan; Zhang, Zheren; Zheng, Hancheng; Wang, Zheng; Zha, Lagabaiyila; Cai, Jifeng; Gao, Yuzhen; Ji, Chaoneng; Hou, Yiping; Li, Chengtao
2015-01-01
SNPs, abundant in human genome with lower mutation rate, are attractive to genetic application like forensic, anthropological and evolutionary studies. Universal SNPs showing little allelic frequency variation among populations while remaining highly informative for human identification were obtained from previous studies. However, genotyping tools target only dozens of markers simultaneously, limiting their applications. Here, 124 SNPs were simultaneous tested using Ampliseq technology with Ion Torrent PGM platform. Concordance study was performed with 2 reference samples of 9947A and 9948 between NGS and Sanger sequencing. Full concordance were obtained except genotype of rs576261 with 9947A. Parameter of FMAR (%) was introduced for NGS data analysis for the first time, evaluating allelic performance, sensitivity testing and mixture testing. FMAR values for accurate heterozygotes should be range from 50% to 60%, for homozygotes or Y-SNP should be above 90%. SNPs of rs7520386, rs4530059, rs214955, rs1523537, rs2342747, rs576261 and rs12997453 were recognized as poorly performing loci, either with allelic imbalance or with lower coverage. Sensitivity testing demonstrated that with DNA range from 10 ng-0.5 ng, all correct genotypes were obtained. For mixture testing, a clear linear correlation (R2 = 0.9429) between the excepted FMAR and observed FMAR values of mixtures was observed. PMID:26691610
Novel efficient genome-wide SNP panels for the conservation of the highly endangered Iberian lynx.
Kleinman-Ruiz, Daniel; Martínez-Cruz, Begoña; Soriano, Laura; Lucena-Perez, Maria; Cruz, Fernando; Villanueva, Beatriz; Fernández, Jesús; Godoy, José A
2017-07-21
The Iberian lynx (Lynx pardinus) has been acknowledged as the most endangered felid species in the world. An intense contraction and fragmentation during the twentieth century left less than 100 individuals split in two isolated and genetically eroded populations by 2002. Genetic monitoring and management so far have been based on 36 STRs, but their limited variability and the more complex situation of current populations demand more efficient molecular markers. The recent characterization of the Iberian lynx genome identified more than 1.6 million SNPs, of which 1536 were selected and genotyped in an extended Iberian lynx sample. We validated 1492 SNPs and analysed their heterozygosity, Hardy-Weinberg equilibrium, and linkage disequilibrium. We then selected a panel of 343 minimally linked autosomal SNPs from which we extracted subsets optimized for four different typical tasks in conservation applications: individual identification, parentage assignment, relatedness estimation, and admixture classification, and compared their power to currently used STR panels. We ascribed 21 SNPs to chromosome X based on their segregation patterns, and identified one additional marker that showed significant differentiation between sexes. For all applications considered, panels of autosomal SNPs showed higher power than the currently used STR set with only a very modest increase in the number of markers. These novel panels of highly informative genome-wide SNPs provide more powerful, efficient, and flexible tools for the genetic management and non-invasive monitoring of Iberian lynx populations. This example highlights an important outcome of whole-genome studies in genetically threatened species.
Kirsten, Holger; Al-Hasani, Hoor; Holdt, Lesca; Gross, Arnd; Beutner, Frank; Krohn, Knut; Horn, Katrin; Ahnert, Peter; Burkhardt, Ralph; Reiche, Kristin; Hackermüller, Jörg; Löffler, Markus; Teupser, Daniel; Thiery, Joachim; Scholz, Markus
2015-01-01
Genetics of gene expression (eQTLs or expression QTLs) has proved an indispensable tool for understanding biological pathways and pathomechanisms of trait-associated SNPs. However, power of most genome-wide eQTL studies is still limited. We performed a large eQTL study in peripheral blood mononuclear cells of 2112 individuals increasing the power to detect trans-effects genome-wide. Going beyond univariate SNP-transcript associations, we analyse relations of eQTLs to biological pathways, polygenetic effects of expression regulation, trans-clusters and enrichment of co-localized functional elements. We found eQTLs for about 85% of analysed genes, and 18% of genes were trans-regulated. Local eSNPs were enriched up to a distance of 5 Mb to the transcript challenging typically implemented ranges of cis-regulations. Pathway enrichment within regulated genes of GWAS-related eSNPs supported functional relevance of identified eQTLs. We demonstrate that nearest genes of GWAS-SNPs might frequently be misleading functional candidates. We identified novel trans-clusters of potential functional relevance for GWAS-SNPs of several phenotypes including obesity-related traits, HDL-cholesterol levels and haematological phenotypes. We used chromatin immunoprecipitation data for demonstrating biological effects. Yet, we show for strongly heritable transcripts that still little trans-chromosomal heritability is explained by all identified trans-eSNPs; however, our data suggest that most cis-heritability of these transcripts seems explained. Dissection of co-localized functional elements indicated a prominent role of SNPs in loci of pseudogenes and non-coding RNAs for the regulation of coding genes. In summary, our study substantially increases the catalogue of human eQTLs and improves our understanding of the complex genetic regulation of gene expression, pathways and disease-related processes. PMID:26019233
Chen, Kuan-Ju; Wolahan, Stephanie M.; Wang, Hao; Hsu, Chao-Hsiung; Chang, Hsing-Wei; Durazo, Armando; Hwang, Lian-Pin; Garcia, Mitch A.; Jiang, Ziyue Karen; Wu, Lily
2010-01-01
We introduce a new category of nanoparticle-based T1 MRI contrast agents (CAs) by encapsulating paramagnetic chelated gadolinium(III), i.e., Gd3+·DOTA, through supramolecular assembly of molecular building blocks that carry complementary molecular recognition motifs, including adamantane (Ad) and β-cyclodextrin (CD). A small library of Gd3+·DOTA-encapsulated supramolecular nanoparticles (Gd3+·DOTA⊂SNPs) was produced by systematically altering the molecular building block mixing ratios. A broad spectrum of relaxation rates was correlated to the resulting Gd3+·DOTA⊂SNP library. Consequently, an optimal synthetic formulation of Gd3+·DOTA⊂SNPs with an r1 of 17.3 s−1mM−1 (ca. 4-fold higher than clinical Gd3+ chelated complexes at high field strengths) was identified. T1-weighted imaging of Gd3+·DOTA⊂SNPs exhibits an enhanced sensitivity with a contrast-to-noise ratio (C/N ratio) ca. 3.6 times greater than that observed for free Gd3+·DTPA. A Gd3+·DOTA⊂SNPs solution was injected into foot pads of mice, and MRI was employed to monitor dynamic lymphatic drainage of the Gd3+·DOTA⊂SNPs-based CA. We observe an increase in signal intensity of the brachial lymph node in T1-weighted imaging after injecting Gd3+·DOTA⊂SNPs but not after injecting Gd3+·DTPA. The MRI results are supported by ICP-MS analysis ex vivo. These results show that Gd3+·DOTA⊂SNPs not only exhibits enhanced relaxivity and high sensitivity but also can serve as a potential tool for diagnosis of cancer metastasis. PMID:21167594
Gardner, Shea N.; Hall, Barry G.
2013-01-01
Effective use of rapid and inexpensive whole genome sequencing for microbes requires fast, memory efficient bioinformatics tools for sequence comparison. The kSNP v2 software finds single nucleotide polymorphisms (SNPs) in whole genome data. kSNP v2 has numerous improvements over kSNP v1 including SNP gene annotation; better scaling for draft genomes available as assembled contigs or raw, unassembled reads; a tool to identify the optimal value of k; distribution of packages of executables for Linux and Mac OS X for ease of installation and user-friendly use; and a detailed User Guide. SNP discovery is based on k-mer analysis, and requires no multiple sequence alignment or the selection of a single reference genome. Most target sets with hundreds of genomes complete in minutes to hours. SNP phylogenies are built by maximum likelihood, parsimony, and distance, based on all SNPs, only core SNPs, or SNPs present in some intermediate user-specified fraction of targets. The SNP-based trees that result are consistent with known taxonomy. kSNP v2 can handle many gigabases of sequence in a single run, and if one or more annotated genomes are included in the target set, SNPs are annotated with protein coding and other information (UTRs, etc.) from Genbank file(s). We demonstrate application of kSNP v2 on sets of viral and bacterial genomes, and discuss in detail analysis of a set of 68 finished E. coli and Shigella genomes and a set of the same genomes to which have been added 47 assemblies and four “raw read” genomes of H104:H4 strains from the recent European E. coli outbreak that resulted in both bloody diarrhea and hemolytic uremic syndrome (HUS), and caused at least 50 deaths. PMID:24349125
Gardner, Shea N; Hall, Barry G
2013-01-01
Effective use of rapid and inexpensive whole genome sequencing for microbes requires fast, memory efficient bioinformatics tools for sequence comparison. The kSNP v2 software finds single nucleotide polymorphisms (SNPs) in whole genome data. kSNP v2 has numerous improvements over kSNP v1 including SNP gene annotation; better scaling for draft genomes available as assembled contigs or raw, unassembled reads; a tool to identify the optimal value of k; distribution of packages of executables for Linux and Mac OS X for ease of installation and user-friendly use; and a detailed User Guide. SNP discovery is based on k-mer analysis, and requires no multiple sequence alignment or the selection of a single reference genome. Most target sets with hundreds of genomes complete in minutes to hours. SNP phylogenies are built by maximum likelihood, parsimony, and distance, based on all SNPs, only core SNPs, or SNPs present in some intermediate user-specified fraction of targets. The SNP-based trees that result are consistent with known taxonomy. kSNP v2 can handle many gigabases of sequence in a single run, and if one or more annotated genomes are included in the target set, SNPs are annotated with protein coding and other information (UTRs, etc.) from Genbank file(s). We demonstrate application of kSNP v2 on sets of viral and bacterial genomes, and discuss in detail analysis of a set of 68 finished E. coli and Shigella genomes and a set of the same genomes to which have been added 47 assemblies and four "raw read" genomes of H104:H4 strains from the recent European E. coli outbreak that resulted in both bloody diarrhea and hemolytic uremic syndrome (HUS), and caused at least 50 deaths.
Leong, Ivone U S; Stuckey, Alexander; Lai, Daniel; Skinner, Jonathan R; Love, Donald R
2015-05-13
Long QT syndrome (LQTS) is an autosomal dominant condition predisposing to sudden death from malignant arrhythmia. Genetic testing identifies many missense single nucleotide variants of uncertain pathogenicity. Establishing genetic pathogenicity is an essential prerequisite to family cascade screening. Many laboratories use in silico prediction tools, either alone or in combination, or metaservers, in order to predict pathogenicity; however, their accuracy in the context of LQTS is unknown. We evaluated the accuracy of five in silico programs and two metaservers in the analysis of LQTS 1-3 gene variants. The in silico tools SIFT, PolyPhen-2, PROVEAN, SNPs&GO and SNAP, either alone or in all possible combinations, and the metaservers Meta-SNP and PredictSNP, were tested on 312 KCNQ1, KCNH2 and SCN5A gene variants that have previously been characterised by either in vitro or co-segregation studies as either "pathogenic" (283) or "benign" (29). The accuracy, sensitivity, specificity and Matthews Correlation Coefficient (MCC) were calculated to determine the best combination of in silico tools for each LQTS gene, and when all genes are combined. The best combination of in silico tools for KCNQ1 is PROVEAN, SNPs&GO and SIFT (accuracy 92.7%, sensitivity 93.1%, specificity 100% and MCC 0.70). The best combination of in silico tools for KCNH2 is SIFT and PROVEAN or PROVEAN, SNPs&GO and SIFT. Both combinations have the same scores for accuracy (91.1%), sensitivity (91.5%), specificity (87.5%) and MCC (0.62). In the case of SCN5A, SNAP and PROVEAN provided the best combination (accuracy 81.4%, sensitivity 86.9%, specificity 50.0%, and MCC 0.32). When all three LQT genes are combined, SIFT, PROVEAN and SNAP is the combination with the best performance (accuracy 82.7%, sensitivity 83.0%, specificity 80.0%, and MCC 0.44). Both metaservers performed better than the single in silico tools; however, they did not perform better than the best performing combination of in silico tools. The combination of in silico tools with the best performance is gene-dependent. The in silico tools reported here may have some value in assessing variants in the KCNQ1 and KCNH2 genes, but caution should be taken when the analysis is applied to SCN5A gene variants.
Jayashree, B; Hanspal, Manindra S; Srinivasan, Rajgopal; Vigneshwaran, R; Varshney, Rajeev K; Spurthi, N; Eshwar, K; Ramesh, N; Chandra, S; Hoisington, David A
2007-01-01
The large amounts of EST sequence data available from a single species of an organism as well as for several species within a genus provide an easy source of identification of intra- and interspecies single nucleotide polymorphisms (SNPs). In the case of model organisms, the data available are numerous, given the degree of redundancy in the deposited EST data. There are several available bioinformatics tools that can be used to mine this data; however, using them requires a certain level of expertise: the tools have to be used sequentially with accompanying format conversion and steps like clustering and assembly of sequences become time-intensive jobs even for moderately sized datasets. We report here a pipeline of open source software extended to run on multiple CPU architectures that can be used to mine large EST datasets for SNPs and identify restriction sites for assaying the SNPs so that cost-effective CAPS assays can be developed for SNP genotyping in genetics and breeding applications. At the International Crops Research Institute for the Semi-Arid Tropics (ICRISAT), the pipeline has been implemented to run on a Paracel high-performance system consisting of four dual AMD Opteron processors running Linux with MPICH. The pipeline can be accessed through user-friendly web interfaces at http://hpc.icrisat.cgiar.org/PBSWeb and is available on request for academic use. We have validated the developed pipeline by mining chickpea ESTs for interspecies SNPs, development of CAPS assays for SNP genotyping, and confirmation of restriction digestion pattern at the sequence level.
Sulovari, Arvis; Li, Dawei
2014-07-19
Genome-wide association studies (GWAS) have successfully identified genes associated with complex human diseases. Although much of the heritability remains unexplained, combining single nucleotide polymorphism (SNP) genotypes from multiple studies for meta-analysis will increase the statistical power to identify new disease-associated variants. Meta-analysis requires same allele definition (nomenclature) and genome build among individual studies. Similarly, imputation, commonly-used prior to meta-analysis, requires the same consistency. However, the genotypes from various GWAS are generated using different genotyping platforms, arrays or SNP-calling approaches, resulting in use of different genome builds and allele definitions. Incorrect assumptions of identical allele definition among combined GWAS lead to a large portion of discarded genotypes or incorrect association findings. There is no published tool that predicts and converts among all major allele definitions. In this study, we have developed a tool, GACT, which stands for Genome build and Allele definition Conversion Tool, that predicts and inter-converts between any of the common SNP allele definitions and between the major genome builds. In addition, we assessed several factors that may affect imputation quality, and our results indicated that inclusion of singletons in the reference had detrimental effects while ambiguous SNPs had no measurable effect. Unexpectedly, exclusion of genotypes with missing rate > 0.001 (40% of study SNPs) showed no significant decrease of imputation quality (even significantly higher when compared to the imputation with singletons in the reference), especially for rare SNPs. GACT is a new, powerful, and user-friendly tool with both command-line and interactive online versions that can accurately predict, and convert between any of the common allele definitions and between genome builds for genome-wide meta-analysis and imputation of genotypes from SNP-arrays or deep-sequencing, particularly for data from the dbGaP and other public databases. http://www.uvm.edu/genomics/software/gact.
Pavy, Nathalie; Parsons, Lee S; Paule, Charles; MacKay, John; Bousquet, Jean
2006-01-01
Background High-throughput genotyping technologies represent a highly efficient way to accelerate genetic mapping and enable association studies. As a first step toward this goal, we aimed to develop a resource of candidate Single Nucleotide Polymorphisms (SNP) in white spruce (Picea glauca [Moench] Voss), a softwood tree of major economic importance. Results A white spruce SNP resource encompassing 12,264 SNPs was constructed from a set of 6,459 contigs derived from Expressed Sequence Tags (EST) and by using the bayesian-based statistical software PolyBayes. Several parameters influencing the SNP prediction were analysed including the a priori expected polymorphism, the probability score (PSNP), and the contig depth and length. SNP detection in 3' and 5' reads from the same clones revealed a level of inconsistency between overlapping sequences as low as 1%. A subset of 245 predicted SNPs were verified through the independent resequencing of genomic DNA of a genotype also used to prepare cDNA libraries. The validation rate reached a maximum of 85% for SNPs predicted with either PSNP ≥ 0.95 or ≥ 0.99. A total of 9,310 SNPs were detected by using PSNP ≥ 0.95 as a criterion. The SNPs were distributed among 3,590 contigs encompassing an array of broad functional categories, with an overall frequency of 1 SNP per 700 nucleotide sites. Experimental and statistical approaches were used to evaluate the proportion of paralogous SNPs, with estimates in the range of 8 to 12%. The 3,789 coding SNPs identified through coding region annotation and ORF prediction, were distributed into 39% nonsynonymous and 61% synonymous substitutions. Overall, there were 0.9 SNP per 1,000 nonsynonymous sites and 5.2 SNPs per 1,000 synonymous sites, for a genome-wide nonsynonymous to synonymous substitution rate ratio (Ka/Ks) of 0.17. Conclusion We integrated the SNP data in the ForestTreeDB database along with functional annotations to provide a tool facilitating the choice of candidate genes for mapping purposes or association studies. PMID:16824208
Huang, Chao-Wei; Lin, Yu-Tsung; Ding, Shih-Torng; Lo, Ling-Ling; Wang, Pei-Hwa; Lin, En-Chung; Liu, Fang-Wei; Lu, Yen-Wen
2015-01-01
The genetic markers associated with economic traits have been widely explored for animal breeding. Among these markers, single-nucleotide polymorphism (SNPs) are gradually becoming a prevalent and effective evaluation tool. Since SNPs only focus on the genetic sequences of interest, it thereby reduces the evaluation time and cost. Compared to traditional approaches, SNP genotyping techniques incorporate informative genetic background, improve the breeding prediction accuracy and acquiesce breeding quality on the farm. This article therefore reviews the typical procedures of animal breeding using SNPs and the current status of related techniques. The associated SNP information and genotyping techniques, including microarray and Lab-on-a-Chip based platforms, along with their potential are highlighted. Examples in pig and poultry with different SNP loci linked to high economic trait values are given. The recommendations for utilizing SNP genotyping in nimal breeding are summarized. PMID:27600241
DOE Office of Scientific and Technical Information (OSTI.GOV)
Gardner, Shea; Slezak, Tom
With the flood of whole genome finished and draft microbial sequences, we need faster, more scalable bioinformatics tools for sequence comparison. An algorithm is described to find single nucleotide polymorphisms (SNPs) in whole genome data. It scales to hundreds of bacterial or viral genomes, and can be used for finished and/or draft genomes available as unassembled contigs. The method is fast to compute, finding SNPs and building a SNP phylogeny in seconds to hours. We use it to identify thousands of putative SNPs from all publicly available Filoviridae, Poxviridae, foot-and-mouth disease virus, Bacillus, and Escherichia coli genomes and plasmids. Themore » SNP-based trees that result are consistent with known taxonomy and trees determined in other studies. The approach we describe can handle as input hundreds of gigabases of sequence in a single run. The algorithm is based on k-mer analysis using a suffix array, so we call it saSNP.« less
Scaltriti, Erika; Sassera, Davide; Comandatore, Francesco; Morganti, Marina; Mandalari, Carmen; Gaiarsa, Stefano; Bandi, Claudio; Zehender, Gianguglielmo; Bolzoni, Luca; Casadei, Gabriele
2015-01-01
We retrospectively analyzed a rare Salmonella enterica serovar Manhattan outbreak that occurred in Italy in 2009 to evaluate the potential of new genomic tools based on differential single nucleotide polymorphism (SNP) analysis in comparison with the gold standard genotyping method, pulsed-field gel electrophoresis. A total of 39 isolates were analyzed from patients (n = 15) and food, feed, animal, and environmental sources (n = 24), resulting in five different pulsed-field gel electrophoresis (PFGE) profiles. Isolates epidemiologically related to the outbreak clustered within the same pulsotype, SXB_BS.0003, without any further differentiation. Thirty-three isolates were considered for genomic analysis based on different sets of SNPs, core, synonymous, nonsynonymous, as well as SNPs in different codon positions, by Bayesian and maximum likelihood algorithms. Trees generated from core and nonsynonymous SNPs, as well as SNPs at the second and first plus second codon positions detailed four distinct groups of isolates within the outbreak pulsotype, discriminating outbreak-related isolates of human and food origins. Conversely, the trees derived from synonymous and third-codon-position SNPs clustered food and human isolates together, indicating that all outbreak-related isolates constituted a single clone, which was in line with the epidemiological evidence. Further experiments are in place to extend this approach within our regional enteropathogen surveillance system. PMID:25653407
Scaltriti, Erika; Sassera, Davide; Comandatore, Francesco; Morganti, Marina; Mandalari, Carmen; Gaiarsa, Stefano; Bandi, Claudio; Zehender, Gianguglielmo; Bolzoni, Luca; Casadei, Gabriele; Pongolini, Stefano
2015-04-01
We retrospectively analyzed a rare Salmonella enterica serovar Manhattan outbreak that occurred in Italy in 2009 to evaluate the potential of new genomic tools based on differential single nucleotide polymorphism (SNP) analysis in comparison with the gold standard genotyping method, pulsed-field gel electrophoresis. A total of 39 isolates were analyzed from patients (n=15) and food, feed, animal, and environmental sources (n=24), resulting in five different pulsed-field gel electrophoresis (PFGE) profiles. Isolates epidemiologically related to the outbreak clustered within the same pulsotype, SXB_BS.0003, without any further differentiation. Thirty-three isolates were considered for genomic analysis based on different sets of SNPs, core, synonymous, nonsynonymous, as well as SNPs in different codon positions, by Bayesian and maximum likelihood algorithms. Trees generated from core and nonsynonymous SNPs, as well as SNPs at the second and first plus second codon positions detailed four distinct groups of isolates within the outbreak pulsotype, discriminating outbreak-related isolates of human and food origins. Conversely, the trees derived from synonymous and third-codon-position SNPs clustered food and human isolates together, indicating that all outbreak-related isolates constituted a single clone, which was in line with the epidemiological evidence. Further experiments are in place to extend this approach within our regional enteropathogen surveillance system. Copyright © 2015, American Society for Microbiology. All Rights Reserved.
HapZipper: sharing HapMap populations just got easier.
Chanda, Pritam; Elhaik, Eran; Bader, Joel S
2012-11-01
The rapidly growing amount of genomic sequence data being generated and made publicly available necessitate the development of new data storage and archiving methods. The vast amount of data being shared and manipulated also create new challenges for network resources. Thus, developing advanced data compression techniques is becoming an integral part of data production and analysis. The HapMap project is one of the largest public resources of human single-nucleotide polymorphisms (SNPs), characterizing over 3 million SNPs genotyped in over 1000 individuals. The standard format and biological properties of HapMap data suggest that a dedicated genetic compression method can outperform generic compression tools. We propose a compression methodology for genetic data by introducing HapZipper, a lossless compression tool tailored to compress HapMap data beyond benchmarks defined by generic tools such as gzip, bzip2 and lzma. We demonstrate the usefulness of HapZipper by compressing HapMap 3 populations to <5% of their original sizes. HapZipper is freely downloadable from https://bitbucket.org/pchanda/hapzipper/downloads/HapZipper.tar.bz2.
Agrahari, Ashish Kumar; Muskan, Meghana; George Priya Doss, C; Siva, R; Zayed, Hatem
2018-05-27
The NF1 gene encodes for neurofibromin protein, which is ubiquitously expressed, but most highly in the central nervous system. Non-synonymous SNPs (nsSNPs) in the NF1 gene were found to be associated with Neurofibromatosis Type 1 disease, which is characterized by the growth of tumors along nerves in the skin, brain, and other parts of the body. In this study, we used several in silico predictions tools to analyze 16 nsSNPs in the RAS-GAP domain of neurofibromin, the K1444N (K1423N) mutation was predicted as the most pathogenic. The comparative molecular dynamic simulation (MDS; 50 ns) between the wild type and the K1444N (K1423N) mutant suggested a significant change in the electrostatic potential. In addition, the RMSD, RMSF, Rg, hydrogen bonds, and PCA analysis confirmed the loss of flexibility and increase in compactness of the mutant protein. Further, SASA analysis revealed exchange between hydrophobic and hydrophilic residues from the core of the RAS-GAP domain to the surface of the mutant domain, consistent with the secondary structure analysis that showed significant alteration in the mutant protein conformation. Our data concludes that the K1444N (K1423N) mutant lead to increasing the rigidity and compactness of the protein. This study provides evidence of the benefits of the computational tools in predicting the pathogenicity of genetic mutations and suggests the application of MDS and different in silico prediction tools for variant assessment and classification in genetic clinics.
Use of a draft genome of coffee (Coffea arabica) to identify SNPs associated with caffeine content.
Tran, Hue T M; Ramaraj, Thiruvarangan; Furtado, Agnelo; Lee, Leonard Slade; Henry, Robert J
2018-03-07
Arabica coffee (Coffea arabica) has a small gene pool limiting genetic improvement. Selection for caffeine content within this gene pool would be assisted by identification of the genes controlling this important trait. Sequencing of DNA bulks from 18 genotypes with extreme high- or low-caffeine content from a population of 232 genotypes was used to identify linked polymorphisms. To obtain a reference genome, a whole genome assembly of arabica coffee (variety K7) was achieved by sequencing using short read (Illumina) and long-read (PacBio) technology. Assembly was performed using a range of assembly tools resulting in 76 409 scaffolds with a scaffold N50 of 54 544 bp and a total scaffold length of 1448 Mb. Validation of the genome assembly using different tools showed high completeness of the genome. More than 99% of transcriptome sequences mapped to the C. arabica draft genome, and 89% of BUSCOs were present. The assembled genome annotated using AUGUSTUS yielded 99 829 gene models. Using the draft arabica genome as reference in mapping and variant calling allowed the detection of 1444 nonsynonymous single nucleotide polymorphisms (SNPs) associated with caffeine content. Based on Kyoto Encyclopaedia of Genes and Genomes pathway-based analysis, 65 caffeine-associated SNPs were discovered, among which 11 SNPs were associated with genes encoding enzymes involved in the conversion of substrates, which participate in the caffeine biosynthesis pathways. This analysis demonstrated the complex genetic control of this key trait in coffee. © 2018 The Authors. Plant Biotechnology Journal published by Society for Experimental Biology and The Association of Applied Biologists and John Wiley & Sons Ltd.
Catalog of MicroRNA Seed Polymorphisms in Vertebrates
Calin, George Adrian; Horvat, Simon; Jiang, Zhihua; Dovc, Peter; Kunej, Tanja
2012-01-01
MicroRNAs (miRNAs) are a class of non-coding RNA that plays an important role in posttranscriptional regulation of mRNA. Evidence has shown that miRNA gene variability might interfere with its function resulting in phenotypic variation and disease susceptibility. A major role in miRNA target recognition is ascribed to complementarity with the miRNA seed region that can be affected by polymorphisms. In the present study, we developed an online tool for the detection of miRNA polymorphisms (miRNA SNiPer) in vertebrates (http://www.integratomics-time.com/miRNA-SNiPer) and generated a catalog of miRNA seed region polymorphisms (miR-seed-SNPs) consisting of 149 SNPs in six species. Although a majority of detected polymorphisms were due to point mutations, two consecutive nucleotide substitutions (double nucleotide polymorphisms, DNPs) were also identified in nine miRNAs. We determined that miR-SNPs are frequently located within the quantitative trait loci (QTL), chromosome fragile sites, and cancer susceptibility loci, indicating their potential role in the genetic control of various complex traits. To test this further, we performed an association analysis between the mmu-miR-717 seed SNP rs30372501, which is polymorphic in a large number of standard inbred strains, and all phenotypic traits in these strains deposited in the Mouse Phenome Database. Analysis showed a significant association between the mmu-miR-717 seed SNP and a diverse array of traits including behavior, blood-clinical chemistry, body weight size and growth, and immune system suggesting that seed SNPs can indeed have major pleiotropic effects. The bioinformatics analyses, data and tools developed in the present study can serve researchers as a starting point in testing more targeted hypotheses and designing experiments using optimal species or strains for further mechanistic studies. PMID:22303453
Knecht, Carolin; Mort, Matthew; Junge, Olaf; Cooper, David N.; Krawczak, Michael
2017-01-01
Abstract The in silico prediction of the functional consequences of mutations is an important goal of human pathogenetics. However, bioinformatic tools that classify mutations according to their functionality employ different algorithms so that predictions may vary markedly between tools. We therefore integrated nine popular prediction tools (PolyPhen-2, SNPs&GO, MutPred, SIFT, MutationTaster2, Mutation Assessor and FATHMM as well as conservation-based Grantham Score and PhyloP) into a single predictor. The optimal combination of these tools was selected by means of a wide range of statistical modeling techniques, drawing upon 10 029 disease-causing single nucleotide variants (SNVs) from Human Gene Mutation Database and 10 002 putatively ‘benign’ non-synonymous SNVs from UCSC. Predictive performance was found to be markedly improved by model-based integration, whilst maximum predictive capability was obtained with either random forest, decision tree or logistic regression analysis. A combination of PolyPhen-2, SNPs&GO, MutPred, MutationTaster2 and FATHMM was found to perform as well as all tools combined. Comparison of our approach with other integrative approaches such as Condel, CoVEC, CAROL, CADD, MetaSVM and MetaLR using an independent validation dataset, revealed the superiority of our newly proposed integrative approach. An online implementation of this approach, IMHOTEP (‘Integrating Molecular Heuristics and Other Tools for Effect Prediction’), is provided at http://www.uni-kiel.de/medinfo/cgi-bin/predictor/. PMID:28180317
Hagstrom, Stephanie A; Ying, Gui-shuang; Pauer, Gayle J T; Sturgill-Short, Gwen M; Huang, Jiayan; Maguire, Maureen G; Martin, Daniel F
2014-05-01
Individual variation in response and duration of anti-vascular endothelial growth factor (VEGF) therapy is seen among patients with neovascular age-related macular degeneration. Identification of genetic markers that affect clinical response may result in optimization of anti-VEGF therapy. To evaluate the pharmacogenetic relationship between genotypes of single-nucleotide polymorphisms (SNPs) in the VEGF signaling pathway and response to treatment with ranibizumab or bevacizumab for neovascular age-related macular degeneration. In total, 835 of 1149 patients (72.7%) participating in the Comparison of Age-Related Macular Degeneration Treatments Trials (CATT) at 43 CATT clinical centers. Each patient was genotyped for 7 SNPs in VEGFA (rs699946, rs699947, rs833069, rs833070, rs1413711, rs2010963, and rs2146323) and 1 SNP in VEGFR2 (rs2071559) using TaqMan SNP genotyping assays. Genotypic frequencies were compared with clinical measures of response to therapy at 1 year, including the mean visual acuity, mean change in visual acuity, at least a 15-letter increase, retinal thickness, mean change in total foveal thickness, presence of fluid on optical coherence tomography, presence of leakage on fluorescein angiography, mean change in lesion size, and mean number of injections administered. Differences in response by genotype were evaluated with tests of linear trend calculated from logistic regression models for categorical outcomes and linear regression models for continuous outcomes. The method of controlling the false discovery rate was used to adjust for multiple comparisons. For each of the measures of visual acuity evaluated, no association was observed with any of the genotypes or with the number of risk alleles. Four VEGFA SNPs demonstrated an association with retinal thickness: rs699947 (P = .03), rs833070 (P = .04), rs1413711 (P = .045), and rs2146323 (P = .006). However, adjusted P values for these associations were all statistically nonsignificant (range, P = .24 to P = .45). Among the participants in 2 as-needed groups, no association was found in the number of injections among the different genotypes or for the total number of risk alleles. The effect of risk alleles on each clinical measure did not differ by treatment group, drug, or dosing regimen (P > .01 for all). This study provides evidence that no pharmacogenetic associations exist between the studied VEGFA and VEGFR2 SNPs and response to anti-VEGF therapy. clinicaltrials.gov Identifier: NCT00593450.
Dima, Danai; de Jong, Simone; Breen, Gerome; Frangou, Sophia
2016-01-01
Genome-wise association studies have identified a number of common single-nucleotide polymorphisms (SNPs), each of small effect, associated with risk to bipolar disorder (BD). Several risk-conferring SNPs have been individually shown to influence regional brain activation thus linking genetic risk for BD to altered brain function. The current study examined whether the polygenic risk score method, which models the cumulative load of all known risk-conferring SNPs, may be useful in the identification of brain regions whose function may be related to the polygenic architecture of BD. We calculated the individual polygenic risk score for BD (PGR-BD) in forty-one patients with the disorder, twenty-five unaffected first-degree relatives and forty-six unrelated healthy controls using the most recent Psychiatric Genomics Consortium data. Functional magnetic resonance imaging was used to define task-related brain activation patterns in response to facial affect and working memory processing. We found significant effects of the PGR-BD score on task-related activation irrespective of diagnostic group. There was a negative association between the PGR-BD score and activation in the visual association cortex during facial affect processing. In contrast, the PGR-BD score was associated with failure to deactivate the ventromedial prefrontal region of the default mode network during working memory processing. These results are consistent with the threshold-liability model of BD, and demonstrate the usefulness of the PGR-BD score in identifying brain functional alternations associated with vulnerability to BD. Additionally, our findings suggest that the polygenic architecture of BD is not regionally confined but impacts on the task-dependent recruitment of multiple brain regions.
In search of causal variants: refining disease association signals using cross-population contrasts.
Saccone, Nancy L; Saccone, Scott F; Goate, Alison M; Grucza, Richard A; Hinrichs, Anthony L; Rice, John P; Bierut, Laura J
2008-08-29
Genome-wide association (GWA) using large numbers of single nucleotide polymorphisms (SNPs) is now a powerful, state-of-the-art approach to mapping human disease genes. When a GWA study detects association between a SNP and the disease, this signal usually represents association with a set of several highly correlated SNPs in strong linkage disequilibrium. The challenge we address is to distinguish among these correlated loci to highlight potential functional variants and prioritize them for follow-up. We implemented a systematic method for testing association across diverse population samples having differing histories and LD patterns, using a logistic regression framework. The hypothesis is that important underlying biological mechanisms are shared across human populations, and we can filter correlated variants by testing for heterogeneity of genetic effects in different population samples. This approach formalizes the descriptive comparison of p-values that has typified similar cross-population fine-mapping studies to date. We applied this method to correlated SNPs in the cholinergic nicotinic receptor gene cluster CHRNA5-CHRNA3-CHRNB4, in a case-control study of cocaine dependence composed of 504 European-American and 583 African-American samples. Of the 10 SNPs genotyped in the r2 > or = 0.8 bin for rs16969968, three demonstrated significant cross-population heterogeneity and are filtered from priority follow-up; the remaining SNPs include rs16969968 (heterogeneity p = 0.75). Though the power to filter out rs16969968 is reduced due to the difference in allele frequency in the two groups, the results nevertheless focus attention on a smaller group of SNPs that includes the non-synonymous SNP rs16969968, which retains a similar effect size (odds ratio) across both population samples. Filtering out SNPs that demonstrate cross-population heterogeneity enriches for variants more likely to be important and causative. Our approach provides an important and effective tool to help interpret results from the many GWA studies now underway.
Kirsten, Holger; Al-Hasani, Hoor; Holdt, Lesca; Gross, Arnd; Beutner, Frank; Krohn, Knut; Horn, Katrin; Ahnert, Peter; Burkhardt, Ralph; Reiche, Kristin; Hackermüller, Jörg; Löffler, Markus; Teupser, Daniel; Thiery, Joachim; Scholz, Markus
2015-08-15
Genetics of gene expression (eQTLs or expression QTLs) has proved an indispensable tool for understanding biological pathways and pathomechanisms of trait-associated SNPs. However, power of most genome-wide eQTL studies is still limited. We performed a large eQTL study in peripheral blood mononuclear cells of 2112 individuals increasing the power to detect trans-effects genome-wide. Going beyond univariate SNP-transcript associations, we analyse relations of eQTLs to biological pathways, polygenetic effects of expression regulation, trans-clusters and enrichment of co-localized functional elements. We found eQTLs for about 85% of analysed genes, and 18% of genes were trans-regulated. Local eSNPs were enriched up to a distance of 5 Mb to the transcript challenging typically implemented ranges of cis-regulations. Pathway enrichment within regulated genes of GWAS-related eSNPs supported functional relevance of identified eQTLs. We demonstrate that nearest genes of GWAS-SNPs might frequently be misleading functional candidates. We identified novel trans-clusters of potential functional relevance for GWAS-SNPs of several phenotypes including obesity-related traits, HDL-cholesterol levels and haematological phenotypes. We used chromatin immunoprecipitation data for demonstrating biological effects. Yet, we show for strongly heritable transcripts that still little trans-chromosomal heritability is explained by all identified trans-eSNPs; however, our data suggest that most cis-heritability of these transcripts seems explained. Dissection of co-localized functional elements indicated a prominent role of SNPs in loci of pseudogenes and non-coding RNAs for the regulation of coding genes. In summary, our study substantially increases the catalogue of human eQTLs and improves our understanding of the complex genetic regulation of gene expression, pathways and disease-related processes. © The Author 2015. Published by Oxford University Press.
Esteves, F; Gaspar, J; de Sousa, B; Antunes, F; Mansinho, K; Matos, O
2012-06-01
Specific single-nucleotide polymorphisms (SNPs) are recognized as important DNA sequence variations influencing the pathogenesis of Pneumocystis jirovecii and the clinical outcome of Pneumocystis pneumonia, which is a major worldwide cause of illness among immunocompromised patients. Genotyping platforms for pooled DNA samples are promising methodologies for genetic characterization of infectious organisms. We have developed a new typing strategy for P. jirovecii, which consisted of DNA pools prepared according to clinical data (HIV diagnosis, microscopic and molecular detection of P. jirovecii, parasite burden, clinical diagnosis and follow-up of infection) from individual samples using quantitative real-time PCR followed by multiplex-PCR/single base extension (MPCR/SBE). The frequencies of multiple P. jirovecii SNPs (DHFR312, mt85, SOD215 and SOD110) encoded at three distinct loci, the dihydrofolate reductase (DHFR), the mitochondrial large-subunit rRNA (mtLSU rRNA) and the superoxide dismutase (SOD) loci, were estimated in seven DNA pooled samples, representing a total of 100 individual samples. The studied SNPs were confirmed to be associated with distinct clinical parameters of infection such as parasite burden and follow-up. The MPCR/SBE-DNA pooling methodology, described in the present study, was demonstrated to be a useful high-throughput procedure for large-scale P. jirovecii SNPs screening and a powerful tool for evaluation of clinically relevant SNPs potentially related to parasite burden, clinical diagnosis and follow-up of P. jirovecii infection. In further studies, the candidate SNPs mt85, SOD215 and SOD110 may be used as molecular markers in association with MPCR/SBE-DNA pooling to generate useful information for understanding the patterns and causes of Pneumocystis pneumonia. © 2012 The Authors. Clinical Microbiology and Infection © 2012 European Society of Clinical Microbiology and Infectious Diseases.
Waide, Emily H; Tuggle, Christopher K; Serão, Nick V L; Schroyen, Martine; Hess, Andrew; Rowland, Raymond R R; Lunney, Joan K; Plastow, Graham; Dekkers, Jack C M
2018-02-01
Genomic prediction of the pig's response to the porcine reproductive and respiratory syndrome (PRRS) virus (PRRSV) would be a useful tool in the swine industry. This study investigated the accuracy of genomic prediction based on porcine SNP60 Beadchip data using training and validation datasets from populations with different genetic backgrounds that were challenged with different PRRSV isolates. Genomic prediction accuracy averaged 0.34 for viral load (VL) and 0.23 for weight gain (WG) following experimental PRRSV challenge, which demonstrates that genomic selection could be used to improve response to PRRSV infection. Training on WG data during infection with a less virulent PRRSV, KS06, resulted in poor accuracy of prediction for WG during infection with a more virulent PRRSV, NVSL. Inclusion of single nucleotide polymorphisms (SNPs) that are in linkage disequilibrium with a major quantitative trait locus (QTL) on chromosome 4 was vital for accurate prediction of VL. Overall, SNPs that were significantly associated with either trait in single SNP genome-wide association analysis were unable to predict the phenotypes with an accuracy as high as that obtained by using all genotyped SNPs across the genome. Inclusion of data from close relatives into the training population increased whole genome prediction accuracy by 33% for VL and by 37% for WG but did not affect the accuracy of prediction when using only SNPs in the major QTL region. Results show that genomic prediction of response to PRRSV infection is moderately accurate and, when using all SNPs on the porcine SNP60 Beadchip, is not very sensitive to differences in virulence of the PRRSV in training and validation populations. Including close relatives in the training population increased prediction accuracy when using the whole genome or SNPs other than those near a major QTL.
Rašić, Gordana; Filipović, Igor; Weeks, Andrew R; Hoffmann, Ary A
2014-04-11
Genetic markers are widely used to understand the biology and population dynamics of disease vectors, but often markers are limited in the resolution they provide. In particular, the delineation of population structure, fine scale movement and patterns of relatedness are often obscured unless numerous markers are available. To address this issue in the major arbovirus vector, the yellow fever mosquito (Aedes aegypti), we used double digest Restriction-site Associated DNA (ddRAD) sequencing for the discovery of genome-wide single nucleotide polymorphisms (SNPs). We aimed to characterize the new SNP set and to test the resolution against previously described microsatellite markers in detecting broad and fine-scale genetic patterns in Ae. aegypti. We developed bioinformatics tools that support the customization of restriction enzyme-based protocols for SNP discovery. We showed that our approach for RAD library construction achieves unbiased genome representation that reflects true evolutionary processes. In Ae. aegypti samples from three continents we identified more than 18,000 putative SNPs. They were widely distributed across the three Ae. aegypti chromosomes, with 47.9% found in intergenic regions and 17.8% in exons of over 2,300 genes. Pattern of their imputed effects in ORFs and UTRs were consistent with those found in a recent transcriptome study. We demonstrated that individual mosquitoes from Indonesia, Australia, Vietnam and Brazil can be assigned with a very high degree of confidence to their region of origin using a large SNP panel. We also showed that familial relatedness of samples from a 0.4 km2 area could be confidently established with a subset of SNPs. Using a cost-effective customized RAD sequencing approach supported by our bioinformatics tools, we characterized over 18,000 SNPs in field samples of the dengue fever mosquito Ae. aegypti. The variants were annotated and positioned onto the three Ae. aegypti chromosomes. The new SNP set provided much greater resolution in detecting population structure and estimating fine-scale relatedness than a set of polymorphic microsatellites. RAD-based markers demonstrate great potential to advance our understanding of mosquito population processes, critical for implementing new control measures against this major disease vector.
Park, George D; Reed, Catherine L
2015-10-01
Despite attentional prioritization for grasping space near the hands, tool-use appears to transfer attentional bias to the tool's end/functional part. The contributions of haptic and visual inputs to attentional distribution along a tool were investigated as a function of tool-use in near (Experiment 1) and far (Experiment 2) space. Visual attention was assessed with a 50/50, go/no-go, target discrimination task, while a tool was held next to targets appearing near the tool-occupied hand or tool-end. Target response times (RTs) and sensitivity (d-prime) were measured at target locations, before and after functional tool practice for three conditions: (1) open-tool: tool-end visible (visual + haptic inputs), (2) hidden-tool: tool-end visually obscured (haptic input only), and (3) short-tool: stick missing tool's length/end (control condition: hand occupied but no visual/haptic input). In near space, both open- and hidden-tool groups showed a tool-end, attentional bias (faster RTs toward tool-end) before practice; after practice, RTs near the hand improved. In far space, the open-tool group showed no bias before practice; after practice, target RTs near the tool-end improved. However, the hidden-tool group showed a consistent tool-end bias despite practice. Lack of short-tool group results suggested that hidden-tool group results were specific to haptic inputs. In conclusion, (1) allocation of visual attention along a tool due to tool practice differs in near and far space, and (2) visual attention is drawn toward the tool's end even when visually obscured, suggesting haptic input provides sufficient information for directing attention along the tool.
SNP-RFLPing 2: an updated and integrated PCR-RFLP tool for SNP genotyping.
Chang, Hsueh-Wei; Cheng, Yu-Huei; Chuang, Li-Yeh; Yang, Cheng-Hong
2010-04-08
PCR-restriction fragment length polymorphism (RFLP) assay is a cost-effective method for SNP genotyping and mutation detection, but the manual mining for restriction enzyme sites is challenging and cumbersome. Three years after we constructed SNP-RFLPing, a freely accessible database and analysis tool for restriction enzyme mining of SNPs, significant improvements over the 2006 version have been made and incorporated into the latest version, SNP-RFLPing 2. The primary aim of SNP-RFLPing 2 is to provide comprehensive PCR-RFLP information with multiple functionality about SNPs, such as SNP retrieval to multiple species, different polymorphism types (bi-allelic, tri-allelic, tetra-allelic or indels), gene-centric searching, HapMap tagSNPs, gene ontology-based searching, miRNAs, and SNP500Cancer. The RFLP restriction enzymes and the corresponding PCR primers for the natural and mutagenic types of each SNP are simultaneously analyzed. All the RFLP restriction enzyme prices are also provided to aid selection. Furthermore, the previously encountered updating problems for most SNP related databases are resolved by an on-line retrieval system. The user interfaces for functional SNP analyses have been substantially improved and integrated. SNP-RFLPing 2 offers a new and user-friendly interface for RFLP genotyping that can be used in association studies and is freely available at http://bio.kuas.edu.tw/snp-rflping2.
Optimal Design of Low-Density SNP Arrays for Genomic Prediction: Algorithm and Applications.
Wu, Xiao-Lin; Xu, Jiaqi; Feng, Guofei; Wiggans, George R; Taylor, Jeremy F; He, Jun; Qian, Changsong; Qiu, Jiansheng; Simpson, Barry; Walker, Jeremy; Bauck, Stewart
2016-01-01
Low-density (LD) single nucleotide polymorphism (SNP) arrays provide a cost-effective solution for genomic prediction and selection, but algorithms and computational tools are needed for the optimal design of LD SNP chips. A multiple-objective, local optimization (MOLO) algorithm was developed for design of optimal LD SNP chips that can be imputed accurately to medium-density (MD) or high-density (HD) SNP genotypes for genomic prediction. The objective function facilitates maximization of non-gap map length and system information for the SNP chip, and the latter is computed either as locus-averaged (LASE) or haplotype-averaged Shannon entropy (HASE) and adjusted for uniformity of the SNP distribution. HASE performed better than LASE with ≤1,000 SNPs, but required considerably more computing time. Nevertheless, the differences diminished when >5,000 SNPs were selected. Optimization was accomplished conditionally on the presence of SNPs that were obligated to each chromosome. The frame location of SNPs on a chip can be either uniform (evenly spaced) or non-uniform. For the latter design, a tunable empirical Beta distribution was used to guide location distribution of frame SNPs such that both ends of each chromosome were enriched with SNPs. The SNP distribution on each chromosome was finalized through the objective function that was locally and empirically maximized. This MOLO algorithm was capable of selecting a set of approximately evenly-spaced and highly-informative SNPs, which in turn led to increased imputation accuracy compared with selection solely of evenly-spaced SNPs. Imputation accuracy increased with LD chip size, and imputation error rate was extremely low for chips with ≥3,000 SNPs. Assuming that genotyping or imputation error occurs at random, imputation error rate can be viewed as the upper limit for genomic prediction error. Our results show that about 25% of imputation error rate was propagated to genomic prediction in an Angus population. The utility of this MOLO algorithm was also demonstrated in a real application, in which a 6K SNP panel was optimized conditional on 5,260 obligatory SNP selected based on SNP-trait association in U.S. Holstein animals. With this MOLO algorithm, both imputation error rate and genomic prediction error rate were minimal.
Ribeiro, Antonio; Golicz, Agnieszka; Hackett, Christine Anne; Milne, Iain; Stephen, Gordon; Marshall, David; Flavell, Andrew J; Bayer, Micha
2015-11-11
Single Nucleotide Polymorphisms (SNPs) are widely used molecular markers, and their use has increased massively since the inception of Next Generation Sequencing (NGS) technologies, which allow detection of large numbers of SNPs at low cost. However, both NGS data and their analysis are error-prone, which can lead to the generation of false positive (FP) SNPs. We explored the relationship between FP SNPs and seven factors involved in mapping-based variant calling - quality of the reference sequence, read length, choice of mapper and variant caller, mapping stringency and filtering of SNPs by read mapping quality and read depth. This resulted in 576 possible factor level combinations. We used error- and variant-free simulated reads to ensure that every SNP found was indeed a false positive. The variation in the number of FP SNPs generated ranged from 0 to 36,621 for the 120 million base pairs (Mbp) genome. All of the experimental factors tested had statistically significant effects on the number of FP SNPs generated and there was a considerable amount of interaction between the different factors. Using a fragmented reference sequence led to a dramatic increase in the number of FP SNPs generated, as did relaxed read mapping and a lack of SNP filtering. The choice of reference assembler, mapper and variant caller also significantly affected the outcome. The effect of read length was more complex and suggests a possible interaction between mapping specificity and the potential for contributing more false positives as read length increases. The choice of tools and parameters involved in variant calling can have a dramatic effect on the number of FP SNPs produced, with particularly poor combinations of software and/or parameter settings yielding tens of thousands in this experiment. Between-factor interactions make simple recommendations difficult for a SNP discovery pipeline but the quality of the reference sequence is clearly of paramount importance. Our findings are also a stark reminder that it can be unwise to use the relaxed mismatch settings provided as defaults by some read mappers when reads are being mapped to a relatively unfinished reference sequence from e.g. a non-model organism in its early stages of genomic exploration.
Optimal Design of Low-Density SNP Arrays for Genomic Prediction: Algorithm and Applications
Wu, Xiao-Lin; Xu, Jiaqi; Feng, Guofei; Wiggans, George R.; Taylor, Jeremy F.; He, Jun; Qian, Changsong; Qiu, Jiansheng; Simpson, Barry; Walker, Jeremy; Bauck, Stewart
2016-01-01
Low-density (LD) single nucleotide polymorphism (SNP) arrays provide a cost-effective solution for genomic prediction and selection, but algorithms and computational tools are needed for the optimal design of LD SNP chips. A multiple-objective, local optimization (MOLO) algorithm was developed for design of optimal LD SNP chips that can be imputed accurately to medium-density (MD) or high-density (HD) SNP genotypes for genomic prediction. The objective function facilitates maximization of non-gap map length and system information for the SNP chip, and the latter is computed either as locus-averaged (LASE) or haplotype-averaged Shannon entropy (HASE) and adjusted for uniformity of the SNP distribution. HASE performed better than LASE with ≤1,000 SNPs, but required considerably more computing time. Nevertheless, the differences diminished when >5,000 SNPs were selected. Optimization was accomplished conditionally on the presence of SNPs that were obligated to each chromosome. The frame location of SNPs on a chip can be either uniform (evenly spaced) or non-uniform. For the latter design, a tunable empirical Beta distribution was used to guide location distribution of frame SNPs such that both ends of each chromosome were enriched with SNPs. The SNP distribution on each chromosome was finalized through the objective function that was locally and empirically maximized. This MOLO algorithm was capable of selecting a set of approximately evenly-spaced and highly-informative SNPs, which in turn led to increased imputation accuracy compared with selection solely of evenly-spaced SNPs. Imputation accuracy increased with LD chip size, and imputation error rate was extremely low for chips with ≥3,000 SNPs. Assuming that genotyping or imputation error occurs at random, imputation error rate can be viewed as the upper limit for genomic prediction error. Our results show that about 25% of imputation error rate was propagated to genomic prediction in an Angus population. The utility of this MOLO algorithm was also demonstrated in a real application, in which a 6K SNP panel was optimized conditional on 5,260 obligatory SNP selected based on SNP-trait association in U.S. Holstein animals. With this MOLO algorithm, both imputation error rate and genomic prediction error rate were minimal. PMID:27583971
Wang, Cathy K; Xu, Michael S; Ross, Colin J; Lo, Ryan; Procyshyn, Ric M; Vila-Rodriguez, Fidel; White, Randall F; Honer, William G; Barr, Alasdair M
2015-09-01
Brain derived neurotrophic factor (BDNF) is a molecular trophic factor that plays a key role in neuronal survival and plasticity. Single nucleotide polymorphisms (SNPs) of the BDNF gene have been associated with specific phenotypic traits in a large number of neuropsychiatric disorders and the response to psychotherapeutic medications in patient populations. Nevertheless, due to study differences and occasionally contrasting findings, substantial further research is required to understand in better detail the association between specific BDNF SNPs and these psychiatric disorders. While considerable progress has been made recently in developing advanced genotyping platforms of SNPs, many high-throughput probe- or array-based detection methods currently available are limited by high costs, slow processing times or access to advanced instrumentation. The polymerase chain reaction (PCR)-based, tetra-primer amplification refractory mutation system (T-ARMS) method is a potential alternative technique for detecting SNP genotypes efficiently, quickly, easily, and cheaply. As a tool in psychopathology research, T-ARMS was shown to be capable of detecting five common SNPs in the BDNF gene (rs6265, rs988748, rs11030104, 11757G/C and rs7103411), which are all SNPs with previously demonstrated clinical relevance to schizophrenia and depression. The present technique therefore represents a suitable protocol for many research laboratories to study the genetic correlates of BDNF in psychiatric disorders. Copyright Copyright © 2015 John Wiley & Sons, Ltd. Copyright © 2015 John Wiley & Sons, Ltd.
Lack of Association for Reported Endocrine Pancreatic Cancer Risk Loci in the PANDoRA Consortium.
Campa, Daniele; Obazee, Ofure; Pastore, Manuela; Panzuto, Francesco; Liço, Valbona; Greenhalf, William; Katzke, Verena; Tavano, Francesca; Costello, Eithne; Corbo, Vincenzo; Talar-Wojnarowska, Renata; Strobel, Oliver; Zambon, Carlo Federico; Neoptolemos, John P; Zerboni, Giulia; Kaaks, Rudolf; Key, Timothy J; Lombardo, Carlo; Jamroziak, Krzysztof; Gioffreda, Domenica; Hackert, Thilo; Khaw, Kay-Tee; Landi, Stefano; Milanetto, Anna Caterina; Landoni, Luca; Lawlor, Rita T; Bambi, Franco; Pirozzi, Felice; Basso, Daniela; Pasquali, Claudio; Capurso, Gabriele; Canzian, Federico
2017-08-01
Background: Pancreatic neuroendocrine tumors (PNETs) are rare neoplasms for which very little is known about either environmental or genetic risk factors. Only a handful of association studies have been performed so far, suggesting a small number of risk loci. Methods: To replicate the best findings, we have selected 16 SNPs suggested in previous studies to be relevant in PNET etiogenesis. We genotyped the selected SNPs (rs16944, rs1052536, rs1059293, rs1136410, rs1143634, rs2069762, rs2236302, rs2387632, rs3212961, rs3734299, rs3803258, rs4962081, rs7234941, rs7243091, rs12957119, and rs1800629) in 344 PNET sporadic cases and 2,721 controls in the context of the PANcreatic Disease ReseArch (PANDoRA) consortium. Results: After correction for multiple testing, we did not observe any statistically significant association between the SNPs and PNET risk. We also used three online bioinformatic tools (HaploReg, RegulomeDB, and GTEx) to predict a possible functional role of the SNPs, but we did not observe any clear indication. Conclusions: None of the selected SNPs were convincingly associated with PNET risk in the PANDoRA consortium. Impact: We can exclude a major role of the selected polymorphisms in PNET etiology, and this highlights the need for replication of epidemiologic findings in independent populations, especially in rare diseases such as PNETs. Cancer Epidemiol Biomarkers Prev; 26(8); 1349-51. ©2017 AACR . ©2017 American Association for Cancer Research.
Singh, Kanhaiya; Agrawal, Neeraj K.; Gupta, Sanjeev K.
2013-01-01
The Toll-Like receptor 4 (TLR4) plays an important role in immunity, tissue repair, and regeneration. The objective of the present work was to evaluate the association of TLR4 single nucleotide polymorphisms (SNPs) rs4986790, rs4986791, rs11536858 (merged into rs10759931), rs1927911, and rs1927914 with increased diabetic foot ulcer (DFU) risk in patients with type 2 diabetes mellitus (T2DM). PCR-RFLP was used for genotyping TLR4 SNPs in 125 T2DM patients with DFU and 130 controls. The haplotypes and linkage disequilibrium between the SNPs were determined using Haploview software. Multivariate linear regression (MLR) and artificial neural network (ANN) modeling was done to observe their predictability for the risk of DFU in T2DM patients. Risk genotypes of all SNPs except rs1927914 were significantly associated with DFU. Haplotype ACATC (P value = 9.3E − 5) showed strong association with DFU risk. Two haplotypes ATATC (P value = 0.0119) and ATGTT (P value = 0.0087) were found to be protective against DFU. In conclusion TLR4 SNPs and their haplotypes may increase the risk of impairment of wound healing in T2DM patients. ANN model (83%) is found to be better than the MLR model (76%) and can be used as a tool for the DFU risk assessment in T2DM patients. PMID:23936790
MultiBLUP: improved SNP-based prediction for complex traits.
Speed, Doug; Balding, David J
2014-09-01
BLUP (best linear unbiased prediction) is widely used to predict complex traits in plant and animal breeding, and increasingly in human genetics. The BLUP mathematical model, which consists of a single random effect term, was adequate when kinships were measured from pedigrees. However, when genome-wide SNPs are used to measure kinships, the BLUP model implicitly assumes that all SNPs have the same effect-size distribution, which is a severe and unnecessary limitation. We propose MultiBLUP, which extends the BLUP model to include multiple random effects, allowing greatly improved prediction when the random effects correspond to classes of SNPs with distinct effect-size variances. The SNP classes can be specified in advance, for example, based on SNP functional annotations, and we also provide an adaptive procedure for determining a suitable partition of SNPs. We apply MultiBLUP to genome-wide association data from the Wellcome Trust Case Control Consortium (seven diseases), and from much larger studies of celiac disease and inflammatory bowel disease, finding that it consistently provides better prediction than alternative methods. Moreover, MultiBLUP is computationally very efficient; for the largest data set, which includes 12,678 individuals and 1.5 M SNPs, the total analysis can be run on a single desktop PC in less than a day and can be parallelized to run even faster. Tools to perform MultiBLUP are freely available in our software LDAK. © 2014 Speed and Balding; Published by Cold Spring Harbor Laboratory Press.
Kitchens, John W; Kassem, Nawal; Wood, William; Stone, Thomas W; Isernhagen, Rick; Wood, Edward; Hancock, Brad A; Radovich, Milan; Waymire, Josh; Li, Lang; Schneider, Bryan P
2013-01-01
Purpose To ascertain whether single nucleotide polymorphisms (SNPs) in the Vascular Endothelial Growth factor (VEGFA), Complement Factor H (CFH), and LOC387715 genes could predict outcome to anti-VEGF therapy for patients with age related macular degeneration (AMD). Methods Patients with “wet” AMD were identified by chart review. Baseline optical coherence tomography (OCT) and visual acuity (VA) data, and at least 6 months of clinical follow up after 3 initial monthly injections of bevacizumab or ranibizumab were required for inclusion. Based on OCT and VA, patients were categorized into two possible clinical outcomes: (a) responders and (b) non-responders. DNA was extracted from saliva and genotyped for candidate SNPs in the VEGFA, LOC387715, and CFH genes. Clinical outcomes were statistically compared to patient genotypes. Results 101 patients were recruited, and one eye from each patient was included in the analysis. 97% of samples were successfully genotyped for all SNPs. We found a statistically significant association between the LOC387715 A69S TT genotype and outcome based on OCT. Conclusion Genetic variation may be associated with outcome in patients receiving anti-VEGF therapy. PMID:24143065
HRM and SNaPshot as alternative forensic SNP genotyping methods.
Mehta, Bhavik; Daniel, Runa; McNevin, Dennis
2017-09-01
Single nucleotide polymorphisms (SNPs) have been widely used in forensics for prediction of identity, biogeographical ancestry (BGA) and externally visible characteristics (EVCs). Single base extension (SBE) assays, most notably SNaPshot® (Thermo Fisher Scientific), are commonly used for forensic SNP genotyping as they can be employed on standard instrumentation in forensic laboratories (e.g. capillary electrophoresis). High resolution melt (HRM) analysis is an alternative method and is a simple, fast, single tube assay for low throughput SNP typing. This study compares HRM and SNaPshot®. HRM produced reproducible and concordant genotypes at 500 pg, however, difficulties were encountered when genotyping SNPs with high GC content in flanking regions and differentiating variants of symmetrical SNPs. SNaPshot® was reproducible at 100 pg and is less dependent on SNP choice. HRM has a shorter processing time in comparison to SNaPshot®, avoids post PCR contamination risk and has potential as a screening tool for many forensic applications.
Single nucleotide polymorphisms and haplotypes associated with feed efficiency in beef cattle
2013-01-01
Background General, breed- and diet-dependent associations between feed efficiency in beef cattle and single nucleotide polymorphisms (SNPs) or haplotypes were identified on a population of 1321 steers using a 50 K SNP panel. Genomic associations with traditional two-step indicators of feed efficiency – residual feed intake (RFI), residual average daily gain (RADG), and residual intake gain (RIG) – were compared to associations with two complementary one-step indicators of feed efficiency: efficiency of intake (EI) and efficiency of gain (EG). Associations uncovered in a training data set were evaluated on independent validation data set. A multi-SNP model was developed to predict feed efficiency. Functional analysis of genes harboring SNPs significantly associated with feed efficiency and network visualization aided in the interpretation of the results. Results For the five feed efficiency indicators, the numbers of general, breed-dependent, and diet-dependent associations with SNPs (P-value < 0.0001) were 31, 40, and 25, and with haplotypes were six, ten, and nine, respectively. Of these, 20 SNP and six haplotype associations overlapped between RFI and EI, and five SNP and one haplotype associations overlapped between RADG and EG. This result confirms the complementary value of the one and two-step indicators. The multi-SNP models included 89 SNPs and offered a precise prediction of the five feed efficiency indicators. The associations of 17 SNPs and 7 haplotypes with feed efficiency were confirmed on the validation data set. Nine clusters of Gene Ontology and KEGG pathway categories (mean P-value < 0.001) including, 9nucleotide binding; ion transport, phosphorous metabolic process, and the MAPK signaling pathway were overrepresented among the genes harboring the SNPs associated with feed efficiency. Conclusions The general SNP associations suggest that a single panel of genomic variants can be used regardless of breed and diet. The breed- and diet-dependent associations between SNPs and feed efficiency suggest that further refinement of variant panels require the consideration of the breed and management practices. The unique genomic variants associated with the one- and two-step indicators suggest that both types of indicators offer complementary description of feed efficiency that can be exploited for genome-enabled selection purposes. PMID:24066663
Machiela, Mitchell J; Chanock, Stephen J
2015-11-01
Assessing linkage disequilibrium (LD) across ancestral populations is a powerful approach for investigating population-specific genetic structure as well as functionally mapping regions of disease susceptibility. Here, we present LDlink, a web-based collection of bioinformatic modules that query single nucleotide polymorphisms (SNPs) in population groups of interest to generate haplotype tables and interactive plots. Modules are designed with an emphasis on ease of use, query flexibility, and interactive visualization of results. Phase 3 haplotype data from the 1000 Genomes Project are referenced for calculating pairwise metrics of LD, searching for proxies in high LD, and enumerating all observed haplotypes. LDlink is tailored for investigators interested in mapping common and uncommon disease susceptibility loci by focusing on output linking correlated alleles and highlighting putative functional variants. LDlink is a free and publically available web tool which can be accessed at http://analysistools.nci.nih.gov/LDlink/. mitchell.machiela@nih.gov. Published by Oxford University Press 2015. This work is written by US Government employees and is in the public domain in the US.
Alzahrani, Eman
2017-01-01
The use of nanoparticles in sensing is attracting the interest of many researchers. The aim of this work was to fabricate Acacia gum–stabilised silver nanoparticles (SNPs) using green chemistry to use them as a highly sensitive and cost-effective localised surface plasmon resonance (LSPR) colorimeter sensor for the determination of reactive oxygen species, such as hydrogen peroxide (H2O2). Silver nanoparticles were fabricated by the reduction of an inorganic precursor silver nitrate solution (AgNO3) using white sugar as the reducing reagent and Acacia gum as the stabilising reagent and a sonication bath to form uniform silver nanoparticles. The fabricated nanoparticles were characterised by visual observation, ultraviolet-visible (UV-Vis) spectrophotometry, transmission electron microscopy (TEM) analysis, energy-dispersive X-ray spectroscopy (EDAX), thermogravimetric analysis (TGA), and Fourier transform infrared spectroscopy (FT-IR). The TEM micrographs of the synthesised nanoparticles showed the presence of spherical nanoparticles with sizes of approximately 10 nm. The EDAX spectrum result confirmed the presence of silver (58%), carbon (30%), and oxygen (12%). Plasmon colorimetric sensing of H2O2 solution was investigated by introducing H2O2 solution into Acacia gum–capped SNP dispersion, and the change in the LSPR band in the UV-Vis region of spectra was monitored. In this study, it was found that the yellow colour of Acacia gum–stabilised SNPs gradually changed to transparent, and moreover, a remarkable change in the LSPR absorbance strength was observed. The calibration curve was linear over 0.1–0.00001 M H2O2, with a correlation estimation (R2) of .953. This was due to the aggregation of SNPs following introduction of the H2O2 solution. Furthermore, the fabricated SNPs were successfully used to detect H2O2 solution in a liquid milk sample, thereby demonstrating the ability of the fabricated SNPs to detect H2O2 solution in liquid milk samples. This work showed that Acacia gum–stabilised SNPs may have the potential as a colour indicator in medical and environmental applications. PMID:28469405
An innovative SNP genotyping method adapting to multiple platforms and throughputs
USDA-ARS?s Scientific Manuscript database
Single nucleotide polymorphisms (SNPs) are highly abundant, distributed throughout the genome in various species, and therefore they are widely used as genetic markers. However, the usefulness of this genetic tool relies heavily on the availability of user-friendly SNP genotyping methods. We have d...
Jo, Jinkwan; Purushotham, Preethi M.; Han, Koeun; Lee, Heung-Ryul; Nah, Gyoungju; Kang, Byoung-Cheorl
2017-01-01
Single nucleotide polymorphisms (SNPs) play important roles as molecular markers in plant genomics and breeding studies. Although onion (Allium cepa L.) is an important crop globally, relatively few molecular marker resources have been reported due to its large genome and high heterozygosity. Genotyping-by-sequencing (GBS) offers a greater degree of complexity reduction followed by concurrent SNP discovery and genotyping for species with complex genomes. In this study, GBS was employed for SNP mining in onion, which currently lacks a reference genome. A segregating F2 population, derived from a cross between ‘NW-001’ and ‘NW-002,’ as well as multiple parental lines were used for GBS analysis. A total of 56.15 Gbp of raw sequence data were generated and 1,851,428 SNPs were identified from the de novo assembled contigs. Stringent filtering resulted in 10,091 high-fidelity SNP markers. Robust SNPs that satisfied the segregation ratio criteria and with even distribution in the mapping population were used to construct an onion genetic map. The final map contained eight linkage groups and spanned a genetic length of 1,383 centiMorgans (cM), with an average marker interval of 8.08 cM. These robust SNPs were further analyzed using the high-throughput Fluidigm platform for marker validation. This is the first study in onion to develop genome-wide SNPs using GBS. The resulting SNP markers and developed linkage map will be valuable tools for genetic mapping of important agronomic traits and marker-assisted selection in onion breeding programs. PMID:28959273
Feltus, F Alex; Wan, Jun; Schulze, Stefan R; Estill, James C; Jiang, Ning; Paterson, Andrew H
2004-09-01
Dense coverage of the rice genome with polymorphic DNA markers is an invaluable tool for DNA marker-assisted breeding, positional cloning, and a wide range of evolutionary studies. We have aligned drafts of two rice subspecies, indica and japonica, and analyzed levels and patterns of genetic diversity. After filtering multiple copy and low quality sequence, 408,898 candidate DNA polymorphisms (SNPs/INDELs) were discerned between the two subspecies. These filters have the consequence that our data set includes only a subset of the available SNPs (in particular excluding large numbers of SNPs that may occur between repetitive DNA alleles) but increase the likelihood that this subset is useful: Direct sequencing suggests that 79.8% +/- 7.5% of the in silico SNPs are real. The SNP sample in our database is not randomly distributed across the genome. In fact, 566 rice genomic regions had unusually high (328 contigs/48.6 Mb/13.6% of genome) or low (237 contigs/64.7 Mb/18.1% of genome) polymorphism rates. Many SNP-poor regions were substantially longer than most SNP-rich regions, covering up to 4 Mb, and possibly reflecting introgression between the respective gene pools that may have occurred hundreds of years ago. Although 46.2% +/- 8.3% of the SNPs differentiate other pairs of japonica and indica genotypes, SNP rates in rice were not predictive of evolutionary rates for corresponding genes in another grass species, sorghum. The data set is freely available at http://www.plantgenome.uga.edu/snp.
Feltus, F. Alex; Wan, Jun; Schulze, Stefan R.; Estill, James C.; Jiang, Ning; Paterson, Andrew H.
2004-01-01
Dense coverage of the rice genome with polymorphic DNA markers is an invaluable tool for DNA marker-assisted breeding, positional cloning, and a wide range of evolutionary studies. We have aligned drafts of two rice subspecies, indica and japonica, and analyzed levels and patterns of genetic diversity. After filtering multiple copy and low quality sequence, 408,898 candidate DNA polymorphisms (SNPs/INDELs) were discerned between the two subspecies. These filters have the consequence that our data set includes only a subset of the available SNPs (in particular excluding large numbers of SNPs that may occur between repetitive DNA alleles) but increase the likelihood that this subset is useful: Direct sequencing suggests that 79.8% ± 7.5% of the in silico SNPs are real. The SNP sample in our database is not randomly distributed across the genome. In fact, 566 rice genomic regions had unusually high (328 contigs/48.6 Mb/13.6% of genome) or low (237 contigs/64.7 Mb/18.1% of genome) polymorphism rates. Many SNP-poor regions were substantially longer than most SNP-rich regions, covering up to 4 Mb, and possibly reflecting introgression between the respective gene pools that may have occurred hundreds of years ago. Although 46.2% ± 8.3% of the SNPs differentiate other pairs of japonica and indica genotypes, SNP rates in rice were not predictive of evolutionary rates for corresponding genes in another grass species, sorghum. The data set is freely available at http://www.plantgenome.uga.edu/snp. PMID:15342564
SNPs selection using support vector regression and genetic algorithms in GWAS
2014-01-01
Introduction This paper proposes a new methodology to simultaneously select the most relevant SNPs markers for the characterization of any measurable phenotype described by a continuous variable using Support Vector Regression with Pearson Universal kernel as fitness function of a binary genetic algorithm. The proposed methodology is multi-attribute towards considering several markers simultaneously to explain the phenotype and is based jointly on statistical tools, machine learning and computational intelligence. Results The suggested method has shown potential in the simulated database 1, with additive effects only, and real database. In this simulated database, with a total of 1,000 markers, and 7 with major effect on the phenotype and the other 993 SNPs representing the noise, the method identified 21 markers. Of this total, 5 are relevant SNPs between the 7 but 16 are false positives. In real database, initially with 50,752 SNPs, we have reduced to 3,073 markers, increasing the accuracy of the model. In the simulated database 2, with additive effects and interactions (epistasis), the proposed method matched to the methodology most commonly used in GWAS. Conclusions The method suggested in this paper demonstrates the effectiveness in explaining the real phenotype (PTA for milk), because with the application of the wrapper based on genetic algorithm and Support Vector Regression with Pearson Universal, many redundant markers were eliminated, increasing the prediction and accuracy of the model on the real database without quality control filters. The PUK demonstrated that it can replicate the performance of linear and RBF kernels. PMID:25573332
Nair, Sethu C; Pattaradilokrat, Sittiporn; Zilversmit, Martine M; Dommer, Jennifer; Nagarajan, Vijayaraj; Stephens, Melissa T; Xiao, Wenming; Tan, John C; Su, Xin-Zhuan
2014-01-01
The rodent malaria parasite Plasmodium yoelii is an important model for studying malaria immunity and pathogenesis. One approach for studying malaria disease phenotypes is genetic mapping, which requires typing a large number of genetic markers from multiple parasite strains and/or progeny from genetic crosses. Hundreds of microsatellite (MS) markers have been developed to genotype the P. yoelii genome; however, typing a large number of MS markers can be labor intensive, time consuming, and expensive. Thus, development of high-throughput genotyping tools such as DNA microarrays that enable rapid and accurate large-scale genotyping of the malaria parasite will be highly desirable. In this study, we sequenced the genomes of two P. yoelii strains (33X and N67) and obtained a large number of single nucleotide polymorphisms (SNPs). Based on the SNPs obtained, we designed sets of oligonucleotide probes to develop a microarray that could interrogate ∼11,000 SNPs across the 14 chromosomes of the parasite in a single hybridization. Results from hybridizations of DNA samples of five P. yoelii strains or cloned lines (17XNL, YM, 33X, N67 and N67C) and two progeny from a genetic cross (N67×17XNL) to the microarray showed that the array had a high call rate (∼97%) and accuracy (99.9%) in calling SNPs, providing a simple and reliable tool for typing the P. yoelii genome. Our data show that the P. yoelii genome is highly polymorphic, although isogenic pairs of parasites were also detected. Additionally, our results indicate that the 33X parasite is a progeny of 17XNL (or YM) and an unknown parasite. The highly accurate and reliable microarray developed in this study will greatly facilitate our ability to study the genetic basis of important traits and the disease it causes. Published by Elsevier B.V.
Analysis and visualization of chromosomal abnormalities in SNP data with SNPscan
Ting, Jason C; Ye, Ying; Thomas, George H; Ruczinski, Ingo; Pevsner, Jonathan
2006-01-01
Background A variety of diseases are caused by chromosomal abnormalities such as aneuploidies (having an abnormal number of chromosomes), microdeletions, microduplications, and uniparental disomy. High density single nucleotide polymorphism (SNP) microarrays provide information on chromosomal copy number changes, as well as genotype (heterozygosity and homozygosity). SNP array studies generate multiple types of data for each SNP site, some with more than 100,000 SNPs represented on each array. The identification of different classes of anomalies within SNP data has been challenging. Results We have developed SNPscan, a web-accessible tool to analyze and visualize high density SNP data. It enables researchers (1) to visually and quantitatively assess the quality of user-generated SNP data relative to a benchmark data set derived from a control population, (2) to display SNP intensity and allelic call data in order to detect chromosomal copy number anomalies (duplications and deletions), (3) to display uniparental isodisomy based on loss of heterozygosity (LOH) across genomic regions, (4) to compare paired samples (e.g. tumor and normal), and (5) to generate a file type for viewing SNP data in the University of California, Santa Cruz (UCSC) Human Genome Browser. SNPscan accepts data exported from Affymetrix Copy Number Analysis Tool as its input. We validated SNPscan using data generated from patients with known deletions, duplications, and uniparental disomy. We also inspected previously generated SNP data from 90 apparently normal individuals from the Centre d'Étude du Polymorphisme Humain (CEPH) collection, and identified three cases of uniparental isodisomy, four females having an apparently mosaic X chromosome, two mislabelled SNP data sets, and one microdeletion on chromosome 2 with mosaicism from an apparently normal female. These previously unrecognized abnormalities were all detected using SNPscan. The microdeletion was independently confirmed by fluorescence in situ hybridization, and a region of homozygosity in a UPD case was confirmed by sequencing of genomic DNA. Conclusion SNPscan is useful to identify chromosomal abnormalities based on SNP intensity (such as chromosomal copy number changes) and heterozygosity data (including regions of LOH and some cases of UPD). The program and source code are available at the SNPscan website . PMID:16420694
Genotyping analysis and ¹⁸FDG uptake in breast cancer patients: a preliminary research.
Bravatà, Valentina; Stefano, Alessandro; Cammarata, Francesco P; Minafra, Luigi; Russo, Giorgio; Nicolosi, Stefania; Pulizzi, Sabina; Gelfi, Cecilia; Gilardi, Maria C; Messa, Cristina
2013-04-30
Diagnostic imaging plays a relevant role in the care of patients with breast cancer (BC). Positron Emission Tomography (PET) with 18F-fluoro-2-deoxy-D-glucose (FDG) has been widely proven to be a clinical tool suitable for BC detection and staging in which the glucose analog supplies metabolic information about the tumor. A limited number of studies, sometimes controversial, describe possible associations between FDG uptake and single nucleotide polymorphisms (SNPs). For this reason this field has to be explored and clarified. We investigated the association of SNPs in GLUT1, HIF-1a, EPAS1, APEX1, VEGFA and MTHFR genes with the FDG uptake in BC. In 26 caucasian individuals with primary BC, whole-body PET-CT scans were obtained and quantitative analysis was performed by calculating the maximum Standardized Uptake Value normalized to body-weight (SUVmax) and the mean SUV normalized to body-weight corrected for partial volume effect (SUVpvc). Human Gene Mutation Database and dbSNP Short Genetic Variations database were used to analyze gene regions containing the selected SNPs. Patient genotypes were obtained using Sanger DNA sequencing analysis performed by Capillary Electrophoresis. BC patients were genotyped for the following nine SNPs: GLUT1: rs841853 and rs710218; HIF-1a: rs11549465 and rs11549467; EPAS1: rs137853037 and rs137853036; APEX1: rs1130409; VEGFA: rs3025039 and MTHFR: rs1801133. In this work correlations between the nine potentially useful polymorphisms selected and previously suggested with tracer uptake (using both SUVmax and SUVpvc) were not found. The possible functional influence of specific SNPs on FDG uptake needs further studies in human cancer. In summary, this is the first pilot study, to our knowledge, which investigates the association between a large panel of SNPs and FDG uptake specifically in BC patients. This work represents a multidisciplinary and translational medicine approach to study BC where, the possible correlation between SNPs and tracer uptake, may be considered to improve personalized cancer treatment and care.
Wong, Xin Yi; Chong, Kok Joon; van Til, Janine A; Wee, Hwee Lin
2017-11-21
Breast cancer is the top cancer by incidence and mortality in Singaporean women. Mammography is by far its best screening tool, but current recommended age and interval may not yield the most benefit. Recent studies have demonstrated the potential of single nucleotide polymorphisms (SNPs) to improve discriminatory accuracy of breast cancer risk assessment models. This study was conducted to understand Singaporean women's views towards breast cancer screening and SNPs gene testing to guide personalised screening strategies. Focus group discussions were conducted among English-speaking women (n = 27) between 40 to 65 years old, both current and lapsed mammogram users. Women were divided into four groups based on age and mammogram usage. Discussions about breast cancer and screening experience, as well as perception and attitude towards SNPs gene testing were conducted by an experienced moderator. Women were also asked for factors that will influence their uptake of the test. Transcripts were analysed using thematic analysis to captured similarities and differences in views expressed. Barriers to repeat mammogram attendance include laziness to make appointment and painful and uncomfortable screening process. However, the underlying reason may be low perceived susceptibility to breast cancer. Facilitators to repeat mammogram attendance include ease of making appointment and timely reminders. Women were generally receptive towards SNPs gene testing, but required information on accuracy, cost, invasiveness, and side effects before they decide whether to go for it. Other factors include waiting time for results and frequency interval. On average, women gave a rating of 7.5 (range 5 to 10) when asked how likely they will go for the test. Addressing concerns such as pain and discomfort during mammogram, providing timely reminders and debunking breast cancer myths can help to improve screening uptake. Women demonstrated a spectrum of responses towards a novel test like SNPs gene testing, but need more information to make an informed decision. Future public health education on predictive genetic testing should adequately address both benefits and risks. Findings from this study is used to inform a discrete choice experiment to empirically quantify women preferences and willingness-to-pay for SNPs gene testing.
SNP-markers in Allium species to facilitate introgression breeding in onion.
Scholten, Olga E; van Kaauwen, Martijn P W; Shahin, Arwa; Hendrickx, Patrick M; Keizer, L C Paul; Burger, Karin; van Heusden, Adriaan W; van der Linden, C Gerard; Vosman, Ben
2016-08-31
Within onion, Allium cepa L., the availability of disease resistance is limited. The identification of sources of resistance in related species, such as Allium roylei and Allium fistulosum, was a first step towards the improvement of onion cultivars by breeding. SNP markers linked to resistance and polymorphic between these related species and onion cultivars are a valuable tool to efficiently introgress disease resistance genes. In this paper we describe the identification and validation of SNP markers valuable for onion breeding. Transcriptome sequencing resulted in 192 million RNA seq reads from the interspecific F1 hybrid between A. roylei and A. fistulosum (RF) and nine onion cultivars. After assembly, reliable SNPs were discovered in about 36 % of the contigs. For genotyping of the interspecific three-way cross population, derived from a cross between an onion cultivar and the RF (CCxRF), 1100 SNPs that are polymorphic in RF and monomorphic in the onion cultivars (RF SNPs) were selected for the development of KASP assays. A molecular linkage map based on 667 RF-SNP markers was constructed for CCxRF. In addition, KASP assays were developed for 1600 onion-SNPs (SNPs polymorphic among onion cultivars). A second linkage map was constructed for an F2 of onion x A. roylei (F2(CxR)) that consisted of 182 onion-SNPs and 119 RF-SNPs, and 76 previously mapped markers. Markers co-segregating in both the F2(CxR) and the CCxRF population were used to assign the linkage groups of RF to onion chromosomes. To validate usefulness of these SNP markers, QTL mapping was applied in the CCxRF population that segregates for resistance to Botrytis squamosa and resulted in a QTL for resistance on chromosome 6 of A. roylei. Our research has more than doubled the publicly available marker sequences of expressed onion genes and two onion-related species. It resulted in a detailed genetic map for the interspecific CCxRF population. This is the first paper that reports the detection of a QTL for resistance to B. squamosa in A. roylei.
Zhang, Suhua; Bian, Yingnan; Chen, Anqi; Zheng, Hancheng; Gao, Yuzhen; Hou, Yiping; Li, Chengtao
2017-03-01
Utilizing massively parallel sequencing (MPS) technology for SNP testing in forensic genetics is becoming attractive because of the shortcomings of STR markers, such as their high mutation rates and disadvantages associated with the current PCR-CE method as well as its limitations regarding multiplex capabilities. MPS offers the potential to genotype hundreds to thousands of SNPs from multiple samples in a single experimental run. In this study, we designed a customized SNP panel that includes 273 forensically relevant identity SNPs chosen from SNPforID, IISNP, and the HapMap database as well as previously related studies and evaluated the levels of genotyping precision, sequence coverage, sensitivity and SNP performance using the Ion Torrent PGM. In a concordant study of the custom MPS-SNP panel, only four MPS callings were missing due to coverage reads that were too low (<20), whereas the others were fully concordant with Sanger's sequencing results across the two control samples, that is, 9947A and 9948. The analyses indicated a balanced coverage among the included loci, with the exception of the 16 SNPs that were used to detect an inconsistent allele balance and/or lower coverage reads among 50 tested individuals from the Chinese HAN population and the above controls. With the exception of the 16 poorly performing SNPs, the sequence coverage obtained was extensive for the bulk of the SNPs, and only three Y-SNPs (rs16980601, rs11096432, rs3900) showed a mean coverage below 1000. Analyses of the dilution series of control DNA 9948 yielded reproducible results down to 1ng of DNA input. In addition, we provide an analysis tool for automated data quality control and genotyping checks, and we conclude that the SNP targets are polymorphic and independent in the Chinese HAN population. In summary, the evaluation of the sensitivity, accuracy and genotyping performance provides strong support for the application of MPS technology in forensic SNP analysis, and the assay offers a straightforward sample-to-genotype workflow that could be beneficial in forensic casework with respect to both individual identification and complex kinship issues. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.
Linkage maps of the Atlantic salmon (Salmo salar) genome derived from RAD sequencing
2014-01-01
Background Genetic linkage maps are useful tools for mapping quantitative trait loci (QTL) influencing variation in traits of interest in a population. Genotyping-by-sequencing approaches such as Restriction-site Associated DNA sequencing (RAD-Seq) now enable the rapid discovery and genotyping of genome-wide SNP markers suitable for the development of dense SNP linkage maps, including in non-model organisms such as Atlantic salmon (Salmo salar). This paper describes the development and characterisation of a high density SNP linkage map based on SbfI RAD-Seq SNP markers from two Atlantic salmon reference families. Results Approximately 6,000 SNPs were assigned to 29 linkage groups, utilising markers from known genomic locations as anchors. Linkage maps were then constructed for the four mapping parents separately. Overall map lengths were comparable between male and female parents, but the distribution of the SNPs showed sex-specific patterns with a greater degree of clustering of sire-segregating SNPs to single chromosome regions. The maps were integrated with the Atlantic salmon draft reference genome contigs, allowing the unique assignment of ~4,000 contigs to a linkage group. 112 genome contigs mapped to two or more linkage groups, highlighting regions of putative homeology within the salmon genome. A comparative genomics analysis with the stickleback reference genome identified putative genes closely linked to approximately half of the ordered SNPs and demonstrated blocks of orthology between the Atlantic salmon and stickleback genomes. A subset of 47 RAD-Seq SNPs were successfully validated using a high-throughput genotyping assay, with a correspondence of 97% between the two assays. Conclusions This Atlantic salmon RAD-Seq linkage map is a resource for salmonid genomics research as genotyping-by-sequencing becomes increasingly common. This is aided by the integration of the SbfI RAD-Seq SNPs with existing reference maps and the draft reference genome, as well as the identification of putative genes proximal to the SNPs. Differences in the distribution of recombination events between the sexes is evident, and regions of homeology have been identified which are reflective of the recent salmonid whole genome duplication. PMID:24571138
The Role of Motor Learning in Spatial Adaptation near a Tool
Brown, Liana E.; Doole, Robert; Malfait, Nicole
2011-01-01
Some visual-tactile (bimodal) cells have visual receptive fields (vRFs) that overlap and extend moderately beyond the skin of the hand. Neurophysiological evidence suggests, however, that a vRF will grow to encompass a hand-held tool following active tool use but not after passive holding. Why does active tool use, and not passive holding, lead to spatial adaptation near a tool? We asked whether spatial adaptation could be the result of motor or visual experience with the tool, and we distinguished between these alternatives by isolating motor from visual experience with the tool. Participants learned to use a novel, weighted tool. The active training group received both motor and visual experience with the tool, the passive training group received visual experience with the tool, but no motor experience, and finally, a no-training control group received neither visual nor motor experience using the tool. After training, we used a cueing paradigm to measure how quickly participants detected targets, varying whether the tool was placed near or far from the target display. Only the active training group detected targets more quickly when the tool was placed near, rather than far, from the target display. This effect of tool location was not present for either the passive-training or control groups. These results suggest that motor learning influences how visual space around the tool is represented. PMID:22174944
Genome-Wide SNP Detection, Validation, and Development of an 8K SNP Array for Apple
Chagné, David; Crowhurst, Ross N.; Troggio, Michela; Davey, Mark W.; Gilmore, Barbara; Lawley, Cindy; Vanderzande, Stijn; Hellens, Roger P.; Kumar, Satish; Cestaro, Alessandro; Velasco, Riccardo; Main, Dorrie; Rees, Jasper D.; Iezzoni, Amy; Mockler, Todd; Wilhelm, Larry; Van de Weg, Eric; Gardiner, Susan E.; Bassil, Nahla; Peace, Cameron
2012-01-01
As high-throughput genetic marker screening systems are essential for a range of genetics studies and plant breeding applications, the International RosBREED SNP Consortium (IRSC) has utilized the Illumina Infinium® II system to develop a medium- to high-throughput SNP screening tool for genome-wide evaluation of allelic variation in apple (Malus×domestica) breeding germplasm. For genome-wide SNP discovery, 27 apple cultivars were chosen to represent worldwide breeding germplasm and re-sequenced at low coverage with the Illumina Genome Analyzer II. Following alignment of these sequences to the whole genome sequence of ‘Golden Delicious’, SNPs were identified using SoapSNP. A total of 2,113,120 SNPs were detected, corresponding to one SNP to every 288 bp of the genome. The Illumina GoldenGate® assay was then used to validate a subset of 144 SNPs with a range of characteristics, using a set of 160 apple accessions. This validation assay enabled fine-tuning of the final subset of SNPs for the Illumina Infinium® II system. The set of stringent filtering criteria developed allowed choice of a set of SNPs that not only exhibited an even distribution across the apple genome and a range of minor allele frequencies to ensure utility across germplasm, but also were located in putative exonic regions to maximize genotyping success rate. A total of 7867 apple SNPs was established for the IRSC apple 8K SNP array v1, of which 5554 were polymorphic after evaluation in segregating families and a germplasm collection. This publicly available genomics resource will provide an unprecedented resolution of SNP haplotypes, which will enable marker-locus-trait association discovery, description of the genetic architecture of quantitative traits, investigation of genetic variation (neutral and functional), and genomic selection in apple. PMID:22363718
Gutierrez, Alejandro P; Turner, Frances; Gharbi, Karim; Talbot, Richard; Lowe, Natalie R; Peñaloza, Carolina; McCullough, Mark; Prodöhl, Paulo A; Bean, Tim P; Houston, Ross D
2017-07-05
SNP arrays are enabling tools for high-resolution studies of the genetic basis of complex traits in farmed and wild animals. Oysters are of critical importance in many regions from both an ecological and economic perspective, and oyster aquaculture forms a key component of global food security. The aim of our study was to design a combined-species, medium density SNP array for Pacific oyster ( Crassostrea gigas ) and European flat oyster ( Ostrea edulis ), and to test the performance of this array on farmed and wild populations from multiple locations, with a focus on European populations. SNP discovery was carried out by whole-genome sequencing (WGS) of pooled genomic DNA samples from eight C. gigas populations, and restriction site-associated DNA sequencing (RAD-Seq) of 11 geographically diverse O. edulis populations. Nearly 12 million candidate SNPs were discovered and filtered based on several criteria, including preference for SNPs segregating in multiple populations and SNPs with monomorphic flanking regions. An Affymetrix Axiom Custom Array was created and tested on a diverse set of samples ( n = 219) showing ∼27 K high quality SNPs for C. gigas and ∼11 K high quality SNPs for O. edulis segregating in these populations. A high proportion of SNPs were segregating in each of the populations, and the array was used to detect population structure and levels of linkage disequilibrium (LD). Further testing of the array on three C. gigas nuclear families ( n = 165) revealed that the array can be used to clearly distinguish between both families based on identity-by-state (IBS) clustering parental assignment software. This medium density, combined-species array will be publicly available through Affymetrix, and will be applied for genome-wide association and evolutionary genetic studies, and for genomic selection in oyster breeding programs. Copyright © 2017 Gutierrez et al.
Martínez, R; Gómez, Y; Rocha, J F M
2014-08-25
Whole genome selection represents an important tool for improving parameters related to the production of livestock. In order to build genomic selection indexes within a particular breed, it is important to identify polymorphisms that have the most significant association with a desired trait. A genome-wide marker association approach based on the Illumina BovineSNP50 BeadChip(TM) was used to identify genomic regions affecting birth weight (BW), weaning weight (WW), and daily weight gain (DWG) in purebred and crossbred creole cattle populations. We genotyped 654 individuals of Blanco Orejinegro (BON), Romosinuano (ROMO) and Cebú breeds and the crossbreeds BON x Cebú and ROMO x Cebú, and tested 5 genetic control models. In total, 85 single nucleotide polymorphisms (SNPs) were related (P < 0.05) to the 3 evaluated traits; BW was associated with the highest number of SNPs. For statistical false-positive correction, Bonferroni correction was used. From the results, we identified 7, 6, and 4 SNPs with strong associations with BW, WW, and DWG, respectively. Many of these SNPs were located on important coding regions of the bovine genome; their ontology and interactions are discussed herein. The results could contribute to the identification of genes involved in the physiology of beef cattle growth and the development of new strategies for breeding management via genomic selection to improve the productivity of creole cattle herds.
Knüppel, Sven; Meidtner, Karina; Arregui, Maria; Holzhütter, Hermann-Georg; Boeing, Heiner
2015-07-01
Analyzing multiple single nucleotide polymorphisms (SNPs) is a promising approach to finding genetic effects beyond single-locus associations. We proposed the use of multilocus stepwise regression (MSR) to screen for allele combinations as a method to model joint effects, and compared the results with the often used genetic risk score (GRS), conventional stepwise selection, and the shrinkage method LASSO. In contrast to MSR, the GRS, conventional stepwise selection, and LASSO model each genotype by the risk allele doses. We reanalyzed 20 unlinked SNPs related to type 2 diabetes (T2D) in the EPIC-Potsdam case-cohort study (760 cases, 2193 noncases). No SNP-SNP interactions and no nonlinear effects were found. Two SNP combinations selected by MSR (Nagelkerke's R² = 0.050 and 0.048) included eight SNPs with mean allele combination frequency of 2%. GRS and stepwise selection selected nearly the same SNP combinations consisting of 12 and 13 SNPs (Nagelkerke's R² ranged from 0.020 to 0.029). LASSO showed similar results. The MSR method showed the best model fit measured by Nagelkerke's R² suggesting that further improvement may render this method a useful tool in genetic research. However, our comparison suggests that the GRS is a simple way to model genetic effects since it does not consider linkage, SNP-SNP interactions, and no non-linear effects. © 2015 John Wiley & Sons Ltd/University College London.
Stepanov, Vadim; Vagaitseva, Ksenyia; Kharkov, Vladimir; Cherednichenko, Anastasia; Bocharova, Anna; Berezina, Galina; Svyatova, Gulnara
2016-01-01
X chromosome genetic markers are widely used in basic population genetic research as well as in forensic genetics. In this paper we analyze the genetic diversity of 62 X chromosome SNPs in 4 populations using multiplex genotyping based on multi-locus PCR and MALDI-TOF mass spectrometry, and report forensic and population genetic features of the panel of X-linked SNPs (XSNPid). Studied populations represent Siberian (Buryat and Khakas), North Asian (Khanty) and Central Asian (Kazakh) native people. Khanty, Khakas and Kazakh population demonstrate average gene diversity over 0.45. Only East Siberian Buryat population is characterized by lower average heterozygosity (0.436). AMOVA analysis of genetic structure reveals a relatively low but significant level of genetic differentiation in a group of 4 population studied (FST=0.023, p=0.0000). The XSNPid panel provides a very high discriminating power in each population. The combined probability of discrimination in females (PDf) for XSNPid panel ranged between populations from 0.99999999999999999999999982 in Khakas to 0.9999999999999999999999963 in Buryats. The combined discriminating power in males (PDm) varies from 0.999999999999999792 to 0.9999999999999999819. The developed multiplex set of X chromosome SNPs can be a useful tool for population genetic studies and for forensic identity and kinship testing. Copyright © 2015 Elsevier Ireland Ltd. All rights reserved.
Kumar, Ambuj; Rajendran, Vidya; Sethumadhavan, Rao; Purohit, Rituraj
2012-01-01
Human STIL (SCL/TAL1 interrupting locus) protein maintains centriole stability and spindle pole localisation. It helps in recruitment of CENPJ (Centromere protein J)/CPAP (centrosomal P4.1-associated protein) and other centrosomal proteins. Mutations in STIL protein are reported in several disorders, especially in deregulation of cell cycle cascades. In this work, we examined the non-synonymous single nucleotide polymorphisms (nsSNPs) reported in STIL protein for their disease association. Different SNP prediction tools were used to predict disease-associated nsSNPs. Our evaluation technique predicted rs147744459 (R242C) as a highly deleterious disease-associated nsSNP and its interaction behaviour with CENPJ protein. Molecular modelling, docking and molecular dynamics simulation were conducted to examine the structural consequences of the predicted disease-associated mutation. By molecular dynamic simulation we observed structural consequences of R242C mutation which affects interaction of STIL and CENPJ functional domains. The result obtained in this study will provide a biophysical insight into future investigations of pathological nsSNPs using a computational platform.
Making a chocolate chip: development and evaluation of a 6K SNP array for Theobroma cacao
Livingstone, Donald; Royaert, Stefan; Stack, Conrad; Mockaitis, Keithanne; May, Greg; Farmer, Andrew; Saski, Christopher; Schnell, Ray; Kuhn, David; Motamayor, Juan Carlos
2015-01-01
Theobroma cacao, the key ingredient in chocolate production, is one of the world's most important tree fruit crops, with ∼4,000,000 metric tons produced across 50 countries. To move towards gene discovery and marker-assisted breeding in cacao, a single-nucleotide polymorphism (SNP) identification project was undertaken using RNAseq data from 16 diverse cacao cultivars. RNA sequences were aligned to the assembled transcriptome of the cultivar Matina 1-6, and 330,000 SNPs within coding regions were identified. From these SNPs, a subset of 6,000 high-quality SNPs were selected for inclusion on an Illumina Infinium SNP array: the Cacao6kSNP array. Using Cacao6KSNP array data from over 1,000 cacao samples, we demonstrate that our custom array produces a saturated genetic map and can be used to distinguish among even closely related genotypes. Our study enhances and expands the genetic resources available to the cacao research community, and provides the genome-scale set of tools that are critical for advancing breeding with molecular markers in an agricultural species with high genetic diversity. PMID:26070980
Henriques, Dora; Browne, Keith A; Barnett, Mark W; Parejo, Melanie; Kryger, Per; Freeman, Tom C; Muñoz, Irene; Garnery, Lionel; Highet, Fiona; Jonhston, J Spencer; McCormack, Grace P; Pinto, M Alice
2018-06-04
The natural distribution of the honeybee (Apis mellifera L.) has been changed by humans in recent decades to such an extent that the formerly widest-spread European subspecies, Apis mellifera mellifera, is threatened by extinction through introgression from highly divergent commercial strains in large tracts of its range. Conservation efforts for A. m. mellifera are underway in multiple European countries requiring reliable and cost-efficient molecular tools to identify purebred colonies. Here, we developed four ancestry-informative SNP assays for high sample throughput genotyping using the iPLEX Mass Array system. Our customized assays were tested on DNA from individual and pooled, haploid and diploid honeybee samples extracted from different tissues using a diverse range of protocols. The assays had a high genotyping success rate and yielded accurate genotypes. Performance assessed against whole-genome data showed that individual assays behaved well, although the most accurate introgression estimates were obtained for the four assays combined (117 SNPs). The best compromise between accuracy and genotyping costs was achieved when combining two assays (62 SNPs). We provide a ready-to-use cost-effective tool for accurate molecular identification and estimation of introgression levels to more effectively monitor and manage A. m. mellifera conservatories.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Song, Qijian; Jia, Gaofeng; Hyten, David L.
A total of 992,682 single-nucleotide polymorphisms (SNPs) was identified as ideal for Illumina Infinium II BeadChip design after sequencing a diverse set of 17 common bean (Phaseolus vulgaris L) varieties with the aid of next-generation sequencing technology. From these, two BeadChips each with >5000 SNPs were designed. The BARCBean6K_1 BeadChip was selected for the purpose of optimizing polymorphism among market classes and, when possible, SNPs were targeted to sequence scaffolds in the Phaseolus vulgaris 14× genome assembly with sequence lengths >10 kb. The BARCBean6K_2 BeadChip was designed with the objective of anchoring additional scaffolds and to facilitate orientation of largemore » scaffolds. Analysis of 267 F2 plants from a cross of varieties Stampede × Red Hawk with the two BeadChips resulted in linkage maps with a total of 7040 markers including 7015 SNPs. With the linkage map, a total of 432.3 Mb of sequence from 2766 scaffolds was anchored to create the Phaseolus vulgaris v1.0 assembly, which accounted for approximately 89% of the 487 Mb of available sequence scaffolds of the Phaseolus vulgaris v0.9 assembly. A core set of 6000 SNPs (BARCBean6K_3 BeadChip) with high genotyping quality and polymorphism was selected based on the genotyping of 365 dry bean and 134 snap bean accessions with the BARCBean6K_1 and BARCBean6K_2 BeadChips. The BARCBean6K_3 BeadChip is a useful tool for genetics and genomics research and it is widely used by breeders and geneticists in the United States and abroad.« less
Khan, Imran; Ansari, Irfan A; Singh, Pratichi; Dass J, Febin Prabhu
2017-09-01
The phosphatase and tensin homolog (PTEN) gene plays a crucial role in signal transduction by negatively regulating the PI3K signaling pathway. It is the most frequent mutated gene in many human-related cancers. Considering its critical role, a functional analysis of missense mutations of PTEN gene was undertaken in this study. Thirty five nonsynonymous single nucleotide polymorphisms (nsSNPs) within the coding region of the PTEN gene were selected for our in silico investigation, and five nsSNPs (G129E, C124R, D252G, H61D, and R130G) were found to be deleterious based on combinatorial predictions of different computational tools. Moreover, molecular dynamics (MD) simulation was performed to investigate the conformational variation between native and all the five mutant PTEN proteins having predicted deleterious nsSNPs. The results of MD simulation of all mutant models illustrated variation in structural attributes such as root-mean-square deviation, root-mean-square fluctuation, radius of gyration, and total energy; which depicts the structural stability of PTEN protein. Furthermore, mutant PTEN protein structures also showed a significant variation in the solvent accessible surface area and hydrogen bond frequencies from the native PTEN structure. In conclusion, results of this study have established the deleterious effect of the all the five predicted nsSNPs on the PTEN protein structure. Thus, results of the current study can pave a new platform to sort out nsSNPs that can be undertaken for the confirmation of their phenotype and their correlation with diseased status in case of control studies. © 2016 International Union of Biochemistry and Molecular Biology, Inc.
Song, Qijian; Jia, Gaofeng; Hyten, David L.; ...
2015-08-28
A total of 992,682 single-nucleotide polymorphisms (SNPs) was identified as ideal for Illumina Infinium II BeadChip design after sequencing a diverse set of 17 common bean (Phaseolus vulgaris L) varieties with the aid of next-generation sequencing technology. From these, two BeadChips each with >5000 SNPs were designed. The BARCBean6K_1 BeadChip was selected for the purpose of optimizing polymorphism among market classes and, when possible, SNPs were targeted to sequence scaffolds in the Phaseolus vulgaris 14× genome assembly with sequence lengths >10 kb. The BARCBean6K_2 BeadChip was designed with the objective of anchoring additional scaffolds and to facilitate orientation of largemore » scaffolds. Analysis of 267 F2 plants from a cross of varieties Stampede × Red Hawk with the two BeadChips resulted in linkage maps with a total of 7040 markers including 7015 SNPs. With the linkage map, a total of 432.3 Mb of sequence from 2766 scaffolds was anchored to create the Phaseolus vulgaris v1.0 assembly, which accounted for approximately 89% of the 487 Mb of available sequence scaffolds of the Phaseolus vulgaris v0.9 assembly. A core set of 6000 SNPs (BARCBean6K_3 BeadChip) with high genotyping quality and polymorphism was selected based on the genotyping of 365 dry bean and 134 snap bean accessions with the BARCBean6K_1 and BARCBean6K_2 BeadChips. The BARCBean6K_3 BeadChip is a useful tool for genetics and genomics research and it is widely used by breeders and geneticists in the United States and abroad.« less
Song, Qijian; Jia, Gaofeng; Hyten, David L; Jenkins, Jerry; Hwang, Eun-Young; Schroeder, Steven G; Osorno, Juan M; Schmutz, Jeremy; Jackson, Scott A; McClean, Phillip E; Cregan, Perry B
2015-08-28
A total of 992,682 single-nucleotide polymorphisms (SNPs) was identified as ideal for Illumina Infinium II BeadChip design after sequencing a diverse set of 17 common bean (Phaseolus vulgaris L) varieties with the aid of next-generation sequencing technology. From these, two BeadChips each with >5000 SNPs were designed. The BARCBean6K_1 BeadChip was selected for the purpose of optimizing polymorphism among market classes and, when possible, SNPs were targeted to sequence scaffolds in the Phaseolus vulgaris 14× genome assembly with sequence lengths >10 kb. The BARCBean6K_2 BeadChip was designed with the objective of anchoring additional scaffolds and to facilitate orientation of large scaffolds. Analysis of 267 F2 plants from a cross of varieties Stampede × Red Hawk with the two BeadChips resulted in linkage maps with a total of 7040 markers including 7015 SNPs. With the linkage map, a total of 432.3 Mb of sequence from 2766 scaffolds was anchored to create the Phaseolus vulgaris v1.0 assembly, which accounted for approximately 89% of the 487 Mb of available sequence scaffolds of the Phaseolus vulgaris v0.9 assembly. A core set of 6000 SNPs (BARCBean6K_3 BeadChip) with high genotyping quality and polymorphism was selected based on the genotyping of 365 dry bean and 134 snap bean accessions with the BARCBean6K_1 and BARCBean6K_2 BeadChips. The BARCBean6K_3 BeadChip is a useful tool for genetics and genomics research and it is widely used by breeders and geneticists in the United States and abroad. Copyright © 2015 Song et al.
Shortt, Katherine; Chaudhary, Suman; Grigoryev, Dmitry; Heruth, Daniel P.; Venkitachalam, Lakshmi; Zhang, Li Q.; Ye, Shui Q.
2014-01-01
Acute respiratory distress syndrome (ARDS) is a lung condition characterized by impaired gas exchange with systemic release of inflammatory mediators, causing pulmonary inflammation, vascular leak and hypoxemia. Existing biomarkers have limited effectiveness as diagnostic and therapeutic targets. To identify disease-associating variants in ARDS patients, whole-exome sequencing was performed on 96 ARDS patients, detecting 1,382,399 SNPs. By comparing these exome data to those of the 1000 Genomes Project, we identified a number of single nucleotide polymorphisms (SNP) which are potentially associated with ARDS. 50,190SNPs were found in all case subgroups and controls, of which89 SNPs were associated with susceptibility. We validated three SNPs (rs78142040, rs9605146 and rs3848719) in additional ARDS patients to substantiate their associations with susceptibility, severity and outcome of ARDS. rs78142040 (C>T) occurs within a histone mark (intron 6) of the Arylsulfatase D gene. rs9605146 (G>A) causes a deleterious coding change (proline to leucine) in the XK, Kell blood group complex subunit-related family, member 3 gene. rs3848719 (G>A) is a synonymous SNP in the Zinc-Finger/Leucine-Zipper Co-Transducer NIF1 gene. rs78142040, rs9605146, and rs3848719 are associated significantly with susceptibility to ARDS. rs3848719 is associated with APACHE II score quartile. rs78142040 is associated with 60-day mortality in the overall ARDS patient population. Exome-seq is a powerful tool to identify potential new biomarkers for ARDS. We selectively validated three SNPs which have not been previously associated with ARDS and represent potential new genetic biomarkers for ARDS. Additional validation in larger patient populations and further exploration of underlying molecular mechanisms are warranted. PMID:25372662
Liu, Jun-Jun; Sniezko, Richard; Murray, Michael; Wang, Ning; Chen, Hao; Zamany, Arezoo; Sturrock, Rona N.; Savin, Douglas; Kegley, Angelia
2016-01-01
Whitebark pine (WBP, Pinus albicaulis Engelm.) is an endangered conifer species due to heavy mortality from white pine blister rust (WPBR, caused by Cronartium ribicola) and mountain pine beetle (Dendroctonus ponderosae). Information about genetic diversity and population structure is of fundamental importance for its conservation and restoration. However, current knowledge on the genetic constitution and genomic variation is still limited for WBP. In this study, an integrated genomics approach was applied to characterize seed collections from WBP breeding programs in western North America. RNA-seq analysis was used for de novo assembly of the WBP needle transcriptome, which contains 97,447 protein-coding transcripts. Within the transcriptome, single nucleotide polymorphisms (SNPs) were discovered, and more than 22,000 of them were non-synonymous SNPs (ns-SNPs). Following the annotation of genes with ns-SNPs, 216 ns-SNPs within candidate genes with putative functions in disease resistance and plant defense were selected to design SNP arrays for high-throughput genotyping. Among these SNP loci, 71 were highly polymorphic, with sufficient variation to identify a unique genotype for each of the 371 individuals originating from British Columbia (Canada), Oregon and Washington (USA). A clear genetic differentiation was evident among seed families. Analyses of genetic spatial patterns revealed varying degrees of diversity and the existence of several genetic subgroups in the WBP breeding populations. Genetic components were associated with geographic variables and phenotypic rating of WPBR disease severity across landscapes, which may facilitate further identification of WBP genotypes and gene alleles contributing to local adaptation and quantitative resistance to WPBR. The WBP genomic resources developed here provide an invaluable tool for further studies and for exploitation and utilization of the genetic diversity preserved within this endangered conifer and other five-needle pines. PMID:27992468
Liu, Jing; Wang, Zheng; He, Guanglin; Zhao, Xueying; Wang, Mengge; Luo, Tao; Li, Chengtao; Hou, Yiping
2018-07-01
Massively parallel sequencing (MPS) technologies can sequence many targeted regions of multiple samples simultaneously and are gaining great interest in the forensic community. The Precision ID Identity Panel contains 90 autosomal SNPs and 34 upper Y-Clade SNPs, which was designed with small amplicons and optimized for forensic degraded or challenging samples. Here, 184 unrelated individuals from three East Asian minority ethnicities (Tibetan, Uygur and Hui) were analyzed using the Precision ID Identity Panel and the Ion PGM System. The sequencing performance and corresponding forensic statistical parameters of this MPS-SNP panel were investigated. The inter-population relationships and substructures among three investigated populations and 30 worldwide populations were further investigated using PCA, MDS, cladogram and STRUCTURE. No significant deviation from Hardy-Weinberg equilibrium (HWE) and Linkage Disequilibrium (LD) tests was observed across all 90 autosomal SNPs. The combined matching probability (CMP) for Tibetan, Uygur and Hui were 2.5880 × 10 -33 , 1.7480 × 10 -35 and 4.6326 × 10 -34 respectively, and the combined power of exclusion (CPE) were 0.999999386152271, 0.999999607712827 and 0.999999696360182 respectively. For 34 Y-SNPs, only 16 haplogroups were obtained, but the haplogroup distributions differ among the three populations. Tibetans from the Sino-Tibetan population and Hui with multiple ethnicities with an admixture population have genetic affinity with East Asian populations, while Uygurs of a Eurasian admixture population have similar genetic components to the South Asian populations and are distributed between East Asian and European populations. The aforementioned results suggest that the Precision ID Identity Panel is informative and polymorphic in three investigated populations and could be used as an effective tool for human forensics. Copyright © 2018 Elsevier B.V. All rights reserved.
2014-10-01
INTRODUCTION: Despite tremendous advances in mutation detection with gene panels and exome sequencing the majority of high risk breast...2a. Align reads to the reference sequence (months 4-10) 2b. Identify SNPs, indels, CNVs and rearrangements by bioinformatic tools (months 4-10) 2c
Dissimilarity based Partial Least Squares (DPLS) for genomic prediction from SNPs.
Singh, Priyanka; Engel, Jasper; Jansen, Jeroen; de Haan, Jorn; Buydens, Lutgarde Maria Celina
2016-05-04
Genomic prediction (GP) allows breeders to select plants and animals based on their breeding potential for desirable traits, without lengthy and expensive field trials or progeny testing. We have proposed to use Dissimilarity-based Partial Least Squares (DPLS) for GP. As a case study, we use the DPLS approach to predict Bacterial wilt (BW) in tomatoes using SNPs as predictors. The DPLS approach was compared with the Genomic Best-Linear Unbiased Prediction (GBLUP) and single-SNP regression with SNP as a fixed effect to assess the performance of DPLS. Eight genomic distance measures were used to quantify relationships between the tomato accessions from the SNPs. Subsequently, each of these distance measures was used to predict the BW using the DPLS prediction model. The DPLS model was found to be robust to the choice of distance measures; similar prediction performances were obtained for each distance measure. DPLS greatly outperformed the single-SNP regression approach, showing that BW is a comprehensive trait dependent on several loci. Next, the performance of the DPLS model was compared to that of GBLUP. Although GBLUP and DPLS are conceptually very different, the prediction quality (PQ) measured by DPLS models were similar to the prediction statistics obtained from GBLUP. A considerable advantage of DPLS is that the genotype-phenotype relationship can easily be visualized in a 2-D scatter plot. This so-called score-plot provides breeders an insight to select candidates for their future breeding program. DPLS is a highly appropriate method for GP. The model prediction performance was similar to the GBLUP and far better than the single-SNP approach. The proposed method can be used in combination with a wide range of genomic dissimilarity measures and genotype representations such as allele-count, haplotypes or allele-intensity values. Additionally, the data can be insightfully visualized by the DPLS model, allowing for selection of desirable candidates from the breeding experiments. In this study, we have assessed the DPLS performance on a single trait.
Improving mapping and SNP-calling performance in multiplexed targeted next-generation sequencing
2012-01-01
Background Compared to classical genotyping, targeted next-generation sequencing (tNGS) can be custom-designed to interrogate entire genomic regions of interest, in order to detect novel as well as known variants. To bring down the per-sample cost, one approach is to pool barcoded NGS libraries before sample enrichment. Still, we lack a complete understanding of how this multiplexed tNGS approach and the varying performance of the ever-evolving analytical tools can affect the quality of variant discovery. Therefore, we evaluated the impact of different software tools and analytical approaches on the discovery of single nucleotide polymorphisms (SNPs) in multiplexed tNGS data. To generate our own test model, we combined a sequence capture method with NGS in three experimental stages of increasing complexity (E. coli genes, multiplexed E. coli, and multiplexed HapMap BRCA1/2 regions). Results We successfully enriched barcoded NGS libraries instead of genomic DNA, achieving reproducible coverage profiles (Pearson correlation coefficients of up to 0.99) across multiplexed samples, with <10% strand bias. However, the SNP calling quality was substantially affected by the choice of tools and mapping strategy. With the aim of reducing computational requirements, we compared conventional whole-genome mapping and SNP-calling with a new faster approach: target-region mapping with subsequent ‘read-backmapping’ to the whole genome to reduce the false detection rate. Consequently, we developed a combined mapping pipeline, which includes standard tools (BWA, SAMtools, etc.), and tested it on public HiSeq2000 exome data from the 1000 Genomes Project. Our pipeline saved 12 hours of run time per Hiseq2000 exome sample and detected ~5% more SNPs than the conventional whole genome approach. This suggests that more potential novel SNPs may be discovered using both approaches than with just the conventional approach. Conclusions We recommend applying our general ‘two-step’ mapping approach for more efficient SNP discovery in tNGS. Our study has also shown the benefit of computing inter-sample SNP-concordances and inspecting read alignments in order to attain more confident results. PMID:22913592
Chaitanya, Lakshmi; Breslin, Krystal; Zuñiga, Sofia; Wirken, Laura; Pośpiech, Ewelina; Kukla-Bartoszek, Magdalena; Sijen, Titia; Knijff, Peter de; Liu, Fan; Branicki, Wojciech; Kayser, Manfred; Walsh, Susan
2018-07-01
Forensic DNA Phenotyping (FDP), i.e. the prediction of human externally visible traits from DNA, has become a fast growing subfield within forensic genetics due to the intelligence information it can provide from DNA traces. FDP outcomes can help focus police investigations in search of unknown perpetrators, who are generally unidentifiable with standard DNA profiling. Therefore, we previously developed and forensically validated the IrisPlex DNA test system for eye colour prediction and the HIrisPlex system for combined eye and hair colour prediction from DNA traces. Here we introduce and forensically validate the HIrisPlex-S DNA test system (S for skin) for the simultaneous prediction of eye, hair, and skin colour from trace DNA. This FDP system consists of two SNaPshot-based multiplex assays targeting a total of 41 SNPs via a novel multiplex assay for 17 skin colour predictive SNPs and the previous HIrisPlex assay for 24 eye and hair colour predictive SNPs, 19 of which also contribute to skin colour prediction. The HIrisPlex-S system further comprises three statistical prediction models, the previously developed IrisPlex model for eye colour prediction based on 6 SNPs, the previous HIrisPlex model for hair colour prediction based on 22 SNPs, and the recently introduced HIrisPlex-S model for skin colour prediction based on 36 SNPs. In the forensic developmental validation testing, the novel 17-plex assay performed in full agreement with the Scientific Working Group on DNA Analysis Methods (SWGDAM) guidelines, as previously shown for the 24-plex assay. Sensitivity testing of the 17-plex assay revealed complete SNP profiles from as little as 63 pg of input DNA, equalling the previously demonstrated sensitivity threshold of the 24-plex HIrisPlex assay. Testing of simulated forensic casework samples such as blood, semen, saliva stains, of inhibited DNA samples, of low quantity touch (trace) DNA samples, and of artificially degraded DNA samples as well as concordance testing, demonstrated the robustness, efficiency, and forensic suitability of the new 17-plex assay, as previously shown for the 24-plex assay. Finally, we provide an update to the publically available HIrisPlex website https://hirisplex.erasmusmc.nl/, now allowing the estimation of individual probabilities for 3 eye, 4 hair, and 5 skin colour categories from HIrisPlex-S input genotypes. The HIrisPlex-S DNA test represents the first forensically validated tool for skin colour prediction, and reflects the first forensically validated tool for simultaneous eye, hair and skin colour prediction from DNA. Copyright © 2018 Elsevier B.V. All rights reserved.
Galehdari, Hamid; Saki, Najmaldin; Mohammadi-Asl, Javad; Rahim, Fakher
2013-01-01
Crigler-Najjar syndrome (CNS) type I and type II are usually inherited as autosomal recessive conditions that result from mutations in the UGT1A1 gene. The main objective of the present review is to summarize results of all available evidence on the accuracy of SNP-based pathogenicity detection tools compared to published clinical result for the prediction of in nsSNPs that leads to disease using prediction performance method. A comprehensive search was performed to find all mutations related to CNS. Database searches included dbSNP, SNPdbe, HGMD, Swissvar, ensemble, and OMIM. All the mutation related to CNS was extracted. The pathogenicity prediction was done using SNP-based pathogenicity detection tools include SIFT, PHD-SNP, PolyPhen2, fathmm, Provean, and Mutpred. Overall, 59 different SNPs related to missense mutations in the UGT1A1 gene, were reviewed. Comparing the diagnostic OR, PolyPhen2 and Mutpred have the highest detection 4.983 (95% CI: 1.24 - 20.02) in both, following by SIFT (diagnostic OR: 3.25, 95% CI: 1.07 - 9.83). The highest MCC of SNP-based pathogenicity detection tools, was belong to SIFT (34.19%) followed by Provean, PolyPhen2, and Mutpred (29.99%, 29.89%, and 29.89%, respectively). Hence the highest SNP-based pathogenicity detection tools ACC, was fit to SIFT (62.71%) followed by PolyPhen2, and Mutpred (61.02%, in both). Our results suggest that some of the well-established SNP-based pathogenicity detection tools can appropriately reflect the role of a disease-associated SNP in both local and global structures.
Wahab, Tara; Birdsell, Dawn N.; Hjertqvist, Marika; Mitchell, Cedar L.; Wagner, David M.; Keim, Paul S.; Hedenström, Ingela; Löfdahl, Sven
2014-01-01
Tularaemia, caused by the bacterium Francisella tularensis, is endemic in Sweden and is poorly understood. The aim of this study was to evaluate the effectiveness of three different genetic typing systems to link a genetic type to the source and place of tularemia infection in Sweden. Canonical single nucleotide polymorphisms (canSNPs), MLVA including five variable number of tandem repeat loci and PmeI-PFGE were tested on 127 F. tularensis positive specimens collected from Swedish case-patients. All three typing methods identified two major genetic groups with near-perfect agreement. Higher genetic resolution was obtained with canSNP and MLVA compared to PFGE; F. tularensis samples were first assigned into ten phylogroups based on canSNPs followed by 33 unique MLVA types. Phylogroups were geographically analysed to reveal complex phylogeographic patterns in Sweden. The extensive phylogenetic diversity found within individual counties posed a challenge to linking specific genetic types with specific geographic locations. Despite this, a single phylogroup (B.22), defined by a SNP marker specific to a lone Swedish sequenced strain, did link genetic type with a likely geographic place. This result suggests that SNP markers, highly specific to a particular reference genome, may be found most frequently among samples recovered from the same location where the reference genome originated. This insight compels us to consider whole-genome sequencing (WGS) as the appropriate tool for effectively linking specific genetic type to geography. Comparing the WGS of an unknown sample to WGS databases of archived Swedish strains maximizes the likelihood of revealing those rare geographically informative SNPs. PMID:25401326
Stegemeier, John P; Schwab, Fabienne; Colman, Benjamin P; Webb, Samuel M; Newville, Matthew; Lanzirotti, Antonio; Winkler, Christopher; Wiesner, Mark R; Lowry, Gregory V
2015-07-21
Terrestrial crops are directly exposed to silver nanoparticles (Ag-NPs) and their environmentally transformed analog silver sulfide nanoparticles (Ag2S-NPs) when wastewater treatment biosolids are applied as fertilizer to agricultural soils. This leads to a need to understand their bioavailability to plants. In the present study, the mechanisms of uptake and distribution of silver in alfalfa (Medicago sativa) were quantified and visualized upon hydroponic exposure to Ag-NPs, Ag2S-NPs, and AgNO3 at 3 mg total Ag/L. Total silver uptake was measured in dried roots and shoots, and the spatial distribution of elements was investigated using transmission electron microscopy (TEM) and synchrotron-based X-ray imaging techniques. Despite large differences in release of Ag(+) ions from the particles, Ag-NPs, Ag2S-NPs, and Ag(+) became associated with plant roots to a similar degree, and exhibited similarly limited (<1%) amounts of translocation of silver into the shoot system. X-ray fluorescence (XRF) mapping revealed differences in the distribution of Ag into roots for each treatment. Silver nanoparticles mainly accumulated in the (columella) border cells and elongation zone, whereas Ag(+) accumulated more uniformly throughout the root. In contrast, Ag2S-NPs remained largely adhered to the root exterior, and the presence of cytoplasmic nano-SixOy aggregates was observed. Exclusively in roots exposed to particulate silver, NPs smaller than the originally dosed NPs were identified by TEM in the cell walls. The apparent accumulation of Ag in the root apoplast determined by XRF, and the presence of small NPs in root cell walls suggests uptake of partially dissolved NPs and translocation along the apoplast.
Qiu, Jingya; Darabos, Christian
2016-01-01
ABSTRACT Genome‐wide association studies (GWAS) have led to the discovery of over 200 single nucleotide polymorphisms (SNPs) associated with type 2 diabetes mellitus (T2DM). Additionally, East Asians develop T2DM at a higher rate, younger age, and lower body mass index than their European ancestry counterparts. The reason behind this occurrence remains elusive. With comprehensive searches through the National Human Genome Research Institute (NHGRI) GWAS catalog literature, we compiled a database of 2,800 ancestry‐specific SNPs associated with T2DM and 70 other related traits. Manual data extraction was necessary because the GWAS catalog reports statistics such as odds ratio and P‐value, but does not consistently include ancestry information. Currently, many statistics are derived by combining initial and replication samples from study populations of mixed ancestry. Analysis of all‐inclusive data can be misleading, as not all SNPs are transferable across diverse populations. We used ancestry data to construct ancestry‐specific human phenotype networks (HPN) centered on T2DM. Quantitative and visual analysis of network models reveal the genetic disparities between ancestry groups. Of the 27 phenotypes in the East Asian HPN, six phenotypes were unique to the network, revealing the underlying ancestry‐specific nature of some SNPs associated with T2DM. We studied the relationship between T2DM and five phenotypes unique to the East Asian HPN to generate new interaction hypotheses in a clinical context. The genetic differences found in our ancestry‐specific HPNs suggest different pathways are involved in the pathogenesis of T2DM among different populations. Our study underlines the importance of ancestry in the development of T2DM and its implications in pharmocogenetics and personalized medicine. PMID:27061195
Chen, Andrew C H; Tang, Yongqiang; Rangaswamy, Madhavi; Wang, Jen C; Almasy, Laura; Foroud, Tatiana; Edenberg, Howard J; Hesselbrock, Victor; Nurnberger, John; Kuperman, Samuel; O'Connor, Sean J; Schuckit, Marc A; Bauer, Lance O; Tischfield, Jay; Rice, John P; Bierut, Laura; Goate, Alison; Porjesz, Bernice
2009-04-05
Evidence suggests the P3 amplitude of the event-related potential and its underlying superimposed event-related oscillations (EROs), primarily in the theta (4-5 Hz) and delta (1-3 Hz) frequencies, as endophenotypes for the risk of alcoholism and other disinhibitory disorders. Major neurochemical substrates contributing to theta and delta rhythms and P3 involve strong GABAergic, cholinergic and glutamatergic system interactions. The aim of this study was to test the potential associations between single nucleotide polymorphisms (SNPs) in glutamate receptor genes and ERO quantitative traits. GRM8 was selected because it maps at chromosome 7q31.3-q32.1 under the peak region where we previously identified significant linkage (peak LOD = 3.5) using a genome-wide linkage scan of the same phenotype (event-related theta band for the target visual stimuli). Neural activities recorded from scalp electrodes during a visual oddball task in which rare target elicited P3s were analyzed in a subset of the Collaborative Study on the Genetics of Alcoholism (COGA) sample comprising 1,049 Caucasian subjects from 209 families (with 472 DSM-IV alcohol dependent individuals). The family-based association test (FBAT) detected significant association (P < 0.05) with multiple SNPs in the GRM8 gene and event-related theta power to target visual stimuli, and also with alcohol dependence, even after correction for multiple comparisons by false discovery rate (FDR). Our results suggest that variation in GRM8 may be involved in modulating event-related theta oscillations during information processing and also in vulnerability to alcoholism. These findings underscore the utility of electrophysiology and the endophenotype approach in the genetic study of psychiatric disorders. (c) 2008 Wiley-Liss, Inc.
Iterating between Tools to Create and Edit Visualizations.
Bigelow, Alex; Drucker, Steven; Fisher, Danyel; Meyer, Miriah
2017-01-01
A common workflow for visualization designers begins with a generative tool, like D3 or Processing, to create the initial visualization; and proceeds to a drawing tool, like Adobe Illustrator or Inkscape, for editing and cleaning. Unfortunately, this is typically a one-way process: once a visualization is exported from the generative tool into a drawing tool, it is difficult to make further, data-driven changes. In this paper, we propose a bridge model to allow designers to bring their work back from the drawing tool to re-edit in the generative tool. Our key insight is to recast this iteration challenge as a merge problem - similar to when two people are editing a document and changes between them need to reconciled. We also present a specific instantiation of this model, a tool called Hanpuku, which bridges between D3 scripts and Illustrator. We show several examples of visualizations that are iteratively created using Hanpuku in order to illustrate the flexibility of the approach. We further describe several hypothetical tools that bridge between other visualization tools to emphasize the generality of the model.
Survey of visualization and analysis tools
NASA Technical Reports Server (NTRS)
Meyer, P. J.
1994-01-01
A large number of commercially available visualization and analysis tools are available to the researcher. Some of the strengths and limitations of some of these tools, from the viewpoint of the earth sciences discipline, are discussed. Visualization and analysis tools fall into one of two categories: those that are designed to a specific purpose and are non-extensive and those that are generic visual programming tools that are extensible. Most of the extensible packages examined incorporate a data flow paradigm.
DMET-analyzer: automatic analysis of Affymetrix DMET data.
Guzzi, Pietro Hiram; Agapito, Giuseppe; Di Martino, Maria Teresa; Arbitrio, Mariamena; Tassone, Pierfrancesco; Tagliaferri, Pierosandro; Cannataro, Mario
2012-10-05
Clinical Bioinformatics is currently growing and is based on the integration of clinical and omics data aiming at the development of personalized medicine. Thus the introduction of novel technologies able to investigate the relationship among clinical states and biological machineries may help the development of this field. For instance the Affymetrix DMET platform (drug metabolism enzymes and transporters) is able to study the relationship among the variation of the genome of patients and drug metabolism, detecting SNPs (Single Nucleotide Polymorphism) on genes related to drug metabolism. This may allow for instance to find genetic variants in patients which present different drug responses, in pharmacogenomics and clinical studies. Despite this, there is currently a lack in the development of open-source algorithms and tools for the analysis of DMET data. Existing software tools for DMET data generally allow only the preprocessing of binary data (e.g. the DMET-Console provided by Affymetrix) and simple data analysis operations, but do not allow to test the association of the presence of SNPs with the response to drugs. We developed DMET-Analyzer a tool for the automatic association analysis among the variation of the patient genomes and the clinical conditions of patients, i.e. the different response to drugs. The proposed system allows: (i) to automatize the workflow of analysis of DMET-SNP data avoiding the use of multiple tools; (ii) the automatic annotation of DMET-SNP data and the search in existing databases of SNPs (e.g. dbSNP), (iii) the association of SNP with pathway through the search in PharmaGKB, a major knowledge base for pharmacogenomic studies. DMET-Analyzer has a simple graphical user interface that allows users (doctors/biologists) to upload and analyse DMET files produced by Affymetrix DMET-Console in an interactive way. The effectiveness and easy use of DMET Analyzer is demonstrated through different case studies regarding the analysis of clinical datasets produced in the University Hospital of Catanzaro, Italy. DMET Analyzer is a novel tool able to automatically analyse data produced by the DMET-platform in case-control association studies. Using such tool user may avoid wasting time in the manual execution of multiple statistical tests avoiding possible errors and reducing the amount of time needed for a whole experiment. Moreover annotations and the direct link to external databases may increase the biological knowledge extracted. The system is freely available for academic purposes at: https://sourceforge.net/projects/dmetanalyzer/files/
Gilbert, Rebecca; Martin, Richard M.; Evans, David M.; Tilling, Kate; Davey Smith, George; Kemp, John P.; Lane, J. Athene; Hamdy, Freddie C.; Neal, David E.; Donovan, Jenny L.; Metcalfe, Chris
2015-01-01
Introduction Prostate-specific antigen (PSA) testing is a widely accepted screening method for prostate cancer, but with low specificity at thresholds giving good sensitivity. Previous research identified four single nucleotide polymorphisms (SNPs) principally associated with circulating PSA levels rather than with prostate cancer risk (TERT rs2736098, FGFR2 rs10788160, TBX3 rs11067228, KLK3 rs17632542). Removing the genetic contribution to PSA levels may improve the ability of the remaining biologically-determined variation in PSA to discriminate between high and low risk of progression within men with identified prostate cancer. We investigate whether incorporating information on the PSA-SNPs improves the discrimination achieved by a single PSA threshold in men with raised PSA levels. Materials and Methods Men with PSA between 3-10ng/mL and histologically-confirmed prostate cancer were categorised as high or low risk of progression (Low risk: Gleason score≤6 and stage T1-T2a; High risk: Gleason score 7–10 or stage T2C). We used the combined genetic effect of the four PSA-SNPs to calculate a genetically corrected PSA risk score. We calculated the Area under the Curve (AUC) to determine how well genetically corrected PSA risk scores distinguished men at high risk of progression from low risk men. Results The analysis includes 868 men with prostate cancer (Low risk: 684 (78.8%); High risk: 184 (21.2%)). Receiver operating characteristic (ROC) curves indicate that including the 4 PSA-SNPs does not improve the performance of measured PSA as a screening tool for high/low risk prostate cancer (measured PSA level AU C = 59.5% (95% CI: 54.7,64.2) vs additionally including information from the 4 PSA-SNPs AUC = 59.8% (95% CI: 55.2,64.5) (p-value = 0.40)). Conclusion We demonstrate that genetically correcting PSA for the combined genetic effect of four PSA-SNPs, did not improve discrimination between high and low risk prostate cancer in men with raised PSA levels (3-10ng/mL). Replication and gaining more accurate estimates of the effects of the 4 PSA-SNPs and additional variants associated with PSA levels and not prostate cancer could be obtained from subsequent GWAS from larger prospective studies. PMID:26431041
Muñoz, Irene; Henriques, Dora; Jara, Laura; Johnston, J Spencer; Chávez-Galarza, Julio; De La Rúa, Pilar; Pinto, M Alice
2017-07-01
The honeybee (Apis mellifera) has been threatened by multiple factors including pests and pathogens, pesticides and loss of locally adapted gene complexes due to replacement and introgression. In western Europe, the genetic integrity of the native A. m. mellifera (M-lineage) is endangered due to trading and intensive queen breeding with commercial subspecies of eastern European ancestry (C-lineage). Effective conservation actions require reliable molecular tools to identify pure-bred A. m. mellifera colonies. Microsatellites have been preferred for identification of A. m. mellifera stocks across conservation centres. However, owing to high throughput, easy transferability between laboratories and low genotyping error, SNPs promise to become popular. Here, we compared the resolving power of a widely utilized microsatellite set to detect structure and introgression with that of different sets that combine a variable number of SNPs selected for their information content and genomic proximity to the microsatellite loci. Contrary to every SNP data set, microsatellites did not discriminate between the two lineages in the PCA space. Mean introgression proportions were identical across the two marker types, although at the individual level, microsatellites' performance was relatively poor at the upper range of Q-values, a result reflected by their lower precision. Our results suggest that SNPs are more accurate and powerful than microsatellites for identification of A. m. mellifera colonies, especially when they are selected by information content. © 2016 John Wiley & Sons Ltd.
BayesPI-BAR: a new biophysical model for characterization of regulatory sequence variations
Wang, Junbai; Batmanov, Kirill
2015-01-01
Sequence variations in regulatory DNA regions are known to cause functionally important consequences for gene expression. DNA sequence variations may have an essential role in determining phenotypes and may be linked to disease; however, their identification through analysis of massive genome-wide sequencing data is a great challenge. In this work, a new computational pipeline, a Bayesian method for protein–DNA interaction with binding affinity ranking (BayesPI-BAR), is proposed for quantifying the effect of sequence variations on protein binding. BayesPI-BAR uses biophysical modeling of protein–DNA interactions to predict single nucleotide polymorphisms (SNPs) that cause significant changes in the binding affinity of a regulatory region for transcription factors (TFs). The method includes two new parameters (TF chemical potentials or protein concentrations and direct TF binding targets) that are neglected by previous methods. The new method is verified on 67 known human regulatory SNPs, of which 47 (70%) have predicted true TFs ranked in the top 10. Importantly, the performance of BayesPI-BAR, which uses principal component analysis to integrate multiple predictions from various TF chemical potentials, is found to be better than that of existing programs, such as sTRAP and is-rSNP, when evaluated on the same SNPs. BayesPI-BAR is a publicly available tool and is able to carry out parallelized computation, which helps to investigate a large number of TFs or SNPs and to detect disease-associated regulatory sequence variations in the sea of genome-wide noncoding regions. PMID:26202972
Song, Peng; Zhu, Haixia; Zhang, Dong; Chu, Haiyan; Wu, Dongmei; Kang, Meiyun; Wang, Meilin; Gong, Weida; Zhou, Jianwei; Zhang, Zhengdong; Zhao, Qinghong
2014-11-17
Single nucleotide polymorphisms (SNPs) in the 3'-untranslated regions targeted by putative mircoRNA can change its binding strength, affecting the susceptibility and prognosis of cancer. We aimed to investigate the associations between SNPs within miR-148a binding sites and gastric cancer (GC) risk and prognosis. Using bioinformatics tools, we selected two SNPs (SCRN1 rs6976789 and PDYN rs2235749) located in miR-148a target sites. We genotyped the two SNPs in a case-control study comprising 753 GC patients and 949 cancer-free subjects. We found a significantly increased risk of GC associated with the SCRN1 rs6976789 C>T polymorphism [adjusted OR = 1.25, 95% confidence interval (CI) = 1.02-1.53; CT/TT vs. CC]. However, no significant association was found between the PDYN rs2235749 and GC risk in all genetic models. Furthermore, we evaluated whether SCRN1 rs6976789 affected the survival of GC patients. Results showed that individuals with SCRN1 rs6976789 TT genotype had poorer overall survival compared with those carried CC/CT genotypes in intestinal-type GC (adjusted HR = 2.47, 95% CI = 1.21-5.05). Luciferase report assay showed that the rs6976789 variant T allele influenced the binding ability of miR-148a. Our results suggested that the SCRN1 rs6976789 polymorphism may play an important role in the GC development and progression.
FABP4 is a leading candidate gene associated with residual feed intake in growing Holstein calves.
Cohen-Zinder, Miri; Asher, Aviv; Lipkin, Ehud; Feingersch, Roi; Agmon, Rotem; Karasik, David; Brosh, Arieh; Shabtay, Ariel
2016-05-01
Ecological and economic concerns drive the need to improve feed utilization by domestic animals. Residual feed intake (RFI) is one of the most acceptable measures for feed efficiency (FE). However, phenotyping RFI-related traits is complex and expensive and requires special equipment. Advances in marker technology allow the development of various DNA-based selection tools. To assimilate these technologies for the benefit of RFI-based selection, reliable phenotypic measures are prerequisite. In the current study, we identified single nucleotide polymorphisms (SNPs) associated with RFI phenotypic consistency across different ages and diets (named RFI 1-3), using DNA samples of high or low RFI ranked Holstein calves. Using targeted sequencing of chromosomal regions associated with FE- and RFI-related traits, we identified 48 top SNPs significantly associated with at least one of three defined RFIs. Eleven of these SNPs were harbored by the fatty acid binding protein 4 (FABP4). While 10 significant SNPs found in FABP4 were common for RFI 1 and RFI 3, one SNP (FABP4_5; A
Lapitan Jr., Lorico D. S.; Guo, Yuan
2015-01-01
Single nucleotide polymorphisms (SNPs) constitute the most common types of genetic variations in the human genome. A number of SNPs have been linked to the development of life threatening diseases including cancer, cardiovascular diseases and neurodegenerative diseases. The ability for ultrasensitive and accurate detection of low abundant disease-related SNPs in bodily fluids (e.g. blood, serum, etc.) holds a significant value in the development of non-invasive future biodiagnostic tools. Over the past two decades, nanomaterials have been utilized in a myriad of biosensing applications due to their ability of detecting extremely low quantities of biologically important biomarkers with high sensitivity and accuracy. Of particular interest is the application of such technologies in the detection of SNPs. The use of various nanomaterials, coupled with different powerful signal amplification strategies, has paved the way for a new generation of ultrasensitive SNP biodiagnostic assays. Over the past few years, several ultrasensitive SNP biosensors capable of detecting specific targets down to the ultra-low regimes (ca. aM and below) and therefore holding great promises for early clinical diagnosis of diseases have been developed. This mini review will highlight some of the most recent, significant advances in nanomaterial-based ultrasensitive SNP sensing technologies capable of detecting specific targets on the attomolar (10–18 M) regime or below. In particular, the design of novel, powerful signal amplification strategies that hold the key to the ultrasensitivity is highlighted. PMID:25785914
Haplotag: Software for Haplotype-Based Genotyping-by-Sequencing Analysis
Tinker, Nicholas A.; Bekele, Wubishet A.; Hattori, Jiro
2016-01-01
Genotyping-by-sequencing (GBS), and related methods, are based on high-throughput short-read sequencing of genomic complexity reductions followed by discovery of single nucleotide polymorphisms (SNPs) within sequence tags. This provides a powerful and economical approach to whole-genome genotyping, facilitating applications in genomics, diversity analysis, and molecular breeding. However, due to the complexity of analyzing large data sets, applications of GBS may require substantial time, expertise, and computational resources. Haplotag, the novel GBS software described here, is freely available, and operates with minimal user-investment on widely available computer platforms. Haplotag is unique in fulfilling the following set of criteria: (1) operates without a reference genome; (2) can be used in a polyploid species; (3) provides a discovery mode, and a production mode; (4) discovers polymorphisms based on a model of tag-level haplotypes within sequenced tags; (5) reports SNPs as well as haplotype-based genotypes; and (6) provides an intuitive visual “passport” for each inferred locus. Haplotag is optimized for use in a self-pollinating plant species. PMID:26818073
Integrated Data Visualization and Virtual Reality Tool
NASA Technical Reports Server (NTRS)
Dryer, David A.
1998-01-01
The Integrated Data Visualization and Virtual Reality Tool (IDVVRT) Phase II effort was for the design and development of an innovative Data Visualization Environment Tool (DVET) for NASA engineers and scientists, enabling them to visualize complex multidimensional and multivariate data in a virtual environment. The objectives of the project were to: (1) demonstrate the transfer and manipulation of standard engineering data in a virtual world; (2) demonstrate the effects of design and changes using finite element analysis tools; and (3) determine the training and engineering design and analysis effectiveness of the visualization system.
The Development of a Visual-Perceptual Chemistry Specific (VPCS) Assessment Tool
ERIC Educational Resources Information Center
Oliver-Hoyo, Maria; Sloan, Caroline
2014-01-01
The development of the Visual-Perceptual Chemistry Specific (VPCS) assessment tool is based on items that align to eight visual-perceptual skills considered as needed by chemistry students. This tool includes a comprehensive range of visual operations and presents items within a chemistry context without requiring content knowledge to solve…
Ma, Yu; Coyne, Clarice J; Grusak, Michael A; Mazourek, Michael; Cheng, Peng; Main, Dorrie; McGee, Rebecca J
2017-02-13
Marker-assisted breeding is now routinely used in major crops to facilitate more efficient cultivar improvement. This has been significantly enabled by the use of next-generation sequencing technology to identify loci and markers associated with traits of interest. While rich in a range of nutritional components, such as protein, mineral nutrients, carbohydrates and several vitamins, pea (Pisum sativum L.), one of the oldest domesticated crops in the world, remains behind many other crops in the availability of genomic and genetic resources. To further improve mineral nutrient levels in pea seeds requires the development of genome-wide tools. The objectives of this research were to develop these tools by: identifying genome-wide single nucleotide polymorphisms (SNPs) using genotyping by sequencing (GBS); constructing a high-density linkage map and comparative maps with other legumes, and identifying quantitative trait loci (QTL) for levels of boron, calcium, iron, potassium, magnesium, manganese, molybdenum, phosphorous, sulfur, and zinc in the seed, as well as for seed weight. In this study, 1609 high quality SNPs were found to be polymorphic between 'Kiflica' and 'Aragorn', two parents of an F 6 -derived recombinant inbred line (RIL) population. Mapping 1683 markers including 75 previously published markers and 1608 SNPs developed from the present study generated a linkage map of size 1310.1 cM. Comparative mapping with other legumes demonstrated that the highest level of synteny was observed between pea and the genome of Medicago truncatula. QTL analysis of the RIL population across two locations revealed at least one QTL for each of the mineral nutrient traits. In total, 46 seed mineral concentration QTLs, 37 seed mineral content QTLs, and 6 seed weight QTLs were discovered. The QTLs explained from 2.4% to 43.3% of the phenotypic variance. The genome-wide SNPs and the genetic linkage map developed in this study permitted QTL identification for pea seed mineral nutrients that will serve as important resources to enable marker-assisted selection (MAS) for nutritional quality traits in pea breeding programs.
Oguz, Cihan; Sen, Shurjo K; Davis, Adam R; Fu, Yi-Ping; O'Donnell, Christopher J; Gibbons, Gary H
2017-10-26
One goal of personalized medicine is leveraging the emerging tools of data science to guide medical decision-making. Achieving this using disparate data sources is most daunting for polygenic traits. To this end, we employed random forests (RFs) and neural networks (NNs) for predictive modeling of coronary artery calcium (CAC), which is an intermediate endo-phenotype of coronary artery disease (CAD). Model inputs were derived from advanced cases in the ClinSeq®; discovery cohort (n=16) and the FHS replication cohort (n=36) from 89 th -99 th CAC score percentile range, and age-matched controls (ClinSeq®; n=16, FHS n=36) with no detectable CAC (all subjects were Caucasian males). These inputs included clinical variables and genotypes of 56 single nucleotide polymorphisms (SNPs) ranked highest in terms of their nominal correlation with the advanced CAC state in the discovery cohort. Predictive performance was assessed by computing the areas under receiver operating characteristic curves (ROC-AUC). RF models trained and tested with clinical variables generated ROC-AUC values of 0.69 and 0.61 in the discovery and replication cohorts, respectively. In contrast, in both cohorts, the set of SNPs derived from the discovery cohort were highly predictive (ROC-AUC ≥0.85) with no significant change in predictive performance upon integration of clinical and genotype variables. Using the 21 SNPs that produced optimal predictive performance in both cohorts, we developed NN models trained with ClinSeq®; data and tested with FHS data and obtained high predictive accuracy (ROC-AUC=0.80-0.85) with several topologies. Several CAD and "vascular aging" related biological processes were enriched in the network of genes constructed from the predictive SNPs. We identified a molecular network predictive of advanced coronary calcium using genotype data from ClinSeq®; and FHS cohorts. Our results illustrate that machine learning tools, which utilize complex interactions between disease predictors intrinsic to the pathogenesis of polygenic disorders, hold promise for deriving predictive disease models and networks.
Making a chocolate chip: development and evaluation of a 6K SNP array for Theobroma cacao.
Livingstone, Donald; Royaert, Stefan; Stack, Conrad; Mockaitis, Keithanne; May, Greg; Farmer, Andrew; Saski, Christopher; Schnell, Ray; Kuhn, David; Motamayor, Juan Carlos
2015-08-01
Theobroma cacao, the key ingredient in chocolate production, is one of the world's most important tree fruit crops, with ∼4,000,000 metric tons produced across 50 countries. To move towards gene discovery and marker-assisted breeding in cacao, a single-nucleotide polymorphism (SNP) identification project was undertaken using RNAseq data from 16 diverse cacao cultivars. RNA sequences were aligned to the assembled transcriptome of the cultivar Matina 1-6, and 330,000 SNPs within coding regions were identified. From these SNPs, a subset of 6,000 high-quality SNPs were selected for inclusion on an Illumina Infinium SNP array: the Cacao6kSNP array. Using Cacao6KSNP array data from over 1,000 cacao samples, we demonstrate that our custom array produces a saturated genetic map and can be used to distinguish among even closely related genotypes. Our study enhances and expands the genetic resources available to the cacao research community, and provides the genome-scale set of tools that are critical for advancing breeding with molecular markers in an agricultural species with high genetic diversity. © The Author 2015. Published by Oxford University Press on behalf of Kazusa DNA Research Institute.
1-CMDb: A Curated Database of Genomic Variations of the One-Carbon Metabolism Pathway.
Bhat, Manoj K; Gadekar, Veerendra P; Jain, Aditya; Paul, Bobby; Rai, Padmalatha S; Satyamoorthy, Kapaettu
2017-01-01
The one-carbon metabolism pathway is vital in maintaining tissue homeostasis by driving the critical reactions of folate and methionine cycles. A myriad of genetic and epigenetic events mark the rate of reactions in a tissue-specific manner. Integration of these to predict and provide personalized health management requires robust computational tools that can process multiomics data. The DNA sequences that may determine the chain of biological events and the endpoint reactions within one-carbon metabolism genes remain to be comprehensively recorded. Hence, we designed the one-carbon metabolism database (1-CMDb) as a platform to interrogate its association with a host of human disorders. DNA sequence and network information of a total of 48 genes were extracted from a literature survey and KEGG pathway that are involved in the one-carbon folate-mediated pathway. The information generated, collected, and compiled for all these genes from the UCSC genome browser included the single nucleotide polymorphisms (SNPs), CpGs, copy number variations (CNVs), and miRNAs, and a comprehensive database was created. Furthermore, a significant correlation analysis was performed for SNPs in the pathway genes. Detailed data of SNPs, CNVs, CpG islands, and miRNAs for 48 folate pathway genes were compiled. The SNPs in CNVs (9670), CpGs (984), and miRNAs (14) were also compiled for all pathway genes. The SIFT score, the prediction and PolyPhen score, as well as the prediction for each of the SNPs were tabulated and represented for folate pathway genes. Also included in the database for folate pathway genes were the links to 124 various phenotypes and disease associations as reported in the literature and from publicly available information. A comprehensive database was generated consisting of genomic elements within and among SNPs, CNVs, CpGs, and miRNAs of one-carbon metabolism pathways to facilitate (a) single source of information and (b) integration into large-genome scale network analysis to be developed in the future by the scientific community. The database can be accessed at http://slsdb.manipal.edu/ocm/. © 2017 S. Karger AG, Basel.
DOT National Transportation Integrated Search
2012-06-01
The use of visual simulation tools to convey complex concepts has become a useful tool in education as well as in research. : This report describes a project that developed curriculum and visualization tools to train transportation engineering studen...
Communications Effects Server (CES) Model for Systems Engineering Research
2012-01-31
Visualization Tool Interface «logical» HLA Tool Interface «logical» DIS Tool Interface «logical» STK Tool Interface «module» Execution Kernels «logical...interoperate with STK when running simulations. GUI Components Architect – The Architect represents the main network design and visualization ...interest» CES «block» Third Party Visualization Tool «block» Third Party Analysis Tool «block» Third Party Text Editor «block» HLA Tools Analyst User Army
SPSmart: adapting population based SNP genotype databases for fast and comprehensive web access.
Amigo, Jorge; Salas, Antonio; Phillips, Christopher; Carracedo, Angel
2008-10-10
In the last five years large online resources of human variability have appeared, notably HapMap, Perlegen and the CEPH foundation. These databases of genotypes with population information act as catalogues of human diversity, and are widely used as reference sources for population genetics studies. Although many useful conclusions may be extracted by querying databases individually, the lack of flexibility for combining data from within and between each database does not allow the calculation of key population variability statistics. We have developed a novel tool for accessing and combining large-scale genomic databases of single nucleotide polymorphisms (SNPs) in widespread use in human population genetics: SPSmart (SNPs for Population Studies). A fast pipeline creates and maintains a data mart from the most commonly accessed databases of genotypes containing population information: data is mined, summarized into the standard statistical reference indices, and stored into a relational database that currently handles as many as 4 x 10(9) genotypes and that can be easily extended to new database initiatives. We have also built a web interface to the data mart that allows the browsing of underlying data indexed by population and the combining of populations, allowing intuitive and straightforward comparison of population groups. All the information served is optimized for web display, and most of the computations are already pre-processed in the data mart to speed up the data browsing and any computational treatment requested. In practice, SPSmart allows populations to be combined into user-defined groups, while multiple databases can be accessed and compared in a few simple steps from a single query. It performs the queries rapidly and gives straightforward graphical summaries of SNP population variability through visual inspection of allele frequencies outlined in standard pie-chart format. In addition, full numerical description of the data is output in statistical results panels that include common population genetics metrics such as heterozygosity, Fst and In.
Myers, Simon; Hellenthal, Garrett; Nerrienet, Eric; Bontrop, Ronald E.; Freeman, Colin; Donnelly, Peter; Mundy, Nicholas I.
2012-01-01
In spite of its evolutionary significance and conservation importance, the population structure of the common chimpanzee, Pan troglodytes, is still poorly understood. An issue of particular controversy is whether the proposed fourth subspecies of chimpanzee, Pan troglodytes ellioti, from parts of Nigeria and Cameroon, is genetically distinct. Although modern high-throughput SNP genotyping has had a major impact on our understanding of human population structure and demographic history, its application to ecological, demographic, or conservation questions in non-human species has been extremely limited. Here we apply these tools to chimpanzee population structure, using ∼700 autosomal SNPs derived from chimpanzee genomic data and a further ∼100 SNPs from targeted re-sequencing. We demonstrate conclusively the existence of P. t. ellioti as a genetically distinct subgroup. We show that there is clear differentiation between the verus, troglodytes, and ellioti populations at the SNP and haplotype level, on a scale that is greater than that separating continental human populations. Further, we show that only a small set of SNPs (10–20) is needed to successfully assign individuals to these populations. Tellingly, use of only mitochondrial DNA variation to classify individuals is erroneous in 4 of 54 cases, reinforcing the dangers of basing demographic inference on a single locus and implying that the demographic history of the species is more complicated than that suggested analyses based solely on mtDNA. In this study we demonstrate the feasibility of developing economical and robust tests of individual chimpanzee origin as well as in-depth studies of population structure. These findings have important implications for conservation strategies and our understanding of the evolution of chimpanzees. They also act as a proof-of-principle for the use of cheap high-throughput genomic methods for ecological questions. PMID:22396655
Bowden, Rory; MacFie, Tammie S; Myers, Simon; Hellenthal, Garrett; Nerrienet, Eric; Bontrop, Ronald E; Freeman, Colin; Donnelly, Peter; Mundy, Nicholas I
2012-01-01
In spite of its evolutionary significance and conservation importance, the population structure of the common chimpanzee, Pan troglodytes, is still poorly understood. An issue of particular controversy is whether the proposed fourth subspecies of chimpanzee, Pan troglodytes ellioti, from parts of Nigeria and Cameroon, is genetically distinct. Although modern high-throughput SNP genotyping has had a major impact on our understanding of human population structure and demographic history, its application to ecological, demographic, or conservation questions in non-human species has been extremely limited. Here we apply these tools to chimpanzee population structure, using ∼700 autosomal SNPs derived from chimpanzee genomic data and a further ∼100 SNPs from targeted re-sequencing. We demonstrate conclusively the existence of P. t. ellioti as a genetically distinct subgroup. We show that there is clear differentiation between the verus, troglodytes, and ellioti populations at the SNP and haplotype level, on a scale that is greater than that separating continental human populations. Further, we show that only a small set of SNPs (10-20) is needed to successfully assign individuals to these populations. Tellingly, use of only mitochondrial DNA variation to classify individuals is erroneous in 4 of 54 cases, reinforcing the dangers of basing demographic inference on a single locus and implying that the demographic history of the species is more complicated than that suggested analyses based solely on mtDNA. In this study we demonstrate the feasibility of developing economical and robust tests of individual chimpanzee origin as well as in-depth studies of population structure. These findings have important implications for conservation strategies and our understanding of the evolution of chimpanzees. They also act as a proof-of-principle for the use of cheap high-throughput genomic methods for ecological questions.
De La Vega, Francisco M; Dailey, David; Ziegle, Janet; Williams, Julie; Madden, Dawn; Gilbert, Dennis A
2002-06-01
Since public and private efforts announced the first draft of the human genome last year, researchers have reported great numbers of single nucleotide polymorphisms (SNPs). We believe that the availability of well-mapped, quality SNP markers constitutes the gateway to a revolution in genetics and personalized medicine that will lead to better diagnosis and treatment of common complex disorders. A new generation of tools and public SNP resources for pharmacogenomic and genetic studies--specifically for candidate-gene, candidate-region, and whole-genome association studies--will form part of the new scientific landscape. This will only be possible through the greater accessibility of SNP resources and superior high-throughput instrumentation-assay systems that enable affordable, highly productive large-scale genetic studies. We are contributing to this effort by developing a high-quality linkage disequilibrium SNP marker map and an accompanying set of ready-to-use, validated SNP assays across every gene in the human genome. This effort incorporates both the public sequence and SNP data sources, and Celera Genomics' human genome assembly and enormous resource ofphysically mapped SNPs (approximately 4,000,000 unique records). This article discusses our approach and methodology for designing the map, choosing quality SNPs, designing and validating these assays, and obtaining population frequency ofthe polymorphisms. We also discuss an advanced, high-performance SNP assay chemisty--a new generation of the TaqMan probe-based, 5' nuclease assay-and high-throughput instrumentation-software system for large-scale genotyping. We provide the new SNP map and validation information, validated SNP assays and reagents, and instrumentation systems as a novel resource for genetic discoveries.
Broekgaarden, Colette; Bucher, Johan; Bac-Molenaar, Johanna; Keurentjes, Joost J. B.; Kruijer, Willem; Voorrips, Roeland E.; Vosman, Ben
2015-01-01
Plants have evolved a variety of ways to defend themselves against biotic attackers. This has resulted in the presence of substantial variation in defense mechanisms among plants, even within a species. Genome-wide association (GWA) mapping is a useful tool to study the genetic architecture of traits, but has so far only had limited exploitation in studies of plant defense. Here, we study the genetic architecture of defense against the phloem-feeding insect cabbage whitefly (Aleyrodes proletella) in Arabidopsis thaliana. We determined whitefly performance, i.e. the survival and reproduction of whitefly females, on 360 worldwide selected natural accessions and subsequently performed GWA mapping using 214,051 SNPs. Substantial variation for whitefly adult survival and oviposition rate (number of eggs laid per female per day) was observed between the accessions. We identified 39 candidate SNPs for either whitefly adult survival or oviposition rate, all with relatively small effects, underpinning the complex architecture of defense traits. Among the corresponding candidate genes, i.e. genes in linkage disequilibrium (LD) with candidate SNPs, none have previously been identified as a gene playing a role in the interaction between plants and phloem-feeding insects. Whitefly performance on knock-out mutants of a number of candidate genes was significantly affected, validating the potential of GWA mapping for novel gene discovery in plant-insect interactions. Our results show that GWA analysis is a very useful tool to gain insight into the genetic architecture of plant defense against herbivorous insects, i.e. we identified and validated several genes affecting whitefly performance that have not previously been related to plant defense against herbivorous insects. PMID:26699853
2011-10-01
the HapMap samples across batches. We also calculated identity-by- descent (IBD) and identity-by-state (IBS) measures to confirm the identity of the...development of adverse events following radiotherapy. Such a tool could be used to aid clinicians in personalizing dosage to improve the therapeutic index of
Scalable Visual Analytics of Massive Textual Datasets
DOE Office of Scientific and Technical Information (OSTI.GOV)
Krishnan, Manoj Kumar; Bohn, Shawn J.; Cowley, Wendy E.
2007-04-01
This paper describes the first scalable implementation of text processing engine used in Visual Analytics tools. These tools aid information analysts in interacting with and understanding large textual information content through visual interfaces. By developing parallel implementation of the text processing engine, we enabled visual analytics tools to exploit cluster architectures and handle massive dataset. The paper describes key elements of our parallelization approach and demonstrates virtually linear scaling when processing multi-gigabyte data sets such as Pubmed. This approach enables interactive analysis of large datasets beyond capabilities of existing state-of-the art visual analytics tools.
Wang, Lin; Liu, Simin; Niu, Tianhua; Xu, Xin
2005-03-18
Single nucleotide polymorphisms (SNPs) provide an important tool in pinpointing susceptibility genes for complex diseases and in unveiling human molecular evolution. Selection and retrieval of an optimal SNP set from publicly available databases have emerged as the foremost bottlenecks in designing large-scale linkage disequilibrium studies, particularly in case-control settings. We describe the architectural structure and implementations of a novel software program, SNPHunter, which allows for both ad hoc-mode and batch-mode SNP search, automatic SNP filtering, and retrieval of SNP data, including physical position, function class, flanking sequences at user-defined lengths, and heterozygosity from NCBI dbSNP. The SNP data extracted from dbSNP via SNPHunter can be exported and saved in plain text format for further down-stream analyses. As an illustration, we applied SNPHunter for selecting SNPs for 10 major candidate genes for type 2 diabetes, including CAPN10, FABP4, IL6, NOS3, PPARG, TNF, UCP2, CRP, ESR1, and AR. SNPHunter constitutes an efficient and user-friendly tool for SNP screening, selection, and acquisition. The executable and user's manual are available at http://www.hsph.harvard.edu/ppg/software.htm
A graph algebra for scalable visual analytics.
Shaverdian, Anna A; Zhou, Hao; Michailidis, George; Jagadish, Hosagrahar V
2012-01-01
Visual analytics (VA), which combines analytical techniques with advanced visualization features, is fast becoming a standard tool for extracting information from graph data. Researchers have developed many tools for this purpose, suggesting a need for formal methods to guide these tools' creation. Increased data demands on computing requires redesigning VA tools to consider performance and reliability in the context of analysis of exascale datasets. Furthermore, visual analysts need a way to document their analyses for reuse and results justification. A VA graph framework encapsulated in a graph algebra helps address these needs. Its atomic operators include selection and aggregation. The framework employs a visual operator and supports dynamic attributes of data to enable scalable visual exploration of data.
The Multisensory Attentional Consequences of Tool Use: A Functional Magnetic Resonance Imaging Study
Holmes, Nicholas P.; Spence, Charles; Hansen, Peter C.; Mackay, Clare E.; Calvert, Gemma A.
2008-01-01
Background Tool use in humans requires that multisensory information is integrated across different locations, from objects seen to be distant from the hand, but felt indirectly at the hand via the tool. We tested the hypothesis that using a simple tool to perceive vibrotactile stimuli results in the enhanced processing of visual stimuli presented at the distal, functional part of the tool. Such a finding would be consistent with a shift of spatial attention to the location where the tool is used. Methodology/Principal Findings We tested this hypothesis by scanning healthy human participants' brains using functional magnetic resonance imaging, while they used a simple tool to discriminate between target vibrations, accompanied by congruent or incongruent visual distractors, on the same or opposite side to the tool. The attentional hypothesis was supported: BOLD response in occipital cortex, particularly in the right hemisphere lingual gyrus, varied significantly as a function of tool position, increasing contralaterally, and decreasing ipsilaterally to the tool. Furthermore, these modulations occurred despite the fact that participants were repeatedly instructed to ignore the visual stimuli, to respond only to the vibrotactile stimuli, and to maintain visual fixation centrally. In addition, the magnitude of multisensory (visual-vibrotactile) interactions in participants' behavioural responses significantly predicted the BOLD response in occipital cortical areas that were also modulated as a function of both visual stimulus position and tool position. Conclusions/Significance These results show that using a simple tool to locate and to perceive vibrotactile stimuli is accompanied by a shift of spatial attention to the location where the functional part of the tool is used, resulting in enhanced processing of visual stimuli at that location, and decreased processing at other locations. This was most clearly observed in the right hemisphere lingual gyrus. Such modulations of visual processing may reflect the functional importance of visuospatial information during human tool use. PMID:18958150
Visualization Tools for Teaching Computer Security
ERIC Educational Resources Information Center
Yuan, Xiaohong; Vega, Percy; Qadah, Yaseen; Archer, Ricky; Yu, Huiming; Xu, Jinsheng
2010-01-01
Using animated visualization tools has been an important teaching approach in computer science education. We have developed three visualization and animation tools that demonstrate various information security concepts and actively engage learners. The information security concepts illustrated include: packet sniffer and related computer network…
Visualization and Analytics Tools for Infectious Disease Epidemiology: A Systematic Review
Carroll, Lauren N.; Au, Alan P.; Detwiler, Landon Todd; Fu, Tsung-chieh; Painter, Ian S.; Abernethy, Neil F.
2014-01-01
Background A myriad of new tools and algorithms have been developed to help public health professionals analyze and visualize the complex data used in infectious disease control. To better understand approaches to meet these users' information needs, we conducted a systematic literature review focused on the landscape of infectious disease visualization tools for public health professionals, with a special emphasis on geographic information systems (GIS), molecular epidemiology, and social network analysis. The objectives of this review are to: (1) Identify public health user needs and preferences for infectious disease information visualization tools; (2) Identify existing infectious disease information visualization tools and characterize their architecture and features; (3) Identify commonalities among approaches applied to different data types; and (4) Describe tool usability evaluation efforts and barriers to the adoption of such tools. Methods We identified articles published in English from January 1, 1980 to June 30, 2013 from five bibliographic databases. Articles with a primary focus on infectious disease visualization tools, needs of public health users, or usability of information visualizations were included in the review. Results A total of 88 articles met our inclusion criteria. Users were found to have diverse needs, preferences and uses for infectious disease visualization tools, and the existing tools are correspondingly diverse. The architecture of the tools was inconsistently described, and few tools in the review discussed the incorporation of usability studies or plans for dissemination. Many studies identified concerns regarding data sharing, confidentiality and quality. Existing tools offer a range of features and functions that allow users to explore, analyze, and visualize their data, but the tools are often for siloed applications. Commonly cited barriers to widespread adoption included lack of organizational support, access issues, and misconceptions about tool use. Discussion and Conclusion As the volume and complexity of infectious disease data increases, public health professionals must synthesize highly disparate data to facilitate communication with the public and inform decisions regarding measures to protect the public's health. Our review identified several themes: consideration of users' needs, preferences, and computer literacy; integration of tools into routine workflow; complications associated with understanding and use of visualizations; and the role of user trust and organizational support in the adoption of these tools. Interoperability also emerged as a prominent theme, highlighting challenges associated with the increasingly collaborative and interdisciplinary nature of infectious disease control and prevention. Future work should address methods for representing uncertainty and missing data to avoid misleading users as well as strategies to minimize cognitive overload. PMID:24747356
Visualization and analytics tools for infectious disease epidemiology: a systematic review.
Carroll, Lauren N; Au, Alan P; Detwiler, Landon Todd; Fu, Tsung-Chieh; Painter, Ian S; Abernethy, Neil F
2014-10-01
A myriad of new tools and algorithms have been developed to help public health professionals analyze and visualize the complex data used in infectious disease control. To better understand approaches to meet these users' information needs, we conducted a systematic literature review focused on the landscape of infectious disease visualization tools for public health professionals, with a special emphasis on geographic information systems (GIS), molecular epidemiology, and social network analysis. The objectives of this review are to: (1) identify public health user needs and preferences for infectious disease information visualization tools; (2) identify existing infectious disease information visualization tools and characterize their architecture and features; (3) identify commonalities among approaches applied to different data types; and (4) describe tool usability evaluation efforts and barriers to the adoption of such tools. We identified articles published in English from January 1, 1980 to June 30, 2013 from five bibliographic databases. Articles with a primary focus on infectious disease visualization tools, needs of public health users, or usability of information visualizations were included in the review. A total of 88 articles met our inclusion criteria. Users were found to have diverse needs, preferences and uses for infectious disease visualization tools, and the existing tools are correspondingly diverse. The architecture of the tools was inconsistently described, and few tools in the review discussed the incorporation of usability studies or plans for dissemination. Many studies identified concerns regarding data sharing, confidentiality and quality. Existing tools offer a range of features and functions that allow users to explore, analyze, and visualize their data, but the tools are often for siloed applications. Commonly cited barriers to widespread adoption included lack of organizational support, access issues, and misconceptions about tool use. As the volume and complexity of infectious disease data increases, public health professionals must synthesize highly disparate data to facilitate communication with the public and inform decisions regarding measures to protect the public's health. Our review identified several themes: consideration of users' needs, preferences, and computer literacy; integration of tools into routine workflow; complications associated with understanding and use of visualizations; and the role of user trust and organizational support in the adoption of these tools. Interoperability also emerged as a prominent theme, highlighting challenges associated with the increasingly collaborative and interdisciplinary nature of infectious disease control and prevention. Future work should address methods for representing uncertainty and missing data to avoid misleading users as well as strategies to minimize cognitive overload. Copyright © 2014 The Authors. Published by Elsevier Inc. All rights reserved.
Visual illusion of tool use recalibrates tactile perception
Miller, Luke E.; Longo, Matthew R.; Saygin, Ayse P.
2018-01-01
Brief use of a tool recalibrates multisensory representations of the user’s body, a phenomenon called tool embodiment. Despite two decades of research, little is known about its boundary conditions. It has been widely argued that embodiment requires active tool use, suggesting a critical role for somatosensory and motor feedback. The present study used a visual illusion to cast doubt on this view. We used a mirror-based setup to induce a visual experience of tool use with an arm that was in fact stationary. Following illusory tool use, tactile perception was recalibrated on this stationary arm, and with equal magnitude as physical use. Recalibration was not found following illusory passive tool holding, and could not be accounted for by sensory conflict or general interhemispheric plasticity. These results suggest visual tool-use signals play a critical role in driving tool embodiment. PMID:28196765
Slattery, Martha L.; Lundgreen, Abbie; Herrick, Jennifer S.; Wolff, Roger K.; Caan, Bette J.
2012-01-01
BACKGROUND The transforming growth factor-β (TGF-β) signaling pathway is involved in many aspects of tumori-genesis, including angiogenesis and metastasis. The authors evaluated this pathway in association with survival after a diagnosis of colon or rectal cancer. METHODS The study included 1553 patients with colon cancer and 754 patients with rectal cancer who had incident first primary disease and were followed for a minimum of 7 years after diagnosis. Genetic variations were evaluated in the genes TGF-β1 (2 single nucleotide polymorphisms [SNPs]), TGF-β receptor 1 (TGF-βR1) (3 SNPs), smooth muscle actin/mothers against decapentaplegic homolog 1 (Smad1) (5 SNPs), Smad2 (4 SNPs), Smad3 (37 SNPs), Smad4 (2 SNPs), Smad7 (11 SNPs), bone morphogenetic protein 1 (BMP1) (11 SNPs), BMP2 (5 SNPs), BMP4 (3 SNPs), bone morphogenetic protein receptor 1A (BMPR1A) (9 SNPs), BMPR1B (21 SNPs), BMPR2 (11 SNPs), growth differentiation factor 10 (GDF10) (7 SNPs), Runt-related transcription factor 1 (RUNX1) (40 SNPs), RUNX2 (19 SNPs), RUNX3 (9 SNPs), eukaryotic translation initiation factor 4E (eiF4E) (3 SNPs), eukaryotic translation initiation factor 4E-binding protein 3 (eiF4EBP2) (2 SNPs), eiF4EBP3 (2 SNPs), and mitogen-activated protein kinase 1 (MAPK1) (6 SNPs). RESULTS After adjusting for American Joint Committee on Cancer stage and tumor molecular phenotype, 12 genes and 18 SNPs were associated with survival in patients with colon cancer, and 7 genes and 15 tagSNPs were associated with survival after a diagnosis of rectal cancer. A summary score based on “at-risk” genotypes revealed a hazard rate ratio of 5.10 (95% confidence interval, 2.56-10.15) for the group with the greatest number of “at-risk” genotypes; for rectal cancer, the hazard rate ratio was 6.03 (95% confidence interval, 2.83-12.75). CONCLUSIONS The current findings suggest that the presence of several higher risk alleles in the TGF-β signaling pathway increase the likelihood of dying after a diagnosis of colon or rectal cancer. PMID:21365634
Pightling, Arthur W.; Petronella, Nicholas; Pagotto, Franco
2014-01-01
The wide availability of whole-genome sequencing (WGS) and an abundance of open-source software have made detection of single-nucleotide polymorphisms (SNPs) in bacterial genomes an increasingly accessible and effective tool for comparative analyses. Thus, ensuring that real nucleotide differences between genomes (i.e., true SNPs) are detected at high rates and that the influences of errors (such as false positive SNPs, ambiguously called sites, and gaps) are mitigated is of utmost importance. The choices researchers make regarding the generation and analysis of WGS data can greatly influence the accuracy of short-read sequence alignments and, therefore, the efficacy of such experiments. We studied the effects of some of these choices, including: i) depth of sequencing coverage, ii) choice of reference-guided short-read sequence assembler, iii) choice of reference genome, and iv) whether to perform read-quality filtering and trimming, on our ability to detect true SNPs and on the frequencies of errors. We performed benchmarking experiments, during which we assembled simulated and real Listeria monocytogenes strain 08-5578 short-read sequence datasets of varying quality with four commonly used assemblers (BWA, MOSAIK, Novoalign, and SMALT), using reference genomes of varying genetic distances, and with or without read pre-processing (i.e., quality filtering and trimming). We found that assemblies of at least 50-fold coverage provided the most accurate results. In addition, MOSAIK yielded the fewest errors when reads were aligned to a nearly identical reference genome, while using SMALT to align reads against a reference sequence that is ∼0.82% distant from 08-5578 at the nucleotide level resulted in the detection of the greatest numbers of true SNPs and the fewest errors. Finally, we show that whether read pre-processing improves SNP detection depends upon the choice of reference sequence and assembler. In total, this study demonstrates that researchers should test a variety of conditions to achieve optimal results. PMID:25144537
Kai, M; Nakata, N; Matsuoka, M; Sekizuka, T; Kuroda, M; Makino, M
2013-10-01
Genome analysis of Mycobacterium leprae strain Kyoto-2 in this study revealed characteristic nucleotide substitutions in gene ML0411, compared to the reference genome M. leprae strain TN. The ML0411 gene of Kyoto-2 had six SNPs compared to that of TN. All SNPs in ML0411 were non-synonymous mutations that result in amino acid replacements. In addition, a seventh SNP was found 41 bp upstream of the start codon in the regulatory region. The seven SNP sites in the ML0411 region were investigated by sequencing in 36 M. leprae isolates from the Leprosy Research Center in Japan. The SNP pattern in 14 of the 36 isolates showed similarity to that of Kyoto-2. Determination of the standard SNP types within the 36 stocked isolates revealed that almost all of the Japanese strains belonged to SNP type III, with nucleotide substitutions at position 14676, 164275, and 2935685 of the M. leprae TN genome. The geographical distribution pattern of east Asian M. leprae isolates by discrimination of ML0411 SNPs was investigated and interestingly turned out to be similar to that of tandem repeat numbers of GACATC in the rpoT gene (3 copies or 4 copies), which has been established as a tool for M. leprae genotyping. All seven Korean M. leprae isolates examined in this study, as well as those derived from Honshu Island of Japan, showed 4 copies of the 6-base tandem repeat plus the ML0411 SNPs observed in M. leprae Kyoto-2. They are termed Northeast Asian (NA) strain of M. leprae. On the other hand, many of isolates derived from the Okinawa Islands of Japan and from the Philippines showed 3 copies of the 6-base tandem repeat in addition to the M. leprae TN ML0411 type of SNPs. These results demonstrate the existence of M. leprae strains in Northeast Asian region having characteristic SNP patterns. Copyright © 2013 Elsevier B.V. All rights reserved.
Cericola, Fabio; Jahoor, Ahmed; Orabi, Jihad; Andersen, Jeppe R; Janss, Luc L; Jensen, Just
2017-01-01
Wheat breeding programs generate a large amount of variation which cannot be completely explored because of limited phenotyping throughput. Genomic prediction (GP) has been proposed as a new tool which provides breeding values estimations without the need of phenotyping all the material produced but only a subset of it named training population (TP). However, genotyping of all the accessions under analysis is needed and, therefore, optimizing TP dimension and genotyping strategy is pivotal to implement GP in commercial breeding schemes. Here, we explored the optimum TP size and we integrated pedigree records and genome wide association studies (GWAS) results to optimize the genotyping strategy. A total of 988 advanced wheat breeding lines were genotyped with the Illumina 15K SNPs wheat chip and phenotyped across several years and locations for yield, lodging, and starch content. Cross-validation using the largest possible TP size and all the SNPs available after editing (~11k), yielded predictive abilities (rGP) ranging between 0.5-0.6. In order to explore the Training population size, rGP were computed using progressively smaller TP. These exercises showed that TP of around 700 lines were enough to yield the highest observed rGP. Moreover, rGP were calculated by randomly reducing the SNPs number. This showed that around 1K markers were enough to reach the highest observed rGP. GWAS was used to identify markers associated with the traits analyzed. A GWAS-based selection of SNPs resulted in increased rGP when compared with random selection and few hundreds SNPs were sufficient to obtain the highest observed rGP. For each of these scenarios, advantages of adding the pedigree information were shown. Our results indicate that moderate TP sizes were enough to yield high rGP and that pedigree information and GWAS results can be used to greatly optimize the genotyping strategy.
A hidden two-locus disease association pattern in genome-wide association studies
2011-01-01
Background Recent association analyses in genome-wide association studies (GWAS) mainly focus on single-locus association tests (marginal tests) and two-locus interaction detections. These analysis methods have provided strong evidence of associations between genetics variances and complex diseases. However, there exists a type of association pattern, which often occurs within local regions in the genome and is unlikely to be detected by either marginal tests or interaction tests. This association pattern involves a group of correlated single-nucleotide polymorphisms (SNPs). The correlation among SNPs can lead to weak marginal effects and the interaction does not play a role in this association pattern. This phenomenon is due to the existence of unfaithfulness: the marginal effects of correlated SNPs do not express their significant joint effects faithfully due to the correlation cancelation. Results In this paper, we develop a computational method to detect this association pattern masked by unfaithfulness. We have applied our method to analyze seven data sets from the Wellcome Trust Case Control Consortium (WTCCC). The analysis for each data set takes about one week to finish the examination of all pairs of SNPs. Based on the empirical result of these real data, we show that this type of association masked by unfaithfulness widely exists in GWAS. Conclusions These newly identified associations enrich the discoveries of GWAS, which may provide new insights both in the analysis of tagSNPs and in the experiment design of GWAS. Since these associations may be easily missed by existing analysis tools, we can only connect some of them to publicly available findings from other association studies. As independent data set is limited at this moment, we also have difficulties to replicate these findings. More biological implications need further investigation. Availability The software is freely available at http://bioinformatics.ust.hk/hidden_pattern_finder.zip. PMID:21569557
Distefano, Gaetano; Caruso, Marco; La Malfa, Stefano; Gentile, Alessandra; Wu, Shu-Biao
2012-01-01
High resolution melting curve analysis (HRM) has been used as an efficient, accurate and cost-effective tool to detect single nucleotide polymorphisms (SNPs) or insertions or deletions (INDELs). However, its efficiency, accuracy and applicability to discriminate microsatellite polymorphism have not been extensively assessed. The traditional protocols used for SSR genotyping include PCR amplification of the DNA fragment and the separation of the fragments on electrophoresis-based platform. However, post-PCR handling processes are laborious and costly. Furthermore, SNPs present in the sequences flanking repeat motif cannot be detected by polyacrylamide-gel-electrophoresis based methods. In the present study, we compared the discriminating power of HRM with the traditional electrophoresis-based methods and provided a panel of primers for HRM genotyping in Citrus. The results showed that sixteen SSR markers produced distinct polymorphic melting curves among the Citrus spp investigated through HRM analysis. Among those, 10 showed more genotypes by HRM analysis than capillary electrophoresis owing to the presence of SNPs in the amplicons. For the SSR markers without SNPs present in the flanking region, HRM also gave distinct melting curves which detected same genotypes as were shown in capillary electrophoresis (CE) analysis. Moreover, HRM analysis allowed the discrimination of most of the 15 citrus genotypes and the resulting genetic distance analysis clustered them into three main branches. In conclusion, it has been approved that HRM is not only an efficient and cost-effective alternative of electrophoresis-based method for SSR markers, but also a method to uncover more polymorphisms contributed by SNPs present in SSRs. It was therefore suggested that the panel of SSR markers could be used in a variety of applications in the citrus biodiversity and breeding programs using HRM analysis. Furthermore, we speculate that the HRM analysis can be employed to analyse SSR markers in a wide range of applications in all other species.
2014-01-01
Background Grapevine (Vitis vinifera L.) is the most important Mediterranean fruit crop, used to produce both wine and spirits as well as table grape and raisins. Wine and table grape cultivars represent two divergent germplasm pools with different origins and domestication history, as well as differential characteristics for berry size, cluster architecture and berry chemical profile, among others. ‘Sultanina’ plays a pivotal role in modern table grape breeding providing the main source of seedlessness. This cultivar is also one of the most planted for fresh consumption and raisins production. Given its importance, we sequenced it and implemented a novel strategy for the de novo assembly of its highly heterozygous genome. Results Our approach produced a draft genome of 466 Mb, recovering 82% of the genes present in the grapevine reference genome; in addition, we identified 240 novel genes. A large number of structural variants and SNPs were identified. Among them, 45 (21 SNPs and 24 INDELs) were experimentally confirmed in ‘Sultanina’ and six SNPs in other 23 table grape varieties. Transposable elements corresponded to ca. 80% of the repetitive sequences involved in structural variants and more than 2,000 genes were affected in their structure by these variants. Some of these genes are likely involved in embryo development, suggesting that they may contribute to seedlessness, a key trait for table grapes. Conclusions This work produced the first structural variants and SNPs catalog for grapevine, constituting a novel and very powerful tool for genomic studies in this key fruit crop, particularly useful to support marker assisted breeding in table grapes. PMID:24397443
Javanrouh, Niloufar; Daneshpour, Maryam S; Soltanian, Ali Reza; Tapak, Leili
2018-06-05
Obesity is a serious health problem that leads to low quality of life and early mortality. To the purpose of prevention and gene therapy for such a worldwide disease, genome wide association study is a powerful tool for finding SNPs associated with increased risk of obesity. To conduct an association analysis, kernel machine regression is a generalized regression method, has an advantage of considering the epistasis effects as well as the correlation between individuals due to unknown factors. In this study, information of the people who participated in Tehran cardio-metabolic genetic study was used. They were genotyped for the chromosomal region, evaluation 986 variations located at 16q12.2; build 38hg. Kernel machine regression and single SNP analysis were used to assess the association between obesity and SNPs genotyped data. We found that associated SNP sets with obesity, were almost in the FTO (P = 0.01), AIKTIP (P = 0.02) and MMP2 (P = 0.02) genes. Moreover, two SNPs, i.e., rs10521296 and rs11647470, showed significant association with obesity using kernel regression (P = 0.02). In conclusion, significant sets were randomly distributed throughout the region with more density around the FTO, AIKTIP and MMP2 genes. Furthermore, two intergenic SNPs showed significant association after using kernel machine regression. Therefore, more studies have to be conducted to assess their functionality or precise mechanism. Copyright © 2018 Elsevier B.V. All rights reserved.
Screening methods for post-stroke visual impairment: a systematic review.
Hanna, Kerry Louise; Hepworth, Lauren Rachel; Rowe, Fiona
2017-12-01
To provide a systematic overview of the various tools available to screen for post-stroke visual impairment. A review of the literature was conducted including randomised controlled trials, controlled trials, cohort studies, observational studies, systematic reviews and retrospective medical note reviews. All languages were included and translation was obtained. Participants included adults ≥18 years old diagnosed with a visual impairment as a direct cause of a stroke. We searched a broad range of scholarly online resources and hand-searched articles registers of published, unpublished and on-going trials. Search terms included a variety of MESH terms and alternatives in relation to stroke and visual conditions. Study selection was performed by two authors independently. The quality of the evidence and risk of bias were assessed using the STROBE, GRACE and PRISMA statements. A total of 25 articles (n = 2924) were included in this review. Articles appraised reported on tools screening solely for visual impairments or for general post-stroke disabilities inclusive of vision. The majority of identified tools screen for visual perception including visual neglect (VN), with few screening for visual acuity (VA), visual field (VF) loss or ocular motility (OM) defects. Six articles reported on nine screening tools which combined visual screening assessment alongside screening for general stroke disabilities. Of these, three included screening for VA; three screened for VF loss; three screened for OM defects and all screened for VN. Two tools screened for all visual impairments. A further 19 articles were found which reported on individual vision screening tests in stroke populations; two for VF loss; 11 for VN and six for other visual perceptual defects. Most tools cannot accurately account for those with aphasia or communicative deficits, which are common problems following a stroke. There is currently no standardised visual screening tool which can accurately assess all potential post-stroke visual impairments. The current tools screen for only a number of potential stroke-related impairments, which means many visual defects may be missed. The sensitivity of those which screen for all impairments is significantly lowered when patients are unable to report their visual symptoms. Future research is required to develop a tool capable of assessing stroke patients which encompasses all potential visual deficits and can also be easily performed by both the patients and administered by health care professionals in order to ensure all stroke survivors with visual impairment are accurately identified and managed. Implications for Rehabilitation Over 65% of stroke survivors will suffer from a visual impairment, whereas 45% of stroke units do not assess vision. Visual impairment significantly reduces the quality of life, such as being unable to return to work, driving and depression. This review outlines the available screening methods to accurately identify stroke survivors with visual impairments. Identifying visual impairment after stroke can aid general rehabilitation and thus, improve the quality of life for these patients.
Learn to Teach Chemistry Using Visual Media Tools
ERIC Educational Resources Information Center
Turkoguz, Suat
2012-01-01
The aim of this study was to investigate undergraduate students' attitudes to using visual media tools in the chemistry laboratory. One hundred and fifteen undergraduates studying science education at Dokuz Eylul University, Turkey participated in the study. They video-recorded chemistry experiments with visual media tools and assessed them on a…
Stegemeier, John P; Colman, Benjamin P; Schwab, Fabienne; Wiesner, Mark R; Lowry, Gregory V
2017-05-02
Aquatic ecosystems are expected to receive Ag 0 and Ag 2 S nanoparticles (NPs) through anthropogenic waste streams. The speciation of silver in Ag-NPs affects their fate in ecosystems, but its influence on interactions with aquatic plants is still unclear. Here, the Ag speciation and distribution was measured in an aquatic plant, duckweed (Landoltia punctata), exposed to Ag 0 or Ag 2 S NPs, or to AgNO 3 . The silver distribution in duckweed roots was visualized using synchrotron-based micro X-ray fluorescence (XRF) mapping and Ag speciation was determined using extended X-ray absorption fine structure (EXAFS) spectroscopy. Duckweed exposed to Ag 2 S-NPs or Ag 0 -NPs accumulated similar Ag concentrations despite an order of magnitude smaller dissolved Ag fraction measured in the exposure medium for Ag 2 S-NPs compared to Ag 0 -NPs. By 24 h after exposure, all three forms of silver had accumulated on and partially in the roots regardless of the form of Ag exposed to the plants. Once associated with duckweed tissue, Ag 0 -NPs had transformed primarily into silver sulfide and silver thiol species. This suggests that plant defenses were active within or at the root surface. The Ag 2 S-NPs remained as Ag 2 S, while AgNO 3 exposure led to Ag 0 and sulfur-associated Ag species in plant tissue. Thus, regardless of initial speciation, Ag was readily available to duckweed.
Takajo, Ichiro; Yamada, Akiteru; Umeki, Kazumi; Saeki, Yuji; Hashikura, Yuuki; Yamamoto, Ikuo; Umekita, Kunihiko; Urayama-Kawano, Midori; Yamasaki, Shogo; Taniguchi, Takako; Misawa, Naoaki; Okayama, Akihiko
2018-01-01
Vibrio furnissii and V. fluvialis are closely related, the discrimination of which by conventional biochemical assay remains a challenge. Investigation of the sequence of the 16S rRNA genes in a clinical isolate of V. furnissii by visual inspection of a sequencing electropherogram revealed two sites of single-nucleotide polymorphisms (SNPs; positions 460 A/G and 1261 A/G) in these genes. A test of 12 strains each of V. fluvialis and V. furnissii revealed these SNPs to be common in V. furnissii but not in V. fluvialis. Divergence of SNP frequency was observed among the strains of V. furnissii tested. Because the SNPs described in V. furnissii produce a difference in the target sequence of restriction enzymes, a combination of polymerase chain reaction (PCR) of the 16S rRNA genes using conventional primers and restriction fragment length polymorphism analysis using Eco RV and Eae I was shown to discriminate between V. fluvialis and V. furnissii. This method is simple and alleviates the need for expensive equipment or primer sets specific to these bacteria. Therefore, we believe that this method can be useful, alongside specific PCR and mass spectrometry, when there is a need to discriminate between V. fluvialis and V. furnissii. Copyright © 2017 Elsevier B.V. All rights reserved.
Web-based visual analysis for high-throughput genomics
2013-01-01
Background Visualization plays an essential role in genomics research by making it possible to observe correlations and trends in large datasets as well as communicate findings to others. Visual analysis, which combines visualization with analysis tools to enable seamless use of both approaches for scientific investigation, offers a powerful method for performing complex genomic analyses. However, there are numerous challenges that arise when creating rich, interactive Web-based visualizations/visual analysis applications for high-throughput genomics. These challenges include managing data flow from Web server to Web browser, integrating analysis tools and visualizations, and sharing visualizations with colleagues. Results We have created a platform simplifies the creation of Web-based visualization/visual analysis applications for high-throughput genomics. This platform provides components that make it simple to efficiently query very large datasets, draw common representations of genomic data, integrate with analysis tools, and share or publish fully interactive visualizations. Using this platform, we have created a Circos-style genome-wide viewer, a generic scatter plot for correlation analysis, an interactive phylogenetic tree, a scalable genome browser for next-generation sequencing data, and an application for systematically exploring tool parameter spaces to find good parameter values. All visualizations are interactive and fully customizable. The platform is integrated with the Galaxy (http://galaxyproject.org) genomics workbench, making it easy to integrate new visual applications into Galaxy. Conclusions Visualization and visual analysis play an important role in high-throughput genomics experiments, and approaches are needed to make it easier to create applications for these activities. Our framework provides a foundation for creating Web-based visualizations and integrating them into Galaxy. Finally, the visualizations we have created using the framework are useful tools for high-throughput genomics experiments. PMID:23758618
Gori, Simone; Molteni, Massimo; Facoetti, Andrea
2016-01-01
A visual illusion refers to a percept that is different in some aspect from the physical stimulus. Illusions are a powerful non-invasive tool for understanding the neurobiology of vision, telling us, indirectly, how the brain processes visual stimuli. There are some neurodevelopmental disorders characterized by visual deficits. Surprisingly, just a few studies investigated illusory perception in clinical populations. Our aim is to review the literature supporting a possible role for visual illusions in helping us understand the visual deficits in developmental dyslexia and autism spectrum disorder. Future studies could develop new tools – based on visual illusions – to identify an early risk for neurodevelopmental disorders. PMID:27199702
Cruz, Vanessa P; Vera, Manuel; Pardo, Belén G; Taggart, John; Martinez, Paulino; Oliveira, Claudio; Foresti, Fausto
2017-05-01
Single nucleotide polymorphism (SNP) markers were identified and validated for two stingrays species, Potamotrygon motoro and Potamotrygon falkneri, using double digest restriction-site associated DNA (ddRAD) reads using 454-Roche technology. A total of 226 774 reads (65.5 Mb) were obtained (mean read length 289 ± 183 bp) detecting a total of 5399 contigs (mean contig length: 396 ± 91 bp). Mining this data set, a panel of 143 in silico SNPs was selected. Eighty-two of these SNPs were successfully validated and 61 were polymorphic: 14 in P. falkneri, 21 in P. motoro, 3 in both species and 26 fixed for alternative variants in both species, thus being useful for population analyses and hybrid detection. © 2016 John Wiley & Sons Ltd.
DOE Office of Scientific and Technical Information (OSTI.GOV)
With the flood of whole genome finished and draft microbial sequences, we need faster, more scalable bioinformatics tools for sequence comparison. An algorithm is described to find single nucleotide polymorphisms (SNPs) in whole genome data. It scales to hundreds of bacterial or viral genomes, and can be used for finished and/or draft genomes available as unassembled contigs or raw, unassembled reads. The method is fast to compute, finding SNPs and building a SNP phylogeny in minutes to hours, depending on the size and diversity of the input sequences. The SNP-based trees that result are consistent with known taxonomy and treesmore » determined in other studies. The approach we describe can handle many gigabases of sequence in a single run. The algorithm is based on k-mer analysis.« less
Southam, Lorraine; Panoutsopoulou, Kalliope; Rayner, N William; Chapman, Kay; Durrant, Caroline; Ferreira, Teresa; Arden, Nigel; Carr, Andrew; Deloukas, Panos; Doherty, Michael; Loughlin, John; McCaskie, Andrew; Ollier, William E R; Ralston, Stuart; Spector, Timothy D; Valdes, Ana M; Wallis, Gillian A; Wilkinson, J Mark; Marchini, Jonathan; Zeggini, Eleftheria
2011-05-01
Imputation is an extremely valuable tool in conducting and synthesising genome-wide association studies (GWASs). Directly typed SNP quality control (QC) is thought to affect imputation quality. It is, therefore, common practise to use quality-controlled (QCed) data as an input for imputing genotypes. This study aims to determine the effect of commonly applied QC steps on imputation outcomes. We performed several iterations of imputing SNPs across chromosome 22 in a dataset consisting of 3177 samples with Illumina 610 k (Illumina, San Diego, CA, USA) GWAS data, applying different QC steps each time. The imputed genotypes were compared with the directly typed genotypes. In addition, we investigated the correlation between alternatively QCed data. We also applied a series of post-imputation QC steps balancing elimination of poorly imputed SNPs and information loss. We found that the difference between the unQCed data and the fully QCed data on imputation outcome was minimal. Our study shows that imputation of common variants is generally very accurate and robust to GWAS QC, which is not a major factor affecting imputation outcome. A minority of common-frequency SNPs with particular properties cannot be accurately imputed regardless of QC stringency. These findings may not generalise to the imputation of low frequency and rare variants.
Brief Overview of a Decade of Genome-Wide Association Studies on Primary Hypertension.
Azam, Afifah Binti; Azizan, Elena Aisha Binti
2018-01-01
Primary hypertension is widely believed to be a complex polygenic disorder with the manifestation influenced by the interactions of genomic and environmental factors making identification of susceptibility genes a major challenge. With major advancement in high-throughput genotyping technology, genome-wide association study (GWAS) has become a powerful tool for researchers studying genetically complex diseases. GWASs work through revealing links between DNA sequence variation and a disease or trait with biomedical importance. The human genome is a very long DNA sequence which consists of billions of nucleotides arranged in a unique way. A single base-pair change in the DNA sequence is known as a single nucleotide polymorphism (SNP). With the help of modern genotyping techniques such as chip-based genotyping arrays, thousands of SNPs can be genotyped easily. Large-scale GWASs, in which more than half a million of common SNPs are genotyped and analyzed for disease association in hundreds of thousands of cases and controls, have been broadly successful in identifying SNPs associated with heart diseases, diabetes, autoimmune diseases, and psychiatric disorders. It is however still debatable whether GWAS is the best approach for hypertension. The following is a brief overview on the outcomes of a decade of GWASs on primary hypertension.
Tzvetkov, Mladen V; Becker, Christian; Kulle, Bettina; Nürnberg, Peter; Brockmöller, Jürgen; Wojnowski, Leszek
2005-02-01
Whole-genome DNA amplification by multiple displacement (MD-WGA) is a promising tool to obtain sufficient DNA amounts from samples of limited quantity. Using Affymetrix' GeneChip Human Mapping 10K Arrays, we investigated the accuracy and allele amplification bias in DNA samples subjected to MD-WGA. We observed an excellent concordance (99.95%) between single-nucleotide polymorphisms (SNPs) called both in the nonamplified and the corresponding amplified DNA. This concordance was only 0.01% lower than the intra-assay reproducibility of the genotyping technique used. However, MD-WGA failed to amplify an estimated 7% of polymorphic loci. Due to the algorithm used to call genotypes, this was detected only for heterozygous loci. We achieved a 4.3-fold reduction of noncalled SNPs by combining the results from two independent MD-WGA reactions. This indicated that inter-reaction variations rather than specific chromosomal loci reduced the efficiency of MD-WGA. Consistently, we detected no regions of reduced amplification, with the exception of several SNPs located near chromosomal ends. Altogether, despite a substantial loss of polymorphic sites, MD-WGA appears to be the current method of choice to amplify genomic DNA for array-based SNP analyses. The number of nonamplified loci can be substantially reduced by amplifying each DNA sample in duplicate.
Zhang, Han; Wheeler, William; Song, Lei; Yu, Kai
2017-07-07
As meta-analysis results published by consortia of genome-wide association studies (GWASs) become increasingly available, many association summary statistics-based multi-locus tests have been developed to jointly evaluate multiple single-nucleotide polymorphisms (SNPs) to reveal novel genetic architectures of various complex traits. The validity of these approaches relies on the accurate estimate of z-score correlations at considered SNPs, which in turn requires knowledge on the set of SNPs assessed by each study participating in the meta-analysis. However, this exact SNP coverage information is usually unavailable from the meta-analysis results published by GWAS consortia. In the absence of the coverage information, researchers typically estimate the z-score correlations by making oversimplified coverage assumptions. We show through real studies that such a practice can generate highly inflated type I errors, and we demonstrate the proper way to incorporate correct coverage information into multi-locus analyses. We advocate that consortia should make SNP coverage information available when posting their meta-analysis results, and that investigators who develop analytic tools for joint analyses based on summary data should pay attention to the variation in SNP coverage and adjust for it appropriately. Published by Oxford University Press 2017. This work is written by US Government employees and is in the public domain in the US.
Rapid ABO genotyping by high-speed droplet allele-specific PCR using crude samples.
Taira, Chiaki; Matsuda, Kazuyuki; Takeichi, Naoya; Furukawa, Satomi; Sugano, Mitsutoshi; Uehara, Takeshi; Okumura, Nobuo; Honda, Takayuki
2018-01-01
ABO genotyping has common tools for personal identification of forensic and transplantation field. We developed a new method based on a droplet allele-specific PCR (droplet-AS-PCR) that enabled rapid PCR amplification. We attempted rapid ABO genotyping using crude DNA isolated from dried blood and buccal cells. We designed allele-specific primers for three SNPs (at nucleotides 261, 526, and 803) in exons 6 and 7 of the ABO gene. We pretreated dried blood and buccal cells with proteinase K, and obtained crude DNAs without DNA purification. Droplet-AS-PCR allowed specific amplification of the SNPs at the three loci using crude DNA, with results similar to those for DNA extracted from fresh peripheral blood. The sensitivity of the methods was 5%-10%. The genotyping of extracted DNA and crude DNA were completed within 8 and 9 minutes, respectively. The genotypes determined by the droplet-AS-PCR method were always consistent with those obtained by direct sequencing. The droplet-AS-PCR method enabled rapid and specific amplification of three SNPs of the ABO gene from crude DNA treated with proteinase K. ABO genotyping by the droplet-AS-PCR has the potential to be applied to various fields including a forensic medicine and transplantation medical care. © 2017 Wiley Periodicals, Inc.
Ma, Li; Runesha, H Birali; Dvorkin, Daniel; Garbe, John R; Da, Yang
2008-01-01
Background Genome-wide association studies (GWAS) using single nucleotide polymorphism (SNP) markers provide opportunities to detect epistatic SNPs associated with quantitative traits and to detect the exact mode of an epistasis effect. Computational difficulty is the main bottleneck for epistasis testing in large scale GWAS. Results The EPISNPmpi and EPISNP computer programs were developed for testing single-locus and epistatic SNP effects on quantitative traits in GWAS, including tests of three single-locus effects for each SNP (SNP genotypic effect, additive and dominance effects) and five epistasis effects for each pair of SNPs (two-locus interaction, additive × additive, additive × dominance, dominance × additive, and dominance × dominance) based on the extended Kempthorne model. EPISNPmpi is the parallel computing program for epistasis testing in large scale GWAS and achieved excellent scalability for large scale analysis and portability for various parallel computing platforms. EPISNP is the serial computing program based on the EPISNPmpi code for epistasis testing in small scale GWAS using commonly available operating systems and computer hardware. Three serial computing utility programs were developed for graphical viewing of test results and epistasis networks, and for estimating CPU time and disk space requirements. Conclusion The EPISNPmpi parallel computing program provides an effective computing tool for epistasis testing in large scale GWAS, and the epiSNP serial computing programs are convenient tools for epistasis analysis in small scale GWAS using commonly available computer hardware. PMID:18644146
Caucasian Families Exhibit Significant Linkage of Myopia to Chromosome 11p.
Musolf, Anthony M; Simpson, Claire L; Moiz, Bilal A; Long, Kyle A; Portas, Laura; Murgia, Federico; Ciner, Elise B; Stambolian, Dwight; Bailey-Wilson, Joan E
2017-07-01
Myopia is a common visual disorder caused by eye overgrowth, resulting in blurry vision. It affects one in four Americans, and its prevalence is increasing. The genetic mechanisms that underpin myopia are not completely understood. Here, we use genotype data and linkage analyses to identify high-risk genetic loci that are significantly linked to myopia. Individuals from 56 Caucasian families with a history of myopia were genotyped on an exome-based array, and the single nucleotide polymorphism (SNP) data were merged with microsatellite genotype data. Refractive error measures on the samples were converted into binary phenotypes consisting of affected, unaffected, or unknown myopia status. Parametric linkage analyses assuming an autosomal dominant model with 90% penetrance and 10% phenocopy rate were performed. Single variant two-point analyses yielded three significantly linked SNPs at 11p14.1 and 11p11.2; a further 45 SNPs at 11p were found to be suggestive. No other chromosome had any significant SNPs or more than seven suggestive linkages. Two of the significant SNPs were located in BBOX1-AS1 and one in the intergenic region between ORA47 and TRIM49B. Collapsed haplotype pattern two-point analysis and multipoint analyses also yielded multiple suggestively linked genes at 11p. Multipoint analysis also identified suggestive evidence of linkage on 20q13. We identified three genome-wide significant linked variants on 11p for myopia in Caucasians. Although the novel specific signals still need to be replicated, 11p is a promising region that has been identified by other linkage studies with a number of potentially interesting candidate genes. We hope that the identification of these regions on 11p as potential causal regions for myopia will lead to more focus on these regions and maybe possible replication of our specific linkage peaks in other studies. We further plan targeted sequencing on 11p for our most highly linked families to more clearly understand the source of the linkage in this region.
Qiu, Jingya; Moore, Jason H; Darabos, Christian
2016-05-01
Genome-wide association studies (GWAS) have led to the discovery of over 200 single nucleotide polymorphisms (SNPs) associated with type 2 diabetes mellitus (T2DM). Additionally, East Asians develop T2DM at a higher rate, younger age, and lower body mass index than their European ancestry counterparts. The reason behind this occurrence remains elusive. With comprehensive searches through the National Human Genome Research Institute (NHGRI) GWAS catalog literature, we compiled a database of 2,800 ancestry-specific SNPs associated with T2DM and 70 other related traits. Manual data extraction was necessary because the GWAS catalog reports statistics such as odds ratio and P-value, but does not consistently include ancestry information. Currently, many statistics are derived by combining initial and replication samples from study populations of mixed ancestry. Analysis of all-inclusive data can be misleading, as not all SNPs are transferable across diverse populations. We used ancestry data to construct ancestry-specific human phenotype networks (HPN) centered on T2DM. Quantitative and visual analysis of network models reveal the genetic disparities between ancestry groups. Of the 27 phenotypes in the East Asian HPN, six phenotypes were unique to the network, revealing the underlying ancestry-specific nature of some SNPs associated with T2DM. We studied the relationship between T2DM and five phenotypes unique to the East Asian HPN to generate new interaction hypotheses in a clinical context. The genetic differences found in our ancestry-specific HPNs suggest different pathways are involved in the pathogenesis of T2DM among different populations. Our study underlines the importance of ancestry in the development of T2DM and its implications in pharmocogenetics and personalized medicine. © 2016 The Authors. *Genetic Epidemiology Published by Wiley Periodicals, Inc.
Dötsch, Annika; Eisele, Lewin; Rabeling, Miriam; Rump, Katharina; Walstein, Kai; Bick, Alexandra; Cox, Linda; Engler, Andrea; Bachmann, Hagen S; Jöckel, Karl-Heinz; Adamzik, Michael; Peters, Jürgen; Schäfer, Simon T
2017-06-14
Hypoxia-inducible-factor-2α (HIF-2α) and HIF-2 degrading prolyl-hydroxylases (PHD) are key regulators of adaptive hypoxic responses i.e., in acute respiratory distress syndrome (ARDS). Specifically, functionally active genetic variants of HIF-2α (single nucleotide polymorphism (SNP) [ch2:46441523(hg18)]) and PHD2 (C/T; SNP rs516651 and T/C; SNP rs480902) are associated with improved adaptation to hypoxia i.e., in high-altitude residents. However, little is known about these SNPs' prevalence in Caucasians and impact on ARDS-outcome. Thus, we tested the hypotheses that in Caucasian ARDS patients SNPs in HIF-2α or PHD2 genes are (1) common, and (2) independent risk factors for 30-day mortality. After ethics-committee approval, 272 ARDS patients were prospectively included, genotyped for PHD2 (Taqman SNP Genotyping Assay) and HIF-2α -polymorphism (restriction digest + agarose-gel visualization), and genotype dependent 30-day mortality was analyzed using Kaplan-Meier-plots and multivariate Cox-regression analyses. Frequencies were 99.62% for homozygous HIF-2α CC-carriers (CG: 0.38%; GG: 0%), 2.3% for homozygous PHD2 SNP rs516651 TT-carriers (CT: 18.9%; CC: 78.8%), and 3.7% for homozygous PHD2 SNP rs480902 TT-carriers (CT: 43.9%; CC: 52.4%). PHD2 rs516651 TT-genotype in ARDS was independently associated with a 3.34 times greater mortality risk (OR 3.34, CI 1.09-10.22; p = 0.034) within 30-days, whereas the other SNPs had no significant impact ( p = ns). The homozygous HIF-2α GG-genotype was not present in our Caucasian ARDS cohort; however PHD2 SNPs exist in Caucasians, and PHD2 rs516651 TT-genotype was associated with an increased 30-day mortality suggesting a relevance for adaptive responses in ARDS.
ERIC Educational Resources Information Center
Ecoma, Victor
2016-01-01
The paper reflects upon the tools, approaches and applications of visual literacy in the Visual Arts Department of Cross River University of Technology, Calabar, Nigeria. The objective of the discourse is to examine how the visual arts training and practice equip students with skills in visual literacy through methods of production, materials and…
Linear reduction method for predictive and informative tag SNP selection.
He, Jingwu; Westbrooks, Kelly; Zelikovsky, Alexander
2005-01-01
Constructing a complete human haplotype map is helpful when associating complex diseases with their related SNPs. Unfortunately, the number of SNPs is very large and it is costly to sequence many individuals. Therefore, it is desirable to reduce the number of SNPs that should be sequenced to a small number of informative representatives called tag SNPs. In this paper, we propose a new linear algebra-based method for selecting and using tag SNPs. We measure the quality of our tag SNP selection algorithm by comparing actual SNPs with SNPs predicted from selected linearly independent tag SNPs. Our experiments show that for sufficiently long haplotypes, knowing only 0.4% of all SNPs the proposed linear reduction method predicts an unknown haplotype with the error rate below 2% based on 10% of the population.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Banerjee, Poulabi; Bahlo, Melanie; Schwartz, Jody R.
2002-01-01
Genome wide disease association analysis using SNPs is being explored as a method for dissecting complex genetic traits and a vast number of SNPs have been generated for this purpose. As there are cost and throughput limitations of genotyping large numbers of SNPs and statistical issues regarding the large number of dependent tests on the same data set, to make association analysis practical it has been proposed that SNPs should be prioritized based on likely functional importance. The most easily identifiable functional SNPs are coding SNPs (cSNPs) and accordingly cSNPs have been screened in a number of studies. SNPs inmore » gene regulatory sequences embedded in noncoding DNA are another class of SNPs suggested for prioritization due to their predicted quantitative impact on gene expression. The main challenge in evaluating these SNPs, in contrast to cSNPs is a lack of robust algorithms and databases for recognizing regulatory sequences in noncoding DNA. Approaches that have been previously used to delineate noncoding sequences with gene regulatory activity include cross-species sequence comparisons and the search for sequences recognized by transcription factors. We combined these two methods to sift through mouse human genomic sequences to identify putative gene regulatory elements and subsequently localized SNPs within these sequences in a 1 Megabase (Mb) region of human chromosome 5q31, orthologous to mouse chromosome 11 containing the Interleukin cluster.« less
van Eck, Herman J; Vos, Peter G; Valkonen, Jari P T; Uitdewilligen, Jan G A M L; Lensing, Hellen; de Vetten, Nick; Visser, Richard G F
2017-03-01
The method of graphical genotyping is applied to a panel of tetraploid potato cultivars to visualize haplotype sharing. The method allowed to map genes involved in virus and nematode resistance. The physical coordinates of the amount of linkage drag surrounding these genes are easily interpretable. Graphical genotyping is a visually attractive and easily interpretable method to represent genetic marker data. In this paper, the method is extended from diploids to a panel of tetraploid potato cultivars. Application of filters to select a subset of SNPs allows one to visualize haplotype sharing between individuals that also share a specific locus. The method is illustrated with cultivars resistant to Potato virus Y (PVY), while simultaneously selecting for the absence of the SNPs in susceptible clones. SNP data will then merge into an image which displays the coordinates of a distal genomic region on the northern arm of chromosome 11 where a specific haplotype is introgressed from the wild potato species S. stoloniferum (CPC 2093) carrying a gene (Ny (o,n)sto ) conferring resistance to two PVY strains, PVY O and PVY NTN . Graphical genotyping was also successful in showing the haplotypes on chromosome 12 carrying Ry-f sto , another resistance gene derived from S. stoloniferum conferring broad-spectrum resistance to PVY, as well as chromosome 5 haplotypes from S. vernei, with the Gpa5 locus involved in resistance against Globodera pallida cyst nematodes. The image also shows shortening of linkage drag by meiotic recombination of the introgression segment in more recent breeding material. Identity-by-descent was found to be a requirement for using graphical genotyping, which is proposed as a non-statistical alternative method for gene discovery, as compared with genome-wide association studies. The potential and limitations of the method are discussed.
Model-Based Reasoning: Using Visual Tools to Reveal Student Learning
ERIC Educational Resources Information Center
Luckie, Douglas; Harrison, Scott H.; Ebert-May, Diane
2011-01-01
Using visual models is common in science and should become more common in classrooms. Our research group has developed and completed studies on the use of a visual modeling tool, the Concept Connector. This modeling tool consists of an online concept mapping Java applet that has automatic scoring functions we refer to as Robograder. The Concept…
A Visual Training Tool for Teaching Kanji to Children with Developmental Dyslexia
ERIC Educational Resources Information Center
Ikeshita-Yamazoe, Hanae; Miyao, Masutomo
2016-01-01
We developed a visual training tool to assist children with developmental dyslexia in learning to recognize and understand Chinese characters (kanji). The visual training tool presents the strokes of a kanji character as separate shapes and requires students to use these fragments to construct the character. Two types of experiments were conducted…
An Exploratory Study of Interactivity in Visualization Tools: "Flow" of Interaction
ERIC Educational Resources Information Center
Liang, Hai-Ning; Parsons, Paul C.; Wu, Hsien-Chi; Sedig, Kamran
2010-01-01
This paper deals with the design of interactivity in visualization tools. There are several factors that can be used to guide the analysis and design of the interactivity of these tools. One such factor is flow, which is concerned with the duration of interaction with visual representations of information--interaction being the actions performed…
AR4VI: AR as an Accessibility Tool for People with Visual Impairments
Coughlan, James M.; Miele, Joshua
2017-01-01
Although AR technology has been largely dominated by visual media, a number of AR tools using both visual and auditory feedback have been developed specifically to assist people with low vision or blindness – an application domain that we term Augmented Reality for Visual Impairment (AR4VI). We describe two AR4VI tools developed at Smith-Kettlewell, as well as a number of pre-existing examples. We emphasize that AR4VI is a powerful tool with the potential to remove or significantly reduce a range of accessibility barriers. Rather than being restricted to use by people with visual impairments, AR4VI is a compelling universal design approach offering benefits for mainstream applications as well. PMID:29303163
AR4VI: AR as an Accessibility Tool for People with Visual Impairments.
Coughlan, James M; Miele, Joshua
2017-10-01
Although AR technology has been largely dominated by visual media, a number of AR tools using both visual and auditory feedback have been developed specifically to assist people with low vision or blindness - an application domain that we term Augmented Reality for Visual Impairment (AR4VI). We describe two AR4VI tools developed at Smith-Kettlewell, as well as a number of pre-existing examples. We emphasize that AR4VI is a powerful tool with the potential to remove or significantly reduce a range of accessibility barriers. Rather than being restricted to use by people with visual impairments, AR4VI is a compelling universal design approach offering benefits for mainstream applications as well.
Abdulkadir, Mohamed; Londono, Douglas; Gordon, Derek; Fernandez, Thomas V; Brown, Lawrence W; Cheon, Keun-Ah; Coffey, Barbara J; Elzerman, Lonneke; Fremer, Carolin; Fründt, Odette; Garcia-Delgar, Blanca; Gilbert, Donald L; Grice, Dorothy E; Hedderly, Tammy; Heyman, Isobel; Hong, Hyun Ju; Huyser, Chaim; Ibanez-Gomez, Laura; Jakubovski, Ewgeni; Kim, Young Key; Kim, Young Shin; Koh, Yun-Joo; Kook, Sodahm; Kuperman, Samuel; Leventhal, Bennett; Ludolph, Andrea G; Madruga-Garrido, Marcos; Maras, Athanasios; Mir, Pablo; Morer, Astrid; Müller-Vahl, Kirsten; Münchau, Alexander; Murphy, Tara L; Plessen, Kerstin J; Roessner, Veit; Shin, Eun-Young; Song, Dong-Ho; Song, Jungeun; Tübing, Jennifer; van den Ban, Els; Visscher, Frank; Wanderer, Sina; Woods, Martin; Zinner, Samuel H; King, Robert A; Tischfield, Jay A; Heiman, Gary A; Hoekstra, Pieter J; Dietrich, Andrea
2018-04-01
Genetic studies in Tourette syndrome (TS) are characterized by scattered and poorly replicated findings. We aimed to replicate findings from candidate gene and genome-wide association studies (GWAS). Our cohort included 465 probands with chronic tic disorder (93% TS) and both parents from 412 families (some probands were siblings). We assessed 75 single nucleotide polymorphisms (SNPs) in 465 parent-child trios; 117 additional SNPs in 211 trios; and 4 additional SNPs in 254 trios. We performed SNP and gene-based transmission disequilibrium tests and compared nominally significant SNP results with those from a large independent case-control cohort. After quality control 71 SNPs were available in 371 trios; 112 SNPs in 179 trios; and 3 SNPs in 192 trios. 17 were candidate SNPs implicated in TS and 2 were implicated in obsessive-compulsive disorder (OCD) or autism spectrum disorder (ASD); 142 were tagging SNPs from eight monoamine neurotransmitter-related genes (including dopamine and serotonin); 10 were top SNPs from TS GWAS; and 13 top SNPs from attention-deficit/hyperactivity disorder, OCD, or ASD GWAS. None of the SNPs or genes reached significance after adjustment for multiple testing. We observed nominal significance for the candidate SNPs rs3744161 (TBCD) and rs4565946 (TPH2) and for five tagging SNPs; none of these showed significance in the independent cohort. Also, SLC1A1 in our gene-based analysis and two TS GWAS SNPs showed nominal significance, rs11603305 (intergenic) and rs621942 (PICALM). We found no convincing support for previously implicated genetic polymorphisms. Targeted re-sequencing should fully appreciate the relevance of candidate genes.
Sinha, Siddharth; Verma, Sharad; Singh, Aditi; Somvanshi, Pallavi; Grover, Abhinav
2018-01-01
Spinocerebellar degeneration, termed as ataxia is a neurological disorder of central nervous system, characterized by limb in-coordination and a progressive gait. The patient also demonstrates specific symptoms of muscle weakness, slurring of speech, and decreased vibration senses. Expansion of polyglutamine trinucleotide (CAG) within ATXN2 gene with 35 or more repeats, results in spinocerebellar ataxia type-2. Protein ataxin-2 coded by ATXN2 gene has been reported to have a crucial role in translation of the genetic information through sequestering the histone acetyl transferases (HAT) resulting in a state of hypo-acetylation. In the present study, we have evaluated the outcome for 122 non synonymous single nucleotide polymorphisms (nsSNPs) reported within ATXN2 gene through computational tools such as SIFT, PolyPhen 2.0, PANTHER, I-mutant 2.0, Phd-SNP, Pmut, MutPred. The apo and mutant (L305V and Q339L) form of structures for the ataxin-2 protein were modeled for gaining insights toward 3D spatial arrangement. Further, molecular dynamics simulations and structural analysis were performed to observe the brunt of disease associated nsSNPs toward the strength and secondary properties of ataxin-2 protein structure. Our results showed that, L305V is a highly deleterious and disease causing point substitution. Analysis based on RMSD, RMSF, Rg, SASA, number of hydrogen bonds (NH bonds), covariance matrix trace, projection analysis for eigen vector demonstrated a significant instability and conformation along with rise in mutant flexibility values in comparison to the apo form of ataxin-2 protein. The study provides a blue print of computational methodologies to examine the ataxin-blend SNPs. J. Cell. Biochem. 119: 499-510, 2018. © 2017 Wiley Periodicals, Inc. © 2017 Wiley Periodicals, Inc.
Söderqvist, Stina; Matsson, Hans; Peyrard-Janvid, Myriam; Kere, Juha; Klingberg, Torkel
2014-01-01
Studying the effects of cognitive training can lead to finding better treatments, but it can also be a tool for investigating factors important for brain plasticity and acquisition of cognitive skills. In this study, we investigated how single-nucleotide polymorphisms (SNPs) and ratings of intrinsic motivation were associated to interindividual differences in improvement during working memory training. The study included 256 children aged 7-19 years who were genotyped for 13 SNPs within or near eight candidate genes previously implicated in learning: COMT, SLC6A3 (DAT1), DRD4, DRD2, PPP1R1B (DARPP32), MAOA, LMX1A, and BDNF. Ratings on the intrinsic motivation inventory were also available for 156 of these children. All participants performed at least 20 sessions of working memory training, and performance during the training was logged and used as the outcome variable. We found that two SNPs, rs1800497 and rs2283265, located near and within the dopamine receptor 2 (DRD2) gene, respectively, were significantly associated with improvements during training (p < .003 and p < .0004, respectively). Scores from a questionnaire regarding intrinsic motivation did not correlate with training outcome. However, we observed both the main effect of genotype at those two loci as well as the interaction between genotypes and ratings of intrinsic motivation (perceived competence). Both SNPs have previously been shown to affect DRD2 receptor density primarily in the BG. Our results suggest that genetic variation is accounting for some interindividual differences in how children acquire cognitive skills and that part of this effect is also seen on intrinsic motivation. Moreover, they suggest that dopamine D2 transmission in the BG is a key factor for cognitive plasticity.
Effect of read-mapping biases on detecting allele-specific expression from RNA-sequencing data
Degner, Jacob F.; Marioni, John C.; Pai, Athma A.; Pickrell, Joseph K.; Nkadori, Everlyne; Gilad, Yoav; Pritchard, Jonathan K.
2009-01-01
Motivation: Next-generation sequencing has become an important tool for genome-wide quantification of DNA and RNA. However, a major technical hurdle lies in the need to map short sequence reads back to their correct locations in a reference genome. Here, we investigate the impact of SNP variation on the reliability of read-mapping in the context of detecting allele-specific expression (ASE). Results: We generated 16 million 35 bp reads from mRNA of each of two HapMap Yoruba individuals. When we mapped these reads to the human genome we found that, at heterozygous SNPs, there was a significant bias toward higher mapping rates of the allele in the reference sequence, compared with the alternative allele. Masking known SNP positions in the genome sequence eliminated the reference bias but, surprisingly, did not lead to more reliable results overall. We find that even after masking, ∼5–10% of SNPs still have an inherent bias toward more effective mapping of one allele. Filtering out inherently biased SNPs removes 40% of the top signals of ASE. The remaining SNPs showing ASE are enriched in genes previously known to harbor cis-regulatory variation or known to show uniparental imprinting. Our results have implications for a variety of applications involving detection of alternate alleles from short-read sequence data. Availability: Scripts, written in Perl and R, for simulating short reads, masking SNP variation in a reference genome and analyzing the simulation output are available upon request from JFD. Raw short read data were deposited in GEO (http://www.ncbi.nlm.nih.gov/geo/) under accession number GSE18156. Contact: jdegner@uchicago.edu; marioni@uchicago.edu; gilad@uchicago.edu; pritch@uchicago.edu Supplementary information: Supplementary data are available at Bioinformatics online. PMID:19808877
Improved Genetic Profiling of Anthropometric Traits Using a Big Data Approach.
Canela-Xandri, Oriol; Rawlik, Konrad; Woolliams, John A; Tenesa, Albert
2016-01-01
Genome-wide association studies (GWAS) promised to translate their findings into clinically beneficial improvements of patient management by tailoring disease management to the individual through the prediction of disease risk. However, the ability to translate genetic findings from GWAS into predictive tools that are of clinical utility and which may inform clinical practice has, so far, been encouraging but limited. Here we propose to use a more powerful statistical approach, the use of which has traditionally been limited due to computational requirements and lack of sufficiently large individual level genotyped cohorts, but which improve the prediction of multiple medically relevant phenotypes using the same panel of SNPs. As a proof of principle, we used a shared panel of 319,038 common SNPs with MAF > 0.05 to train the prediction models in 114,264 unrelated White-British individuals for height and four obesity related traits (body mass index, basal metabolic rate, body fat percentage, and waist-to-hip ratio). We obtained prediction accuracies that ranged between 46% and 75% of the maximum achievable given the captured heritable component. For height, this represents an improvement in prediction accuracy of up to 68% (184% more phenotypic variance explained) over SNPs reported to be robustly associated with height in a previous GWAS meta-analysis of similar size. Across-population predictions in White non-British individuals were similar to those in White-British whilst those in Asian and Black individuals were informative but less accurate. We estimate that the genotyping of circa 500,000 unrelated individuals will yield predictions between 66% and 82% of the SNP-heritability captured by common variants in our array. Prediction accuracies did not improve when including rarer SNPs or when fitting multiple traits jointly in multivariate models.
Compression and fast retrieval of SNP data.
Sambo, Francesco; Di Camillo, Barbara; Toffolo, Gianna; Cobelli, Claudio
2014-11-01
The increasing interest in rare genetic variants and epistatic genetic effects on complex phenotypic traits is currently pushing genome-wide association study design towards datasets of increasing size, both in the number of studied subjects and in the number of genotyped single nucleotide polymorphisms (SNPs). This, in turn, is leading to a compelling need for new methods for compression and fast retrieval of SNP data. We present a novel algorithm and file format for compressing and retrieving SNP data, specifically designed for large-scale association studies. Our algorithm is based on two main ideas: (i) compress linkage disequilibrium blocks in terms of differences with a reference SNP and (ii) compress reference SNPs exploiting information on their call rate and minor allele frequency. Tested on two SNP datasets and compared with several state-of-the-art software tools, our compression algorithm is shown to be competitive in terms of compression rate and to outperform all tools in terms of time to load compressed data. Our compression and decompression algorithms are implemented in a C++ library, are released under the GNU General Public License and are freely downloadable from http://www.dei.unipd.it/~sambofra/snpack.html. © The Author 2014. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.
Compression and fast retrieval of SNP data
Sambo, Francesco; Di Camillo, Barbara; Toffolo, Gianna; Cobelli, Claudio
2014-01-01
Motivation: The increasing interest in rare genetic variants and epistatic genetic effects on complex phenotypic traits is currently pushing genome-wide association study design towards datasets of increasing size, both in the number of studied subjects and in the number of genotyped single nucleotide polymorphisms (SNPs). This, in turn, is leading to a compelling need for new methods for compression and fast retrieval of SNP data. Results: We present a novel algorithm and file format for compressing and retrieving SNP data, specifically designed for large-scale association studies. Our algorithm is based on two main ideas: (i) compress linkage disequilibrium blocks in terms of differences with a reference SNP and (ii) compress reference SNPs exploiting information on their call rate and minor allele frequency. Tested on two SNP datasets and compared with several state-of-the-art software tools, our compression algorithm is shown to be competitive in terms of compression rate and to outperform all tools in terms of time to load compressed data. Availability and implementation: Our compression and decompression algorithms are implemented in a C++ library, are released under the GNU General Public License and are freely downloadable from http://www.dei.unipd.it/~sambofra/snpack.html. Contact: sambofra@dei.unipd.it or cobelli@dei.unipd.it. PMID:25064564
Experiences in using DISCUS for visualizing human communication
NASA Astrophysics Data System (ADS)
Groehn, Matti; Nieminen, Marko; Haho, Paeivi; Smeds, Riitta
2000-02-01
In this paper, we present further improvement to the DISCUS software that can be used to record and analyze the flow and constants of business process simulation session discussion. The tool was initially introduced in 'visual data exploration and analysis IV' conference. The initial features of the tool enabled the visualization of discussion flow in business process simulation sessions and the creation of SOM analyses. The improvements of the tool consists of additional visualization possibilities that enable quick on-line analyses and improved graphical statistics. We have also created the very first interface to audio data and implemented two ways to visualize it. We also outline additional possibilities to use the tool in other application areas: these include usability testing and the possibility to use the tool for capturing design rationale in a product development process. The data gathered with DISCUS may be used in other applications, and further work may be done with data ming techniques.
Ambroise, Jérôme; Butoescu, Valentina; Robert, Annie; Tombal, Bertrand; Gala, Jean-Luc
2015-06-25
Single Nucleotide Polymorphisms (SNPs) identified in Genome Wide Association Studies (GWAS) have generally moderate association with related complex diseases. Accordingly, Multilocus Genetic Risk Scores (MGRSs) have been computed in previous studies in order to assess the cumulative association of multiple SNPs. When several SNPs have to be genotyped for each patient, using successive uniplex pyrosequencing reactions increases analytical reagent expenses and Turnaround Time (TAT). While a set of several pyrosequencing primers could theoretically be used to analyze multiplex amplicons, this would generate overlapping primer-specific pyro-signals that are visually uninterpretable. In the current study, two multiplex assays were developed consisting of a quadruplex (n=4) and a quintuplex (n=5) polymerase chain reaction (PCR) each followed by multiplex pyrosequencing analysis. The aim was to reliably but rapidly genotype a set of prostate cancer-related SNPs (n=9). The nucleotide dispensation order was selected using SENATOR software. Multiplex pyro-signals were analyzed using the new AdvISER-MH-PYRO software based on a sparse representation of the signal. Using uniplex assays as gold standard, the concordance between multiplex and uniplex assays was assessed on DNA extracted from patient blood samples (n = 10). All genotypes (n=90) generated with the quadruplex and the quintuplex pyroquencing assays were perfectly (100 %) concordant with uniplex pyrosequencing. Using multiplex genotyping approach for analyzing a set of 90 patients allowed reducing TAT by approximately 75 % (i.e., from 2025 to 470 min) while reducing reagent consumption and cost by approximately 70 % (i.e., from ~229 US$ /patient to ~64 US$ /patient). This combination of quadruplex and quintuplex pyrosequencing and PCR assays enabled to reduce the amount of DNA required for multi-SNP analysis, and to lower the global TAT and costs of SNP genotyping while providing results as reliable as uniplex analysis. Using this combined multiplex approach also substantially reduced the production of waste material. These genotyping assays appear therefore to be biologically, economically and ecologically highly relevant, being worth to be integrated in genetic-based predictive strategies for better selecting patients at risk for prostate cancer. In addition, the same approach could now equally be transposed to other clinical/research applications relying on the computation of MGRS based on multi-SNP genotyping.
Abedi, Farshad; Wickremasinghe, Sanjeewa; Richardson, Andrea J; Islam, Amirul F M; Guymer, Robyn H; Baird, Paul N
2013-08-01
To determine the association of genetic variants in known age-related macular degeneration (AMD) risk-associated genes with outcome of anti-vascular endothelial growth factor (VEGF) treatment in neovascular AMD. Prospective cohort study. We enrolled 224 consecutive patients with neovascular AMD at the Royal Victorian Eye and Ear Hospital, Australia. Patients were treated with 3 initial monthly ranibizumab or bevacizumab injections followed by 9 months of "as required" injections based on clinician's decision at each follow-up visit according to retreatment criteria. Seventeen single nucleotide polymorphisms (SNPs) in known AMD risk-associated genes including CFH (rs800292, rs3766404, rs1061170, rs2274700 and rs393955), HTRA1 (rs11200638), CFHR1-5 (rs10922153, rs16840639, rs6667243, and rs1853883), LOC387715/ARMS2 (rs3793917 and rs10490924), C3 (rs2230199 and rs1047286), C2 (rs547154), CFB (rs641153) and F13B (rs6003) were examined. Multivariate analysis was used to determine the role of each SNP in treatment outcome. The influence of selected SNPs on mean change in visual acuity (VA) at 12 months. Mean baseline VA was 51 ± 16.8 Early Treatment Diabetic Retinopathy Study letters. Overall, the mean change in VA from baseline was +3.2 ± 14.9 letters at 12 months. The AA (homozygote risk) genotype at rs11200638 - HTRA1 promoter SNP (P = 0.001) and GG (homozygote risk) genotype at rs10490924 (A69S) in LOC387715/ARMS2 (P = 0.002) were each significantly associated with poorer VA outcome at 12 months after multiple correction. Mean ± standard deviation change in VA from baseline in patients with AA genotype at rs11200638 was -2.9 ± 15.2 letters after 12 months compared with +5.1 ± 14.1 letters in patients with AG or GG genotypes at this SNP. Patients with either of these genotypes were also significantly more likely to lose >15 letters after 12 months. SNPs rs11200638 and rs10490924 were in high linkage disequilibrium (r(2) = 0.92). None of the other examined SNPs was associated with outcome. The HTRA1 promoter SNP (rs11200638) and A69S at LOC387715/ARMS2 were associated with a poorer visual outcome for ranibizumab or bevacizumab treatment in neovascular AMD, suggesting strong pharmacogenetic associations with anti-VEGF treatment. This finding could aid in applying more individualized treatment regimens based on patients' genotype to achieve optimal treatment response in AMD. The authors have no proprietary or commercial interest in any materials discussed in this article. Copyright © 2013 American Academy of Ophthalmology. Published by Elsevier Inc. All rights reserved.
LS-SNP: large-scale annotation of coding non-synonymous SNPs based on multiple information sources.
Karchin, Rachel; Diekhans, Mark; Kelly, Libusha; Thomas, Daryl J; Pieper, Ursula; Eswar, Narayanan; Haussler, David; Sali, Andrej
2005-06-15
The NCBI dbSNP database lists over 9 million single nucleotide polymorphisms (SNPs) in the human genome, but currently contains limited annotation information. SNPs that result in amino acid residue changes (nsSNPs) are of critical importance in variation between individuals, including disease and drug sensitivity. We have developed LS-SNP, a genomic scale software pipeline to annotate nsSNPs. LS-SNP comprehensively maps nsSNPs onto protein sequences, functional pathways and comparative protein structure models, and predicts positions where nsSNPs destabilize proteins, interfere with the formation of domain-domain interfaces, have an effect on protein-ligand binding or severely impact human health. It currently annotates 28,043 validated SNPs that produce amino acid residue substitutions in human proteins from the SwissProt/TrEMBL database. Annotations can be viewed via a web interface either in the context of a genomic region or by selecting sets of SNPs, genes, proteins or pathways. These results are useful for identifying candidate functional SNPs within a gene, haplotype or pathway and in probing molecular mechanisms responsible for functional impacts of nsSNPs. http://www.salilab.org/LS-SNP CONTACT: rachelk@salilab.org http://salilab.org/LS-SNP/supp-info.pdf.
Data Visualization Saliency Model: A Tool for Evaluating Abstract Data Visualizations
Matzen, Laura E.; Haass, Michael J.; Divis, Kristin M.; ...
2017-08-29
Evaluating the effectiveness of data visualizations is a challenging undertaking and often relies on one-off studies that test a visualization in the context of one specific task. Researchers across the fields of data science, visualization, and human-computer interaction are calling for foundational tools and principles that could be applied to assessing the effectiveness of data visualizations in a more rapid and generalizable manner. One possibility for such a tool is a model of visual saliency for data visualizations. Visual saliency models are typically based on the properties of the human visual cortex and predict which areas of a scene havemore » visual features (e.g. color, luminance, edges) that are likely to draw a viewer's attention. While these models can accurately predict where viewers will look in a natural scene, they typically do not perform well for abstract data visualizations. In this paper, we discuss the reasons for the poor performance of existing saliency models when applied to data visualizations. We introduce the Data Visualization Saliency (DVS) model, a saliency model tailored to address some of these weaknesses, and we test the performance of the DVS model and existing saliency models by comparing the saliency maps produced by the models to eye tracking data obtained from human viewers. In conclusion, we describe how modified saliency models could be used as general tools for assessing the effectiveness of visualizations, including the strengths and weaknesses of this approach.« less
Data Visualization Saliency Model: A Tool for Evaluating Abstract Data Visualizations
DOE Office of Scientific and Technical Information (OSTI.GOV)
Matzen, Laura E.; Haass, Michael J.; Divis, Kristin M.
Evaluating the effectiveness of data visualizations is a challenging undertaking and often relies on one-off studies that test a visualization in the context of one specific task. Researchers across the fields of data science, visualization, and human-computer interaction are calling for foundational tools and principles that could be applied to assessing the effectiveness of data visualizations in a more rapid and generalizable manner. One possibility for such a tool is a model of visual saliency for data visualizations. Visual saliency models are typically based on the properties of the human visual cortex and predict which areas of a scene havemore » visual features (e.g. color, luminance, edges) that are likely to draw a viewer's attention. While these models can accurately predict where viewers will look in a natural scene, they typically do not perform well for abstract data visualizations. In this paper, we discuss the reasons for the poor performance of existing saliency models when applied to data visualizations. We introduce the Data Visualization Saliency (DVS) model, a saliency model tailored to address some of these weaknesses, and we test the performance of the DVS model and existing saliency models by comparing the saliency maps produced by the models to eye tracking data obtained from human viewers. In conclusion, we describe how modified saliency models could be used as general tools for assessing the effectiveness of visualizations, including the strengths and weaknesses of this approach.« less
The 3D widgets for exploratory scientific visualization
NASA Technical Reports Server (NTRS)
Herndon, Kenneth P.; Meyer, Tom
1995-01-01
Computational fluid dynamics (CFD) techniques are used to simulate flows of fluids like air or water around such objects as airplanes and automobiles. These techniques usually generate very large amounts of numerical data which are difficult to understand without using graphical scientific visualization techniques. There are a number of commercial scientific visualization applications available today which allow scientists to control visualization tools via textual and/or 2D user interfaces. However, these user interfaces are often difficult to use. We believe that 3D direct-manipulation techniques for interactively controlling visualization tools will provide opportunities for powerful and useful interfaces with which scientists can more effectively explore their datasets. A few systems have been developed which use these techniques. In this paper, we will present a variety of 3D interaction techniques for manipulating parameters of visualization tools used to explore CFD datasets, and discuss in detail various techniques for positioning tools in a 3D scene.
Survey of Network Visualization Tools
2007-12-01
Dimensionality • 2D Comments: Deployment Type: • Components for tool building • Standalone Tool OS: • Windows Extensibility • ActiveX ...Visual Basic Comments: Interoperability Daisy is fully compliant with Microsoft’s ActiveX , therefore, other Windows based programs can...other functions that improve analytic decision making. Available in ActiveX , C++, Java, and .NET editions. • Tom Sawyer Visualization: Enables you to
Goyal, Anupama A; Tur, Komalpreet; Mann, Jason; Townsend, Whitney; Flanders, Scott A; Chopra, Vineet
2017-11-01
Although common, the impact of low-cost bedside visual tools, such as whiteboards, on patient care is unclear. To systematically review the literature and assess the influence of bedside visual tools on patient satisfaction. Medline, Embase, SCOPUS, Web of Science, CINAHL, and CENTRAL. Studies of adult or pediatric hospitalized patients reporting physician identification, understanding of provider roles, patient-provider communication, and satisfaction with care from the use of visual tools were included. Outcomes were categorized as positive, negative, or neutral based on survey responses for identification, communication, and satisfaction. Two reviewers screened studies, extracted data, and assessed the risk of study bias. Sixteen studies met the inclusion criteria. Visual tools included whiteboards (n = 4), physician pictures (n = 7), whiteboard and picture (n = 1), electronic medical record-based patient portals (n = 3), and formatted notepads (n = 1). Tools improved patients' identification of providers (13/13 studies). The impact on understanding the providers' roles was largely positive (8/10 studies). Visual tools improved patient-provider communication (4/5 studies) and satisfaction (6/8 studies). In adults, satisfaction varied between positive with the use of whiteboards (2/5 studies) and neutral with pictures (1/5 studies). Satisfaction related to pictures in pediatric patients was either positive (1/3 studies) or neutral (1/3 studies). Differences in tool format (individual pictures vs handouts with pictures of all providers) and study design (randomized vs cohort) may explain variable outcomes. The use of bedside visual tools appears to improve patient recognition of providers and patient-provider communication. Future studies that include better design and outcome assessment are necessary before widespread use can be recommended. © 2017 Society of Hospital Medicine
Visual Impairment Screening Assessment (VISA) tool: pilot validation.
Rowe, Fiona J; Hepworth, Lauren R; Hanna, Kerry L; Howard, Claire
2018-03-06
To report and evaluate a new Vision Impairment Screening Assessment (VISA) tool intended for use by the stroke team to improve identification of visual impairment in stroke survivors. Prospective case cohort comparative study. Stroke units at two secondary care hospitals and one tertiary centre. 116 stroke survivors were screened, 62 by naïve and 54 by non-naïve screeners. Both the VISA screening tool and the comprehensive specialist vision assessment measured case history, visual acuity, eye alignment, eye movements, visual field and visual inattention. Full completion of VISA tool and specialist vision assessment was achieved for 89 stroke survivors. Missing data for one or more sections typically related to patient's inability to complete the assessment. Sensitivity and specificity of the VISA screening tool were 90.24% and 85.29%, respectively; the positive and negative predictive values were 93.67% and 78.36%, respectively. Overall agreement was significant; k=0.736. Lowest agreement was found for screening of eye movement and visual inattention deficits. This early validation of the VISA screening tool shows promise in improving detection accuracy for clinicians involved in stroke care who are not specialists in vision problems and lack formal eye training, with potential to lead to more prompt referral with fewer false positives and negatives. Pilot validation indicates acceptability of the VISA tool for screening of visual impairment in stroke survivors. Sensitivity and specificity were high indicating the potential accuracy of the VISA tool for screening purposes. Results of this study have guided the revision of the VISA screening tool ahead of full clinical validation. © Article author(s) (or their employer(s) unless otherwise stated in the text of the article) 2018. All rights reserved. No commercial use is permitted unless otherwise expressly granted.
Audio-video decision support for patients: the documentary genré as a basis for decision aids.
Volandes, Angelo E; Barry, Michael J; Wood, Fiona; Elwyn, Glyn
2013-09-01
Decision support tools are increasingly using audio-visual materials. However, disagreement exists about the use of audio-visual materials as they may be subjective and biased. This is a literature review of the major texts for documentary film studies to extrapolate issues of objectivity and bias from film to decision support tools. The key features of documentary films are that they attempt to portray real events and that the attempted reality is always filtered through the lens of the filmmaker. The same key features can be said of decision support tools that use audio-visual materials. Three concerns arising from documentary film studies as they apply to the use of audio-visual materials in decision support tools include whose perspective matters (stakeholder bias), how to choose among audio-visual materials (selection bias) and how to ensure objectivity (editorial bias). Decision science needs to start a debate about how audio-visual materials are to be used in decision support tools. Simply because audio-visual materials may be subjective and open to bias does not mean that we should not use them. Methods need to be found to ensure consensus around balance and editorial control, such that audio-visual materials can be used. © 2011 John Wiley & Sons Ltd.
Audio‐video decision support for patients: the documentary genré as a basis for decision aids
Volandes, Angelo E.; Barry, Michael J.; Wood, Fiona; Elwyn, Glyn
2011-01-01
Abstract Objective Decision support tools are increasingly using audio‐visual materials. However, disagreement exists about the use of audio‐visual materials as they may be subjective and biased. Methods This is a literature review of the major texts for documentary film studies to extrapolate issues of objectivity and bias from film to decision support tools. Results The key features of documentary films are that they attempt to portray real events and that the attempted reality is always filtered through the lens of the filmmaker. The same key features can be said of decision support tools that use audio‐visual materials. Three concerns arising from documentary film studies as they apply to the use of audio‐visual materials in decision support tools include whose perspective matters (stakeholder bias), how to choose among audio‐visual materials (selection bias) and how to ensure objectivity (editorial bias). Discussion Decision science needs to start a debate about how audio‐visual materials are to be used in decision support tools. Simply because audio‐visual materials may be subjective and open to bias does not mean that we should not use them. Conclusion Methods need to be found to ensure consensus around balance and editorial control, such that audio‐visual materials can be used. PMID:22032516
The Visual Geophysical Exploration Environment: A Multi-dimensional Scientific Visualization
NASA Astrophysics Data System (ADS)
Pandya, R. E.; Domenico, B.; Murray, D.; Marlino, M. R.
2003-12-01
The Visual Geophysical Exploration Environment (VGEE) is an online learning environment designed to help undergraduate students understand fundamental Earth system science concepts. The guiding principle of the VGEE is the importance of hands-on interaction with scientific visualization and data. The VGEE consists of four elements: 1) an online, inquiry-based curriculum for guiding student exploration; 2) a suite of El Nino-related data sets adapted for student use; 3) a learner-centered interface to a scientific visualization tool; and 4) a set of concept models (interactive tools that help students understand fundamental scientific concepts). There are two key innovations featured in this interactive poster session. One is the integration of concept models and the visualization tool. Concept models are simple, interactive, Java-based illustrations of fundamental physical principles. We developed eight concept models and integrated them into the visualization tool to enable students to probe data. The ability to probe data using a concept model addresses the common problem of transfer: the difficulty students have in applying theoretical knowledge to everyday phenomenon. The other innovation is a visualization environment and data that are discoverable in digital libraries, and installed, configured, and used for investigations over the web. By collaborating with the Integrated Data Viewer developers, we were able to embed a web-launchable visualization tool and access to distributed data sets into the online curricula. The Thematic Real-time Environmental Data Distributed Services (THREDDS) project is working to provide catalogs of datasets that can be used in new VGEE curricula under development. By cataloging this curricula in the Digital Library for Earth System Education (DLESE), learners and educators can discover the data and visualization tool within a framework that guides their use.
Experience Report: Visual Programming in the Real World
NASA Technical Reports Server (NTRS)
Baroth, E.; Hartsough, C
1994-01-01
This paper reports direct experience with two commercial, widely used visual programming environments. While neither of these systems is object oriented, the tools have transformed the development process and indicate a direction for visual object oriented tools to proceed.
Al-Tobasei, Rafet; Ali, Ali; Leeds, Timothy D; Liu, Sixin; Palti, Yniv; Kenney, Brett; Salem, Mohamed
2017-08-07
Coding/functional SNPs change the biological function of a gene and, therefore, could serve as "large-effect" genetic markers. In this study, we used two bioinformatics pipelines, GATK and SAMtools, for discovering coding/functional SNPs with allelic-imbalances associated with total body weight, muscle yield, muscle fat content, shear force, and whiteness. Phenotypic data were collected for approximately 500 fish, representing 98 families (5 fish/family), from a growth-selected line, and the muscle transcriptome was sequenced from 22 families with divergent phenotypes (4 low- versus 4 high-ranked families per trait). GATK detected 59,112 putative SNPs; of these SNPs, 4798 showed allelic imbalances (>2.0 as an amplification and <0.5 as loss of heterozygosity). SAMtools detected 87,066 putative SNPs; and of them, 4962 had allelic imbalances between the low- and high-ranked families. Only 1829 SNPs with allelic imbalances were common between the two datasets, indicating significant differences in algorithms. The two datasets contained 7930 non-redundant SNPs of which 4439 mapped to 1498 protein-coding genes (with 6.4% non-synonymous SNPs) and 684 mapped to 295 lncRNAs. Validation of a subset of 92 SNPs revealed 1) 86.7-93.8% success rate in calling polymorphic SNPs and 2) 95.4% consistent matching between DNA and cDNA genotypes indicating a high rate of identifying SNPs with allelic imbalances. In addition, 4.64% SNPs revealed random monoallelic expression. Genome distribution of the SNPs with allelic imbalances exhibited high density for all five traits in several chromosomes, especially chromosome 9, 20 and 28. Most of the SNP-harboring genes were assigned to important growth-related metabolic pathways. These results demonstrate utility of RNA-Seq in assessing phenotype-associated allelic imbalances in pooled RNA-Seq samples. The SNPs identified in this study were included in a new SNP-Chip design (available from Affymetrix) for genomic and genetic analyses in rainbow trout.
ERIC Educational Resources Information Center
Liang, Hai-Ning; Sedig, Kamran
2010-01-01
Many students find it difficult to engage with mathematical concepts. As a relatively new class of learning tools, visualization tools may be able to promote higher levels of engagement with mathematical concepts. Often, development of new tools may outpace empirical evaluations of the effectiveness of these tools, especially in educational…
Rapid analysis of colipase gene variants by multicapillary electrophoresis.
Jaczó, Zsuzsanna; Pál, Eszter; Dénes, Réka; Somogyi, Anikó; Sasvári-Székely, Mária; Guttman, András; Rónai, Zsolt
2015-06-01
Despite of the fact that the Human Genome Project was completed more than a decade ago, identification of the genetic background of polygenic diseases is still challenging. Several somewhat different approaches are available to investigate inheritable factors of complex phenotypes, all require, however efficient, high-throughput techniques for SNP genotyping. In this paper, we report a robust and reliable multiplex PCR-RFLP for genotype and haplotype analysis of six SNPs (rs41270082, rs3748051, rs142027015, rs3748048, rs73404011, and rs72925892) of the colipase (CLPS) gene. A multicapillary (12 capillaries) electrophoresis unit was used for high throughput and sensitive analysis of the digestion fragments. A Microsoft Excel-based spreadsheet was designed for the flexible visualization and evaluation of the electrophoretic separations, which is readily adaptable for any kind of electrophoresis application. Haplotype analysis of the two loci localized in close proximity of each other was carried out by molecular method, extended haplotypes including all five SNPs in the 5' upstream region were calculated. The techniques were applied in a case-control association study of type 2 diabetes mellitus. Although, single marker analysis did not reveal any significant association, it was observed that the rare GGCCG haplotype of the five 5' upstream region SNPs was about three times more frequent among patients compared to healthy control population. Our results demonstrated the applicability of multicapillary CGE in large-scale, high-throughput SNP analysis, and suggested that the CLPS gene polymorphisms might be considered as genetic risk factor for type 2 diabetes mellitus. © 2014 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.
Boulling, Arnaud; Masson, Emmanuelle; Zou, Wen-Bin; Paliwal, Sumit; Wu, Hao; Issarapu, Prachand; Bhaskar, Seema; Génin, Emmanuelle; Cooper, David N; Li, Zhao-Shen; Chandak, Giriraj R; Liao, Zhuan; Chen, Jian-Min; Férec, Claude
2017-08-01
The haplotype harboring the SPINK1 c.101A>G (p.Asn34Ser) variant (also known as rs17107315:T>C) represents the most important heritable risk factor for idiopathic chronic pancreatitis identified to date. The causal variant contained within this risk haplotype has however remained stubbornly elusive. Herein, we set out to resolve this enigma by employing a hypothesis-driven approach. First, we searched for variants in strong linkage disequilibrium (LD) with rs17107315:T>C using HaploReg v4.1. Second, we identified two candidate SNPs by visual inspection of sequences spanning all 25 SNPs found to be in LD with rs17107315:T>C, guided by prior knowledge of pancreas-specific transcription factors and their cognate binding sites. Third, employing a novel cis-regulatory module (CRM)-guided approach to further filter the two candidate SNPs yielded a solitary candidate causal variant. Finally, combining data from phylogenetic conservation and chromatin accessibility, cotransfection transactivation experiments, and population genetic studies, we suggest that rs142703147:C>A, which disrupts a PTF1L-binding site within an evolutionarily conserved HNF1A-PTF1L CRM located ∼4 kb upstream of the SPINK1 promoter, contributes to the aforementioned chronic pancreatitis risk haplotype. Further studies are required not only to improve the characterization of this functional SNP but also to identify other functional components that might contribute to this high-risk haplotype. © 2017 Wiley Periodicals, Inc.
Nagaie, Satoshi; Ogishima, Soichi; Nakaya, Jun; Tanaka, Hiroshi
2015-01-01
Genome-wide association studies (GWAS) and linkage analysis has identified many single nucleotide polymorphisms (SNPs) related to disease. There are many unknown SNPs whose minor allele frequencies (MAFs) as low as 0.005 having intermediate effects with odds ratio between 1.5~3.0. Low frequency variants having intermediate effects on disease pathogenesis are believed to have complex interactions with environmental factors called gene-environment interactions (GxE). Hence, we describe a model using 3D Manhattan plot called GxE landscape plot to visualize the association of p-values for gene-environment interactions (GxE). We used the Gene-Environment iNteraction Simulator 2 (GENS2) program to simulate interactions between two genetic loci and one environmental factor in this exercise. The dataset used for training contains disease status, gender, 20 environmental exposures and 100 genotypes for 170 subjects, and p-values were calculated by Cochran-Mantel-Haenszel chi-squared test on known data. Subsequently, we created a 3D GxE landscape plot of negative logarithm of the association of p-values for all the possible combinations of genetic and environmental factors with their hierarchical clustering. Thus, the GxE landscape plot is a valuable model to predict association of p-values for GxE and similarity among genotypes and environments in the context of disease pathogenesis. GxE - Gene-environment interactions, GWAS - Genome-wide association study, MAFs - Minor allele frequencies, SNPs - Single nucleotide polymorphisms, EWAS - Environment-wide association study, FDR - False discovery rate, JPT+CHB - HapMap population of Japanese in Tokyo, Japan - Han Chinese in Beijing.
Got Graphs? An Assessment of Data Visualization Tools
NASA Technical Reports Server (NTRS)
Schaefer, C. M.; Foy, M.
2015-01-01
Graphs are powerful tools for simplifying complex data. They are useful for quickly assessing patterns and relationships among one or more variables from a dataset. As the amount of data increases, it becomes more difficult to visualize potential associations. Lifetime Surveillance of Astronaut Health (LSAH) was charged with assessing its current visualization tools along with others on the market to determine whether new tools would be useful for supporting NASA's occupational surveillance effort. It was concluded by members of LSAH that the current tools hindered their ability to provide quick results to researchers working with the department. Due to the high volume of data requests and the many iterations of visualizations requested by researchers, software with a better ability to replicate graphs and edit quickly could improve LSAH's efficiency and lead to faster research results.
Using component technologies for web based wavelet enhanced mammographic image visualization.
Sakellaropoulos, P; Costaridou, L; Panayiotakis, G
2000-01-01
The poor contrast detectability of mammography can be dealt with by domain specific software visualization tools. Remote desktop client access and time performance limitations of a previously reported visualization tool are addressed, aiming at more efficient visualization of mammographic image resources existing in web or PACS image servers. This effort is also motivated by the fact that at present, web browsers do not support domain-specific medical image visualization. To deal with desktop client access the tool was redesigned by exploring component technologies, enabling the integration of stand alone domain specific mammographic image functionality in a web browsing environment (web adaptation). The integration method is based on ActiveX Document Server technology. ActiveX Document is a part of Object Linking and Embedding (OLE) extensible systems object technology, offering new services in existing applications. The standard DICOM 3.0 part 10 compatible image-format specification Papyrus 3.0 is supported, in addition to standard digitization formats such as TIFF. The visualization functionality of the tool has been enhanced by including a fast wavelet transform implementation, which allows for real time wavelet based contrast enhancement and denoising operations. Initial use of the tool with mammograms of various breast structures demonstrated its potential in improving visualization of diagnostic mammographic features. Web adaptation and real time wavelet processing enhance the potential of the previously reported tool in remote diagnosis and education in mammography.
Tools for visually exploring biological networks.
Suderman, Matthew; Hallett, Michael
2007-10-15
Many tools exist for visually exploring biological networks including well-known examples such as Cytoscape, VisANT, Pathway Studio and Patika. These systems play a key role in the development of integrative biology, systems biology and integrative bioinformatics. The trend in the development of these tools is to go beyond 'static' representations of cellular state, towards a more dynamic model of cellular processes through the incorporation of gene expression data, subcellular localization information and time-dependent behavior. We provide a comprehensive review of the relative advantages and disadvantages of existing systems with two goals in mind: to aid researchers in efficiently identifying the appropriate existing tools for data visualization; to describe the necessary and realistic goals for the next generation of visualization tools. In view of the first goal, we provide in the Supplementary Material a systematic comparison of more than 35 existing tools in terms of over 25 different features. Supplementary data are available at Bioinformatics online.
Visual quality assessment of alternative silvicultural practices in upland hardwood management
Tim McDonald; Bryce Stokes
1997-01-01
Visual impacts of forest operations are of increasing concern to forest managers. Tools are available for evaluating, and potentially avoiding, problems in visual quality resulting from poorly designed harvest unit boundaries. One of these visualization tools is applied in comparing various harvest unit shape alternatives in an upland hardwood stand on steeply sloping...
Application of Frameworks in the Analysis and (Re)design of Interactive Visual Learning Tools
ERIC Educational Resources Information Center
Liang, Hai-Ning; Sedig, Kamran
2009-01-01
Interactive visual learning tools (IVLTs) are software environments that encode and display information visually and allow learners to interact with the visual information. This article examines the application and utility of frameworks in the analysis and design of IVLTs at the micro level. Frameworks play an important role in any design. They…
Examining Chemistry Students Visual-Perceptual Skills Using the VSCS Tool and Interview Data
ERIC Educational Resources Information Center
Christian, Caroline
2010-01-01
The Visual-Spatial Chemistry Specific (VSCS) assessment tool was developed to test students' visual-perceptual skills, which are required to form a mental image of an object. The VSCS was designed around the theoretical framework of Rochford and Archer that provides eight distinct and well-defined visual-perceptual skills with identified problems…
Yates, Christopher M; Sternberg, Michael J E
2013-11-01
Non-synonymous single nucleotide polymorphisms (nsSNPs) are single base changes leading to a change to the amino acid sequence of the encoded protein. Many of these variants are associated with disease, so nsSNPs have been well studied, with studies looking at the effects of nsSNPs on individual proteins, for example, on stability and enzyme active sites. In recent years, the impact of nsSNPs upon protein-protein interactions has also been investigated, giving a greater insight into the mechanisms by which nsSNPs can lead to disease. In this review, we summarize these studies, looking at the various mechanisms by which nsSNPs can affect protein-protein interactions. We focus on structural changes that can impair interaction, changes to disorder, gain of interaction, and post-translational modifications before looking at some examples of nsSNPs at human-pathogen protein-protein interfaces and the analysis of nsSNPs from a network perspective. © 2013.
Bianco, Luca; Cestaro, Alessandro; Sargent, Daniel James; Banchi, Elisa; Derdak, Sophia; Di Guardo, Mario; Salvi, Silvio; Jansen, Johannes; Viola, Roberto; Gut, Ivo; Laurens, Francois; Chagné, David; Velasco, Riccardo; van de Weg, Eric; Troggio, Michela
2014-01-01
High-density SNP arrays for genome-wide assessment of allelic variation have made high resolution genetic characterization of crop germplasm feasible. A medium density array for apple, the IRSC 8K SNP array, has been successfully developed and used for screens of bi-parental populations. However, the number of robust and well-distributed markers contained on this array was not sufficient to perform genome-wide association analyses in wider germplasm sets, or Pedigree-Based Analysis at high precision, because of rapid decay of linkage disequilibrium. We describe the development of an Illumina Infinium array targeting 20K SNPs. The SNPs were predicted from re-sequencing data derived from the genomes of 13 Malus × domestica apple cultivars and one accession belonging to a crab apple species (M. micromalus). A pipeline for SNP selection was devised that avoided the pitfalls associated with the inclusion of paralogous sequence variants, supported the construction of robust multi-allelic SNP haploblocks and selected up to 11 entries within narrow genomic regions of ±5 kb, termed focal points (FPs). Broad genome coverage was attained by placing FPs at 1 cM intervals on a consensus genetic map, complementing them with FPs to enrich the ends of each of the chromosomes, and by bridging physical intervals greater than 400 Kbps. The selection also included ∼3.7K validated SNPs from the IRSC 8K array. The array has already been used in other studies where ∼15.8K SNP markers were mapped with an average of ∼6.8K SNPs per full-sib family. The newly developed array with its high density of polymorphic validated SNPs is expected to be of great utility for Pedigree-Based Analysis and Genomic Selection. It will also be a valuable tool to help dissect the genetic mechanisms controlling important fruit quality traits, and to aid the identification of marker-trait associations suitable for the application of Marker Assisted Selection in apple breeding programs.
Bianco, Luca; Cestaro, Alessandro; Sargent, Daniel James; Banchi, Elisa; Derdak, Sophia; Di Guardo, Mario; Salvi, Silvio; Jansen, Johannes; Viola, Roberto; Gut, Ivo; Laurens, Francois; Chagné, David; Velasco, Riccardo; van de Weg, Eric; Troggio, Michela
2014-01-01
High-density SNP arrays for genome-wide assessment of allelic variation have made high resolution genetic characterization of crop germplasm feasible. A medium density array for apple, the IRSC 8K SNP array, has been successfully developed and used for screens of bi-parental populations. However, the number of robust and well-distributed markers contained on this array was not sufficient to perform genome-wide association analyses in wider germplasm sets, or Pedigree-Based Analysis at high precision, because of rapid decay of linkage disequilibrium. We describe the development of an Illumina Infinium array targeting 20K SNPs. The SNPs were predicted from re-sequencing data derived from the genomes of 13 Malus × domestica apple cultivars and one accession belonging to a crab apple species (M. micromalus). A pipeline for SNP selection was devised that avoided the pitfalls associated with the inclusion of paralogous sequence variants, supported the construction of robust multi-allelic SNP haploblocks and selected up to 11 entries within narrow genomic regions of ±5 kb, termed focal points (FPs). Broad genome coverage was attained by placing FPs at 1 cM intervals on a consensus genetic map, complementing them with FPs to enrich the ends of each of the chromosomes, and by bridging physical intervals greater than 400 Kbps. The selection also included ∼3.7K validated SNPs from the IRSC 8K array. The array has already been used in other studies where ∼15.8K SNP markers were mapped with an average of ∼6.8K SNPs per full-sib family. The newly developed array with its high density of polymorphic validated SNPs is expected to be of great utility for Pedigree-Based Analysis and Genomic Selection. It will also be a valuable tool to help dissect the genetic mechanisms controlling important fruit quality traits, and to aid the identification of marker-trait associations suitable for the application of Marker Assisted Selection in apple breeding programs. PMID:25303088
The GenoChip: A New Tool for Genetic Anthropology
Elhaik, Eran; Greenspan, Elliott; Staats, Sean; Krahn, Thomas; Tyler-Smith, Chris; Xue, Yali; Tofanelli, Sergio; Francalacci, Paolo; Cucca, Francesco; Pagani, Luca; Jin, Li; Li, Hui; Schurr, Theodore G.; Greenspan, Bennett; Spencer Wells, R.
2013-01-01
The Genographic Project is an international effort aimed at charting human migratory history. The project is nonprofit and nonmedical, and, through its Legacy Fund, supports locally led efforts to preserve indigenous and traditional cultures. Although the first phase of the project was focused on uniparentally inherited markers on the Y-chromosome and mitochondrial DNA (mtDNA), the current phase focuses on markers from across the entire genome to obtain a more complete understanding of human genetic variation. Although many commercial arrays exist for genome-wide single-nucleotide polymorphism (SNP) genotyping, they were designed for medical genetic studies and contain medically related markers that are inappropriate for global population genetic studies. GenoChip, the Genographic Project’s new genotyping array, was designed to resolve these issues and enable higher resolution research into outstanding questions in genetic anthropology. The GenoChip includes ancestry informative markers obtained for over 450 human populations, an ancient human (Saqqaq), and two archaic hominins (Neanderthal and Denisovan) and was designed to identify all known Y-chromosome and mtDNA haplogroups. The chip was carefully vetted to avoid inclusion of medically relevant markers. To demonstrate its capabilities, we compared the FST distributions of GenoChip SNPs to those of two commercial arrays. Although all arrays yielded similarly shaped (inverse J) FST distributions, the GenoChip autosomal and X-chromosomal distributions had the highest mean FST, attesting to its ability to discern subpopulations. The chip performances are illustrated in a principal component analysis for 14 worldwide populations. In summary, the GenoChip is a dedicated genotyping platform for genetic anthropology. With an unprecedented number of approximately 12,000 Y-chromosomal and approximately 3,300 mtDNA SNPs and over 130,000 autosomal and X-chromosomal SNPs without any known health, medical, or phenotypic relevance, the GenoChip is a useful tool for genetic anthropology and population genetics. PMID:23666864
The GenoChip: a new tool for genetic anthropology.
Elhaik, Eran; Greenspan, Elliott; Staats, Sean; Krahn, Thomas; Tyler-Smith, Chris; Xue, Yali; Tofanelli, Sergio; Francalacci, Paolo; Cucca, Francesco; Pagani, Luca; Jin, Li; Li, Hui; Schurr, Theodore G; Greenspan, Bennett; Spencer Wells, R
2013-01-01
The Genographic Project is an international effort aimed at charting human migratory history. The project is nonprofit and nonmedical, and, through its Legacy Fund, supports locally led efforts to preserve indigenous and traditional cultures. Although the first phase of the project was focused on uniparentally inherited markers on the Y-chromosome and mitochondrial DNA (mtDNA), the current phase focuses on markers from across the entire genome to obtain a more complete understanding of human genetic variation. Although many commercial arrays exist for genome-wide single-nucleotide polymorphism (SNP) genotyping, they were designed for medical genetic studies and contain medically related markers that are inappropriate for global population genetic studies. GenoChip, the Genographic Project's new genotyping array, was designed to resolve these issues and enable higher resolution research into outstanding questions in genetic anthropology. The GenoChip includes ancestry informative markers obtained for over 450 human populations, an ancient human (Saqqaq), and two archaic hominins (Neanderthal and Denisovan) and was designed to identify all known Y-chromosome and mtDNA haplogroups. The chip was carefully vetted to avoid inclusion of medically relevant markers. To demonstrate its capabilities, we compared the FST distributions of GenoChip SNPs to those of two commercial arrays. Although all arrays yielded similarly shaped (inverse J) FST distributions, the GenoChip autosomal and X-chromosomal distributions had the highest mean FST, attesting to its ability to discern subpopulations. The chip performances are illustrated in a principal component analysis for 14 worldwide populations. In summary, the GenoChip is a dedicated genotyping platform for genetic anthropology. With an unprecedented number of approximately 12,000 Y-chromosomal and approximately 3,300 mtDNA SNPs and over 130,000 autosomal and X-chromosomal SNPs without any known health, medical, or phenotypic relevance, the GenoChip is a useful tool for genetic anthropology and population genetics.
ASCI visualization tool evaluation, Version 2.0
DOE Office of Scientific and Technical Information (OSTI.GOV)
Kegelmeyer, P.
1997-04-01
The charter of the ASCI Visualization Common Tools subgroup was to investigate and evaluate 3D scientific visualization tools. As part of that effort, a Tri-Lab evaluation effort was launched in February of 1996. The first step was to agree on a thoroughly documented list of 32 features against which all tool candidates would be evaluated. These evaluation criteria were both gleaned from a user survey and determined from informed extrapolation into the future, particularly as concerns the 3D nature and extremely large size of ASCI data sets. The second step was to winnow a field of 41 candidate tools downmore » to 11. The selection principle was to be as inclusive as practical, retaining every tool that seemed to hold any promise of fulfilling all of ASCI`s visualization needs. These 11 tools were then closely investigated by volunteer evaluators distributed across LANL, LLNL, and SNL. This report contains the results of those evaluations, as well as a discussion of the evaluation philosophy and criteria.« less
USDA-ARS?s Scientific Manuscript database
Using next generation sequencing technology the International Swine SNP Consortium has identified 500,000 SNPs and used these to design an Illumina Infinium iSelect™ SNP BeadChip with a selection of 60,218 SNPs. The selected SNPs include previously validated SNPs and SNPs identified de novo using se...
Coastal On-line Assessment and Synthesis Tool 2.0
NASA Technical Reports Server (NTRS)
Brown, Richard; Navard, Andrew; Nguyen, Beth
2011-01-01
COAST (Coastal On-line Assessment and Synthesis Tool) is a 3D, open-source Earth data browser developed by leveraging and enhancing previous NASA open-source tools. These tools use satellite imagery and elevation data in a way that allows any user to zoom from orbit view down into any place on Earth, and enables the user to experience Earth terrain in a visually rich 3D view. The benefits associated with taking advantage of an open-source geo-browser are that it is free, extensible, and offers a worldwide developer community that is available to provide additional development and improvement potential. What makes COAST unique is that it simplifies the process of locating and accessing data sources, and allows a user to combine them into a multi-layered and/or multi-temporal visual analytical look into possible data interrelationships and coeffectors for coastal environment phenomenology. COAST provides users with new data visual analytic capabilities. COAST has been upgraded to maximize use of open-source data access, viewing, and data manipulation software tools. The COAST 2.0 toolset has been developed to increase access to a larger realm of the most commonly implemented data formats used by the coastal science community. New and enhanced functionalities that upgrade COAST to COAST 2.0 include the development of the Temporal Visualization Tool (TVT) plug-in, the Recursive Online Remote Data-Data Mapper (RECORD-DM) utility, the Import Data Tool (IDT), and the Add Points Tool (APT). With these improvements, users can integrate their own data with other data sources, and visualize the resulting layers of different data types (such as spatial and spectral, for simultaneous visual analysis), and visualize temporal changes in areas of interest.
Bensen, Jeannette T; Xu, Zongli; Smith, Gary J; Mohler, James L; Fontham, Elizabeth T H; Taylor, Jack A
2013-01-01
Genome-wide association studies have established a number of replicated single nucleotide polymorphisms (SNPs) for susceptibility to prostate cancer (CaP), but it is unclear whether these susceptibility SNPs are also associated with disease aggressiveness. This study evaluates whether such replication SNPs or other candidate SNPs are associated with CaP aggressiveness in African-American (AA) and European-American (EA) men. A 1,536 SNP panel which included 34 genome-wide association study (GWAS) replication SNPs, 38 flanking SNPs, a set of ancestry informative markers, and SNPs in candidate genes and other areas was genotyped in 1,060 AA and 1,087 EA men with incident CaP from the North Carolina-Louisiana Prostate Cancer Project (PCaP). Tests for association were conducted using ordinal logistic regression with a log-additive genotype model and a 3-category CaP aggressiveness variable. Four GWAS replication SNPs (rs2660753, rs13254738, rs10090154, rs2735839) and seven flanking SNPs were associated with CaP aggressiveness (P < 0.05) in three genomic regions: One at 3p12 (EA), seven at 8q24 (5 AA, 2 EA), and three at 19q13 at the kallilkrein-related peptidase 3 (KLK3) locus (two AA, one AA and EA). The KLK3 SNPs also were associated with serum prostate-specific antigen (PSA) levels in AA (P < 0.001) but not in EA. A number of the other SNPs showed some evidence of association but none met study-wide significance levels after adjusting for multiple comparisons. Some replicated GWAS susceptibility SNPs may play a role in CaP aggressiveness. However, like susceptibility, these associations are not consistent between racial groups. Copyright © 2012 Wiley Periodicals, Inc.
Bensen, Jeannette T.; Xu, Zongli; Smith, Gary J.; Mohler, James L.; Fontham, Elizabeth T.H.; Taylor, Jack A.
2012-01-01
BACKGROUND Genome-wide association studies have established a number of replicated single nucleotide polymorphisms (SNPs) for susceptibility to prostate cancer (CaP), but it is unclear whether these susceptibility SNPs are also associated with disease aggressiveness. This study evaluates whether such replication SNPs or other candidate SNPs are associated with CaP aggressiveness in African-American (AA) and European-American (EA) men. METHODS A 1,536 SNP panel which included 34 genome-wide association study (GWAS) replication SNPs, 38 flanking SNPs, a set of ancestry informative markers, and SNPs in candidate genes and other areas was genotyped in 1,060 AA and 1,087 EA men with incident CaP from the North Carolina-Louisiana Prostate Cancer Project (PCaP). Tests for association were conducted using ordinal logistic regression with a log-additive genotype model and a 3-category CaP aggressiveness variable. RESULTS 4 GWAS replication SNPs (rs2660753, rs13254738, rs10090154, rs2735839) and 7 flanking SNPs were associated with CaP aggressiveness (P<0.05) in 3 genomic regions: one at 3p12 (EA), 7 at 8q24 (5 AA, 2 EA), and 3 at 19q13 at the kallilkrein-related peptidase 3 (KLK3) locus (2 AA, 1 AA and EA). The KLK3 SNPs also were associated with serum prostate-specific antigen (PSA) levels in AA (p < 0.001) but not in EA. A number of the other SNPs showed some evidence of association but none met study-wide significance levels after adjusting for multiple comparisons. CONCLUSIONS Some replicated GWAS susceptibility SNPs may play a role in CaP aggressiveness. However, like susceptibility, these associations are not consistent between racial groups. PMID:22549899
Wang, Shichen; Wong, Debbie; Forrest, Kerrie; Allen, Alexandra; Chao, Shiaoman; Huang, Bevan E; Maccaferri, Marco; Salvi, Silvio; Milner, Sara G; Cattivelli, Luigi; Mastrangelo, Anna M; Whan, Alex; Stephen, Stuart; Barker, Gary; Wieseke, Ralf; Plieske, Joerg; International Wheat Genome Sequencing Consortium; Lillemo, Morten; Mather, Diane; Appels, Rudi; Dolferus, Rudy; Brown-Guedira, Gina; Korol, Abraham; Akhunova, Alina R; Feuillet, Catherine; Salse, Jerome; Morgante, Michele; Pozniak, Curtis; Luo, Ming-Cheng; Dvorak, Jan; Morell, Matthew; Dubcovsky, Jorge; Ganal, Martin; Tuberosa, Roberto; Lawley, Cindy; Mikoulitch, Ivan; Cavanagh, Colin; Edwards, Keith J; Hayden, Matthew; Akhunov, Eduard
2014-01-01
High-density single nucleotide polymorphism (SNP) genotyping arrays are a powerful tool for studying genomic patterns of diversity, inferring ancestral relationships between individuals in populations and studying marker–trait associations in mapping experiments. We developed a genotyping array including about 90 000 gene-associated SNPs and used it to characterize genetic variation in allohexaploid and allotetraploid wheat populations. The array includes a significant fraction of common genome-wide distributed SNPs that are represented in populations of diverse geographical origin. We used density-based spatial clustering algorithms to enable high-throughput genotype calling in complex data sets obtained for polyploid wheat. We show that these model-free clustering algorithms provide accurate genotype calling in the presence of multiple clusters including clusters with low signal intensity resulting from significant sequence divergence at the target SNP site or gene deletions. Assays that detect low-intensity clusters can provide insight into the distribution of presence–absence variation (PAV) in wheat populations. A total of 46 977 SNPs from the wheat 90K array were genetically mapped using a combination of eight mapping populations. The developed array and cluster identification algorithms provide an opportunity to infer detailed haplotype structure in polyploid wheat and will serve as an invaluable resource for diversity studies and investigating the genetic basis of trait variation in wheat. PMID:24646323
Bruque, Carlos D; Delea, Marisol; Fernández, Cecilia S; Orza, Juan V; Taboas, Melisa; Buzzalino, Noemí; Espeche, Lucía D; Solari, Andrea; Luccerini, Verónica; Alba, Liliana; Nadra, Alejandro D; Dain, Liliana
2016-12-14
Congenital adrenal hyperplasia due to 21-hydroxylase deficiency accounts for 90-95% of CAH cases. In this work we performed an extensive survey of mutations and SNPs modifying the coding sequence of the CYP21A2 gene. Using bioinformatic tools and two plausible CYP21A2 structures as templates, we initially classified all known mutants (n = 343) according to their putative functional impacts, which were either reported in the literature or inferred from structural models. We then performed a detailed analysis on the subset of mutations believed to exclusively impact protein stability. For those mutants, the predicted stability was calculated and correlated with the variant's expected activity. A high concordance was obtained when comparing our predictions with available in vitro residual activities and/or the patient's phenotype. The predicted stability and derived activity of all reported mutations and SNPs lacking functional assays (n = 108) were assessed. As expected, most of the SNPs (52/76) showed no biological implications. Moreover, this approach was applied to evaluate the putative synergy that could emerge when two mutations occurred in cis. In addition, we propose a putative pathogenic effect of five novel mutations, p.L107Q, p.L122R, p.R132H, p.P335L and p.H466fs, found in 21-hydroxylase deficient patients of our cohort.
Bruque, Carlos D.; Delea, Marisol; Fernández, Cecilia S.; Orza, Juan V.; Taboas, Melisa; Buzzalino, Noemí; Espeche, Lucía D.; Solari, Andrea; Luccerini, Verónica; Alba, Liliana; Nadra, Alejandro D.; Dain, Liliana
2016-01-01
Congenital adrenal hyperplasia due to 21-hydroxylase deficiency accounts for 90–95% of CAH cases. In this work we performed an extensive survey of mutations and SNPs modifying the coding sequence of the CYP21A2 gene. Using bioinformatic tools and two plausible CYP21A2 structures as templates, we initially classified all known mutants (n = 343) according to their putative functional impacts, which were either reported in the literature or inferred from structural models. We then performed a detailed analysis on the subset of mutations believed to exclusively impact protein stability. For those mutants, the predicted stability was calculated and correlated with the variant’s expected activity. A high concordance was obtained when comparing our predictions with available in vitro residual activities and/or the patient’s phenotype. The predicted stability and derived activity of all reported mutations and SNPs lacking functional assays (n = 108) were assessed. As expected, most of the SNPs (52/76) showed no biological implications. Moreover, this approach was applied to evaluate the putative synergy that could emerge when two mutations occurred in cis. In addition, we propose a putative pathogenic effect of five novel mutations, p.L107Q, p.L122R, p.R132H, p.P335L and p.H466fs, found in 21-hydroxylase deficient patients of our cohort. PMID:27966633
NASA Astrophysics Data System (ADS)
Sarni, W.
2017-12-01
Water scarcity and poor quality impacts economic development, business growth, and social well-being. Water has become, in our generation, the foremost critical local, regional, and global issue of our time. Despite these needs, there is no water hub or water technology accelerator solely dedicated to water data and tools. There is a need by the public and private sectors for vastly improved data management and visualization tools. This is the WetDATA opportunity - to develop a water data tech hub dedicated to water data acquisition, analytics, and visualization tools for informed policy and business decisions. WetDATA's tools will help incubate disruptive water data technologies and accelerate adoption of current water data solutions. WetDATA is a Colorado-based (501c3), global hub for water data analytics and technology innovation. WetDATA's vision is to be a global leader in water information, data technology innovation and collaborate with other US and global water technology hubs. ROADMAP * Portal (www.wetdata.org) to provide stakeholders with tools/resources to understand related water risks. * The initial activities will provide education, awareness and tools to stakeholders to support the implementation of the Colorado State Water Plan. * Leverage the Western States Water Council Water Data Exchange database. * Development of visualization, predictive analytics and AI tools to engage with stakeholders and provide actionable data and information. TOOLS Education: Provide information on water issues and risks at the local, state, national and global scale. Visualizations: Development of data analytics and visualization tools based upon the 2030 Water Resources Group methodology to support the implementation of the Colorado State Water Plan. Predictive Analytics: Accessing publically available water databases and using machine learning to develop water availability forecasting tools, and time lapse images to support city / urban planning.
2016-11-01
Display Design, Methods , and Results for a User Study by Christopher J Garneau and Robert F Erbacher Approved for public...NOV 2016 US Army Research Laboratory Evaluation of Visualization Tools for Computer Network Defense Analysts: Display Design, Methods ...January 2013–September 2015 4. TITLE AND SUBTITLE Evaluation of Visualization Tools for Computer Network Defense Analysts: Display Design, Methods
Visual impairment and traits of autism in children.
Wrzesińska, Magdalena; Kapias, Joanna; Nowakowska-Domagała, Katarzyna; Kocur, Józef
2017-04-30
Visual impairment present from birth or from an early childhood may lead to psychosocial and emotional disorders. 11-40% of children in the group with visual impairment show traits of autism. The aim of this paper was to present the selected examples of how visual impairment in children is related to the occurrence of autism and to describe the available tools for diagnosing autism in children with visual impairment. So far the relation between visual impairment in children and autism has not been sufficiently confirmed. Psychiatric and psychological diagnosis of children with visual impairment has some difficulties in differentiating between "blindism" and traits typical for autism resulting from a lack of standardized diagnostic tools used to diagnosing children with visual impairment. Another difficulty in diagnosing autism in children with visual impairment is the coexistence of other disabilities in case of most children with vision impairment. Additionally, apart from difficulties in diagnosing autistic disorders in children with eye dysfunctions there is also a question of what tools should be used in therapy and rehabilitation of patients.
Hong, Yanbin; Pandey, Manish K; Liu, Ying; Chen, Xiaoping; Liu, Hong; Varshney, Rajeev K; Liang, Xuanqiang; Huang, Shangzhi
2015-01-01
The cultivated peanut (Arachis hypogaea L.) is an allotetraploid (AABB) species derived from the A-genome (Arachis duranensis) and B-genome (Arachis ipaensis) progenitors. Presence of two versions of a DNA sequence based on the two progenitor genomes poses a serious technical and analytical problem during single nucleotide polymorphism (SNP) marker identification and analysis. In this context, we have analyzed 200 amplicons derived from expressed sequence tags (ESTs) and genome survey sequences (GSS) to identify SNPs in a panel of genotypes consisting of 12 cultivated peanut varieties and two diploid progenitors representing the ancestral genomes. A total of 18 EST-SNPs and 44 genomic-SNPs were identified in 12 peanut varieties by aligning the sequence of A. hypogaea with diploid progenitors. The average frequency of sequence polymorphism was higher for genomic-SNPs than the EST-SNPs with one genomic-SNP every 1011 bp as compared to one EST-SNP every 2557 bp. In order to estimate the potential and further applicability of these identified SNPs, 96 peanut varieties were genotyped using high resolution melting (HRM) method. Polymorphism information content (PIC) values for EST-SNPs ranged between 0.021 and 0.413 with a mean of 0.172 in the set of peanut varieties, while genomic-SNPs ranged between 0.080 and 0.478 with a mean of 0.249. Total 33 SNPs were used for polymorphism detection among the parents and 10 selected lines from mapping population Y13Zh (Zhenzhuhei × Yueyou13). Of the total 33 SNPs, nine SNPs showed polymorphism in the mapping population Y13Zh, and seven SNPs were successfully mapped into five linkage groups. Our results showed that SNPs can be identified in allotetraploid peanut with high accuracy through amplicon sequencing and HRM assay. The identified SNPs were very informative and can be used for different genetic and breeding applications in peanut.
Comparative analysis and visualization of multiple collinear genomes
2012-01-01
Background Genome browsers are a common tool used by biologists to visualize genomic features including genes, polymorphisms, and many others. However, existing genome browsers and visualization tools are not well-suited to perform meaningful comparative analysis among a large number of genomes. With the increasing quantity and availability of genomic data, there is an increased burden to provide useful visualization and analysis tools for comparison of multiple collinear genomes such as the large panels of model organisms which are the basis for much of the current genetic research. Results We have developed a novel web-based tool for visualizing and analyzing multiple collinear genomes. Our tool illustrates genome-sequence similarity through a mosaic of intervals representing local phylogeny, subspecific origin, and haplotype identity. Comparative analysis is facilitated through reordering and clustering of tracks, which can vary throughout the genome. In addition, we provide local phylogenetic trees as an alternate visualization to assess local variations. Conclusions Unlike previous genome browsers and viewers, ours allows for simultaneous and comparative analysis. Our browser provides intuitive selection and interactive navigation about features of interest. Dynamic visualizations adjust to scale and data content making analysis at variable resolutions and of multiple data sets more informative. We demonstrate our genome browser for an extensive set of genomic data sets composed of almost 200 distinct mouse laboratory strains. PMID:22536897
Interactive Visualization of Dependencies
ERIC Educational Resources Information Center
Moreno, Camilo Arango; Bischof, Walter F.; Hoover, H. James
2012-01-01
We present an interactive tool for browsing course requisites as a case study of dependency visualization. This tool uses multiple interactive visualizations to allow the user to explore the dependencies between courses. A usability study revealed that the proposed browser provides significant advantages over traditional methods, in terms of…
Visualizing Qualitative Information
ERIC Educational Resources Information Center
Slone, Debra J.
2009-01-01
The abundance of qualitative data in today's society and the need to easily scrutinize, digest, and share this information calls for effective visualization and analysis tools. Yet, no existing qualitative tools have the analytic power, visual effectiveness, and universality of familiar quantitative instruments like bar charts, scatter-plots, and…
2013-01-01
Background Identification of single nucleotide polymorphisms (SNPs) for specific genes involved in reproduction might improve reliability of genomic estimates for these low-heritability traits. Semen from 550 Holstein bulls of high (≥ 1.7; n = 288) or low (≤ −2; n = 262) daughter pregnancy rate (DPR) was genotyped for 434 candidate SNPs using the Sequenom MassARRAY® system. Three types of SNPs were evaluated: SNPs previously reported to be associated with reproductive traits or physically close to genetic markers for reproduction, SNPs in genes that are well known to be involved in reproductive processes, and SNPs in genes that are differentially expressed between physiological conditions in a variety of tissues associated in reproductive function. Eleven reproduction and production traits were analyzed. Results A total of 40 SNPs were associated (P < 0.05) with DPR. Among these were genes involved in the endocrine system, cell signaling, immune function and inhibition of apoptosis. A total of 10 genes were regulated by estradiol. In addition, 22 SNPs were associated with heifer conception rate, 33 with cow conception rate, 36 with productive life, 34 with net merit, 23 with milk yield, 19 with fat yield, 13 with fat percent, 19 with protein yield, 22 with protein percent, and 13 with somatic cell score. The allele substitution effect for SNPs associated with heifer conception rate, cow conception rate, productive life and net merit were in the same direction as for DPR. Allele substitution effects for several SNPs associated with production traits were in the opposite direction as DPR. Nonetheless, there were 29 SNPs associated with DPR that were not negatively associated with production traits. Conclusion SNPs in a total of 40 genes associated with DPR were identified as well as SNPs for other traits. It might be feasible to include these SNPs into genomic tests of reproduction and other traits. The genes associated with DPR are likely to be important for understanding the physiology of reproduction. Given the large number of SNPs associated with DPR that were not negatively associated with production traits, it should be possible to select for DPR without compromising production. PMID:23759029
Abe, Makiko; Ito, Hidemi; Oze, Isao; Nomura, Masatoshi; Ogawa, Yoshihiro; Matsuo, Keitaro
2017-12-01
Little is known about the difference of genetic predisposition for CRC between ethnicities; however, many genetic traits common to colorectal cancer have been identified. This study investigated whether more SNPs identified in GWAS in East Asian population could improve the risk prediction of Japanese and explored possible application of genetic risk groups as an instrument of the risk communication. 558 Patients histologically verified colorectal cancer and 1116 first-visit outpatients were included for derivation study, and 547 cases and 547 controls were for replication study. Among each population, we evaluated prediction models for the risk of CRC that combined the genetic risk group based on SNPs from GWASs in European-population and a similarly developed model adding SNPs from GWASs in East Asian-population. We examined whether adding East Asian-specific SNPs would improve the discrimination. Six SNPs (rs6983267, rs4779584, rs4444235, rs9929218, rs10936599, rs16969681) from 23 SNPs by European-based GWAS and five SNPs (rs704017, rs11196172, rs10774214, rs647161, rs2423279) among ten SNPs by Asian-based GWAS were selected in CRC risk prediction model. Compared with a 6-SNP-based model, an 11-SNP model including Asian GWAS-SNPs showed improved discrimination capacity in Receiver operator characteristic analysis. A model with 11 SNPs resulted in statistically significant improvement in both derivation (P = 0.0039) and replication studies (P = 0.0018) compared with six SNP model. We estimated cumulative risk of CRC by using genetic risk group based on 11 SNPs and found that the cumulative risk at age 80 is approximately 13% in the high-risk group while 6% in the low-risk group. We constructed a more efficient CRC risk prediction model with 11 SNPs including newly identified East Asian-based GWAS SNPs (rs704017, rs11196172, rs10774214, rs647161, rs2423279). Risk grouping based on 11 SNPs depicted lifetime difference of CRC risk. This might be useful for effective individualized prevention for East Asian.
Visualization of protein interaction networks: problems and solutions
2013-01-01
Background Visualization concerns the representation of data visually and is an important task in scientific research. Protein-protein interactions (PPI) are discovered using either wet lab techniques, such mass spectrometry, or in silico predictions tools, resulting in large collections of interactions stored in specialized databases. The set of all interactions of an organism forms a protein-protein interaction network (PIN) and is an important tool for studying the behaviour of the cell machinery. Since graphic representation of PINs may highlight important substructures, e.g. protein complexes, visualization is more and more used to study the underlying graph structure of PINs. Although graphs are well known data structures, there are different open problems regarding PINs visualization: the high number of nodes and connections, the heterogeneity of nodes (proteins) and edges (interactions), the possibility to annotate proteins and interactions with biological information extracted by ontologies (e.g. Gene Ontology) that enriches the PINs with semantic information, but complicates their visualization. Methods In these last years many software tools for the visualization of PINs have been developed. Initially thought for visualization only, some of them have been successively enriched with new functions for PPI data management and PIN analysis. The paper analyzes the main software tools for PINs visualization considering four main criteria: (i) technology, i.e. availability/license of the software and supported OS (Operating System) platforms; (ii) interoperability, i.e. ability to import/export networks in various formats, ability to export data in a graphic format, extensibility of the system, e.g. through plug-ins; (iii) visualization, i.e. supported layout and rendering algorithms and availability of parallel implementation; (iv) analysis, i.e. availability of network analysis functions, such as clustering or mining of the graph, and the possibility to interact with external databases. Results Currently, many tools are available and it is not easy for the users choosing one of them. Some tools offer sophisticated 2D and 3D network visualization making available many layout algorithms, others tools are more data-oriented and support integration of interaction data coming from different sources and data annotation. Finally, some specialistic tools are dedicated to the analysis of pathways and cellular processes and are oriented toward systems biology studies, where the dynamic aspects of the processes being studied are central. Conclusion A current trend is the deployment of open, extensible visualization tools (e.g. Cytoscape), that may be incrementally enriched by the interactomics community with novel and more powerful functions for PIN analysis, through the development of plug-ins. On the other hand, another emerging trend regards the efficient and parallel implementation of the visualization engine that may provide high interactivity and near real-time response time, as in NAViGaTOR. From a technological point of view, open-source, free and extensible tools, like Cytoscape, guarantee a long term sustainability due to the largeness of the developers and users communities, and provide a great flexibility since new functions are continuously added by the developer community through new plug-ins, but the emerging parallel, often closed-source tools like NAViGaTOR, can offer near real-time response time also in the analysis of very huge PINs. PMID:23368786
Replication of Caucasian Loci Associated with Osteoporosis-related Traits in East Asians
Kim, Beom-Jun; Ahn, Seong Hee; Kim, Hyeon-Mok; Ikegawa, Shiro; Yang, Tie-Lin; Guo, Yan; Deng, Hong-Wen; Koh, Jung-Min
2016-01-01
Background Most reported genome-wide association studies (GWAS) seeking to identify the loci of osteoporosis-related traits have involved Caucasian populations. We aimed to identify the single nucleotide polymorphisms (SNPs) of osteoporosis-related traits among East Asian populations from the bone mineral density (BMD)-related loci of an earlier GWAS meta-analysis. Methods A total of 95 SNPs, identified at the discovery stage of the largest GWAS meta-analysis of BMD, were tested to determine associations with osteoporosis-related traits (BMD, osteoporosis, or fracture) in Korean subjects (n=1,269). The identified SNPs of osteoporosis-related traits in Korean subjects were included in the replication analysis using Chinese (n=2,327) and Japanese (n=768) cohorts. Results A total of 17 SNPs were associated with low BMD in Korean subjects. Specifically, 9, 6, 9, and 5 SNPs were associated with the presence of osteoporosis, non-vertebral fractures, vertebral fractures, and any fracture, respectively. Collectively, 35 of the 95 SNPs (36.8%) were associated with one or more osteoporosis-related trait in Korean subjects. Of the 35 SNPs, 19 SNPs (54.3%) were also associated with one or more osteoporosis-related traits in East Asian populations. Twelve SNPs were associated with low BMD in the Chinese and Japanese cohorts. Specifically, 3, 4, and 2 SNPs were associated with the presence of hip fractures, vertebral fractures, and any fracture, respectively. Conclusions Our results identified the common SNPs of osteoporosis-related traits in both Caucasian and East Asian populations. These SNPs should be further investigated to assess whether they are true genetic markers of osteoporosis. PMID:27965945
Seo, Dong-Won; Oh, Jae-Don; Jin, Shil; Song, Ki-Duk; Park, Hee-Bok; Heo, Kang-Nyeong; Shin, Younhee; Jung, Myunghee; Park, Junhyung; Jo, Cheorun; Lee, Hak-Kyo; Lee, Jun-Heon
2015-02-01
There are five native chicken lines in Korea, which are mainly classified by plumage colors (black, white, red, yellow, gray). These five lines are very important genetic resources in the Korean poultry industry. Based on a next generation sequencing technology, whole genome sequence and reference assemblies were performed using Gallus_gallus_4.0 (NCBI) with whole genome sequences from these lines to identify common and novel single nucleotide polymorphisms (SNPs). We obtained 36,660,731,136 ± 1,257,159,120 bp of raw sequence and average 26.6-fold of 25-29 billion reference assembly sequences representing 97.288 % coverage. Also, 4,006,068 ± 97,534 SNPs were observed from 29 autosomes and the Z chromosome and, of these, 752,309 SNPs are the common SNPs across lines. Among the identified SNPs, the number of novel- and known-location assigned SNPs was 1,047,951 ± 14,956 and 2,948,648 ± 81,414, respectively. The number of unassigned known SNPs was 1,181 ± 150 and unassigned novel SNPs was 8,238 ± 1,019. Synonymous SNPs, non-synonymous SNPs, and SNPs having character changes were 26,266 ± 1,456, 11,467 ± 604, 8,180 ± 458, respectively. Overall, 443,048 ± 26,389 SNPs in each bird were identified by comparing with dbSNP in NCBI. The presently obtained genome sequence and SNP information in Korean native chickens have wide applications for further genome studies such as genetic diversity studies to detect causative mutations for economic and disease related traits.
Accessing and Visualizing scientific spatiotemporal data
NASA Technical Reports Server (NTRS)
Katz, Daniel S.; Bergou, Attila; Berriman, Bruce G.; Block, Gary L.; Collier, Jim; Curkendall, David W.; Good, John; Husman, Laura; Jacob, Joseph C.; Laity, Anastasia;
2004-01-01
This paper discusses work done by JPL 's Parallel Applications Technologies Group in helping scientists access and visualize very large data sets through the use of multiple computing resources, such as parallel supercomputers, clusters, and grids These tools do one or more of the following tasks visualize local data sets for local users, visualize local data sets for remote users, and access and visualize remote data sets The tools are used for various types of data, including remotely sensed image data, digital elevation models, astronomical surveys, etc The paper attempts to pull some common elements out of these tools that may be useful for others who have to work with similarly large data sets.
Your Guide to Medicare Special Needs Plans (SNPs)
... Needs Plans Where Are Medicare SNPs Offered? Each year, different types of Medicare SNPs may be available in different parts of the country. Insurance companies decide where they will do business, so Medicare SNPs may not be available in ...
A Data-Driven Approach to Interactive Visualization of Power Grids
DOE Office of Scientific and Technical Information (OSTI.GOV)
Zhu, Jun
Driven by emerging industry standards, electric utilities and grid coordination organizations are eager to seek advanced tools to assist grid operators to perform mission-critical tasks and enable them to make quick and accurate decisions. The emerging field of visual analytics holds tremendous promise for improving the business practices in today’s electric power industry. The conducted investigation, however, has revealed that the existing commercial power grid visualization tools heavily rely on human designers, hindering user’s ability to discover. Additionally, for a large grid, it is very labor-intensive and costly to build and maintain the pre-designed visual displays. This project proposes amore » data-driven approach to overcome the common challenges. The proposed approach relies on developing powerful data manipulation algorithms to create visualizations based on the characteristics of empirically or mathematically derived data. The resulting visual presentations emphasize what the data is rather than how the data should be presented, thus fostering comprehension and discovery. Furthermore, the data-driven approach formulates visualizations on-the-fly. It does not require a visualization design stage, completely eliminating or significantly reducing the cost for building and maintaining visual displays. The research and development (R&D) conducted in this project is mainly divided into two phases. The first phase (Phase I & II) focuses on developing data driven techniques for visualization of power grid and its operation. Various data-driven visualization techniques were investigated, including pattern recognition for auto-generation of one-line diagrams, fuzzy model based rich data visualization for situational awareness, etc. The R&D conducted during the second phase (Phase IIB) focuses on enhancing the prototyped data driven visualization tool based on the gathered requirements and use cases. The goal is to evolve the prototyped tool developed during the first phase into a commercial grade product. We will use one of the identified application areas as an example to demonstrate how research results achieved in this project are successfully utilized to address an emerging industry need. In summary, the data-driven visualization approach developed in this project has proven to be promising for building the next-generation power grid visualization tools. Application of this approach has resulted in a state-of-the-art commercial tool currently being leveraged by more than 60 utility organizations in North America and Europe .« less
Information visualization of the minority game
NASA Astrophysics Data System (ADS)
Jiang, W.; Herbert, R. D.; Webber, R.
2008-02-01
Many dynamical systems produce large quantities of data. How can the system be understood from the output data? Often people are simply overwhelmed by the data. Traditional tools such as tables and plots are often not adequate, and new techniques are needed to help people to analyze the system. In this paper, we propose the use of two spacefilling visualization tools to examine the output from a complex agent-based financial model. We measure the effectiveness and performance of these tools through usability experiments. Based on the experimental results, we develop two new visualization techniques that combine the advantages and discard the disadvantages of the information visualization tools. The model we use is an evolutionary version of the Minority Game which simulates a financial market.
Distributed visualization of gridded geophysical data: the Carbon Data Explorer, version 0.2.3
NASA Astrophysics Data System (ADS)
Endsley, K. A.; Billmire, M. G.
2016-01-01
Due to the proliferation of geophysical models, particularly climate models, the increasing resolution of their spatiotemporal estimates of Earth system processes, and the desire to easily share results with collaborators, there is a genuine need for tools to manage, aggregate, visualize, and share data sets. We present a new, web-based software tool - the Carbon Data Explorer - that provides these capabilities for gridded geophysical data sets. While originally developed for visualizing carbon flux, this tool can accommodate any time-varying, spatially explicit scientific data set, particularly NASA Earth system science level III products. In addition, the tool's open-source licensing and web presence facilitate distributed scientific visualization, comparison with other data sets and uncertainty estimates, and data publishing and distribution.
Empirical Comparison of Visualization Tools for Larger-Scale Network Analysis
Pavlopoulos, Georgios A.; Paez-Espino, David; Kyrpides, Nikos C.; ...
2017-07-18
Gene expression, signal transduction, protein/chemical interactions, biomedical literature cooccurrences, and other concepts are often captured in biological network representations where nodes represent a certain bioentity and edges the connections between them. While many tools to manipulate, visualize, and interactively explore such networks already exist, only few of them can scale up and follow today’s indisputable information growth. In this review, we shortly list a catalog of available network visualization tools and, from a user-experience point of view, we identify four candidate tools suitable for larger-scale network analysis, visualization, and exploration. Lastly, we comment on their strengths and their weaknesses andmore » empirically discuss their scalability, user friendliness, and postvisualization capabilities.« less
Empirical Comparison of Visualization Tools for Larger-Scale Network Analysis
DOE Office of Scientific and Technical Information (OSTI.GOV)
Pavlopoulos, Georgios A.; Paez-Espino, David; Kyrpides, Nikos C.
Gene expression, signal transduction, protein/chemical interactions, biomedical literature cooccurrences, and other concepts are often captured in biological network representations where nodes represent a certain bioentity and edges the connections between them. While many tools to manipulate, visualize, and interactively explore such networks already exist, only few of them can scale up and follow today’s indisputable information growth. In this review, we shortly list a catalog of available network visualization tools and, from a user-experience point of view, we identify four candidate tools suitable for larger-scale network analysis, visualization, and exploration. Lastly, we comment on their strengths and their weaknesses andmore » empirically discuss their scalability, user friendliness, and postvisualization capabilities.« less
Yokoyama, Eiji; Hirai, Shinichiro; Ishige, Taichiro; Murakami, Satoshi
2018-01-02
Seventeen clusters of Shiga toxin-producing Escherichia coli O157:H7/- (O157) strains, determined by cluster analysis of pulsed-field gel electrophoresis patterns, were analyzed using whole genome sequence (WGS) data to investigate this pathogen's molecular epidemiology. The 17 clusters included 136 strains containing strains from nine outbreaks, with each outbreak caused by a single source contaminated with the organism, as shown by epidemiological contact surveys. WGS data of these strains were used to identify single nucleotide polymorphisms (SNPs) by two methods: short read data were directly mapped to a reference genome (mapping derived SNPs) and common SNPs between the mapping derived SNPs and SNPs in assembled data of short read data (common SNPs). Among both SNPs, those that were detected in genes with a gap were excluded to remove ambiguous SNPs from further analysis. The effectiveness of both SNPs was investigated among all the concatenated SNPs that were detected (whole SNP set); SNPs were divided into three categories based on the genes in which they were located (i.e., backbone SNP set, O-island SNP set, and mobile element SNP set); and SNPs in non-coding regions (intergenic region SNP set). When SNPs from strains isolated from the nine single source derived outbreaks were analyzed using an unweighted pair group method with arithmetic mean tree (UPGMA) and a minimum spanning tree (MST), the maximum pair-wise distances of the backbone SNP set of the mapping derived SNPs were significantly smaller than those of the whole and intergenic region SNP set on both UPGMAs and MSTs. This significant difference was also observed when the backbone SNP set of the common SNPs were examined (Steel-Dwass test, P≤0.01). When the maximum pair-wise distances were compared between the mapping derived and common SNPs, significant differences were observed in those of the whole, mobile element, and intergenic region SNP set (Wilcoxon signed rank test, P≤0.01). When all the strains included in one complex on an MST or one cluster on a UPGMA were designated as the same genotype, the values of the Hunter-Gaston Discriminatory Power Index for the backbone SNP set of the mapping derived and common SNPs were higher than those of other SNP sets. In contrast, the mobile element SNP set could not robustly subdivide lineage I strains of tested O157 strains using both the mapping derived and common SNPs. These results suggested that the backbone SNP set were the most effective for analysis of WGS data for O157 in enabling an appropriation of its molecular epidemiology. Copyright © 2017 Elsevier B.V. All rights reserved.
The Echinococcus canadensis (G7) genome: a key knowledge of parasitic platyhelminth human diseases.
Maldonado, Lucas L; Assis, Juliana; Araújo, Flávio M Gomes; Salim, Anna C M; Macchiaroli, Natalia; Cucher, Marcela; Camicia, Federico; Fox, Adolfo; Rosenzvit, Mara; Oliveira, Guilherme; Kamenetzky, Laura
2017-02-27
The parasite Echinococcus canadensis (G7) (phylum Platyhelminthes, class Cestoda) is one of the causative agents of echinococcosis. Echinococcosis is a worldwide chronic zoonosis affecting humans as well as domestic and wild mammals, which has been reported as a prioritized neglected disease by the World Health Organisation. No genomic data, comparative genomic analyses or efficient therapeutic and diagnostic tools are available for this severe disease. The information presented in this study will help to understand the peculiar biological characters and to design species-specific control tools. We sequenced, assembled and annotated the 115-Mb genome of E. canadensis (G7). Comparative genomic analyses using whole genome data of three Echinococcus species not only confirmed the status of E. canadensis (G7) as a separate species but also demonstrated a high nucleotide sequences divergence in relation to E. granulosus (G1). The E. canadensis (G7) genome contains 11,449 genes with a core set of 881 orthologs shared among five cestode species. Comparative genomics revealed that there are more single nucleotide polymorphisms (SNPs) between E. canadensis (G7) and E. granulosus (G1) than between E. canadensis (G7) and E. multilocularis. This result was unexpected since E. canadensis (G7) and E. granulosus (G1) were considered to belong to the species complex E. granulosus sensu lato. We described SNPs in known drug targets and metabolism genes in the E. canadensis (G7) genome. Regarding gene regulation, we analysed three particular features: CpG island distribution along the three Echinococcus genomes, DNA methylation system and small RNA pathway. The results suggest the occurrence of yet unknown gene regulation mechanisms in Echinococcus. This is the first work that addresses Echinococcus comparative genomics. The resources presented here will promote the study of mechanisms of parasite development as well as new tools for drug discovery. The availability of a high-quality genome assembly is critical for fully exploring the biology of a pathogenic organism. The E. canadensis (G7) genome presented in this study provides a unique opportunity to address the genetic diversity among the genus Echinococcus and its particular developmental features. At present, there is no unequivocal taxonomic classification of Echinococcus species; however, the genome-wide SNPs analysis performed here revealed the phylogenetic distance among these three Echinococcus species. Additional cestode genomes need to be sequenced to be able to resolve their phylogeny.
2011-01-01
Background Cucurbita pepo belongs to the Cucurbitaceae family. The "Zucchini" types rank among the highest-valued vegetables worldwide, and other C. pepo and related Cucurbita spp., are food staples and rich sources of fat and vitamins. A broad range of genomic tools are today available for other cucurbits that have become models for the study of different metabolic processes. However, these tools are still lacking in the Cucurbita genus, thus limiting gene discovery and the process of breeding. Results We report the generation of a total of 512,751 C. pepo EST sequences, using 454 GS FLX Titanium technology. ESTs were obtained from normalized cDNA libraries (root, leaves, and flower tissue) prepared using two varieties with contrasting phenotypes for plant, flowering and fruit traits, representing the two C. pepo subspecies: subsp. pepo cv. Zucchini and subsp. ovifera cv Scallop. De novo assembling was performed to generate a collection of 49,610 Cucurbita unigenes (average length of 626 bp) that represent the first transcriptome of the species. Over 60% of the unigenes were functionally annotated and assigned to one or more Gene Ontology terms. The distributions of Cucurbita unigenes followed similar tendencies than that reported for Arabidopsis or melon, suggesting that the dataset may represent the whole Cucurbita transcriptome. About 34% unigenes were detected to have known orthologs of Arabidopsis or melon, including genes potentially involved in disease resistance, flowering and fruit quality. Furthermore, a set of 1,882 unigenes with SSR motifs and 9,043 high confidence SNPs between Zucchini and Scallop were identified, of which 3,538 SNPs met criteria for use with high throughput genotyping platforms, and 144 could be detected as CAPS. A set of markers were validated, being 80% of them polymorphic in a set of variable C. pepo and C. moschata accessions. Conclusion We present the first broad survey of gene sequences and allelic variation in C. pepo, where limited prior genomic information existed. The transcriptome provides an invaluable new tool for biological research. The developed molecular markers are the basis for future genetic linkage and quantitative trait loci analysis, and will be essential to speed up the process of breeding new and better adapted squash varieties. PMID:21310031
A web-based data visualization tool for the MIMIC-II database.
Lee, Joon; Ribey, Evan; Wallace, James R
2016-02-04
Although MIMIC-II, a public intensive care database, has been recognized as an invaluable resource for many medical researchers worldwide, becoming a proficient MIMIC-II researcher requires knowledge of SQL programming and an understanding of the MIMIC-II database schema. These are challenging requirements especially for health researchers and clinicians who may have limited computer proficiency. In order to overcome this challenge, our objective was to create an interactive, web-based MIMIC-II data visualization tool that first-time MIMIC-II users can easily use to explore the database. The tool offers two main features: Explore and Compare. The Explore feature enables the user to select a patient cohort within MIMIC-II and visualize the distributions of various administrative, demographic, and clinical variables within the selected cohort. The Compare feature enables the user to select two patient cohorts and visually compare them with respect to a variety of variables. The tool is also helpful to experienced MIMIC-II researchers who can use it to substantially accelerate the cumbersome and time-consuming steps of writing SQL queries and manually visualizing extracted data. Any interested researcher can use the MIMIC-II data visualization tool for free to quickly and conveniently conduct a preliminary investigation on MIMIC-II with a few mouse clicks. Researchers can also use the tool to learn the characteristics of the MIMIC-II patients. Since it is still impossible to conduct multivariable regression inside the tool, future work includes adding analytics capabilities. Also, the next version of the tool will aim to utilize MIMIC-III which contains more data.
Genotyping of 75 SNPs using arrays for individual identification in five population groups.
Hwa, Hsiao-Lin; Wu, Lawrence Shih Hsin; Lin, Chun-Yen; Huang, Tsun-Ying; Yin, Hsiang-I; Tseng, Li-Hui; Lee, James Chun-I
2016-01-01
Single nucleotide polymorphism (SNP) typing offers promise to forensic genetics. Various strategies and panels for analyzing SNP markers for individual identification have been published. However, the best panels with fewer identity SNPs for all major population groups are still under discussion. This study aimed to find more autosomal SNPs with high heterozygosity for individual identification among Asian populations. Ninety-six autosomal SNPs of 502 DNA samples from unrelated individuals of five population groups (208 Taiwanese Han, 83 Filipinos, 62 Thais, 69 Indonesians, and 80 individuals with European, Near Eastern, or South Asian ancestry) were analyzed using arrays in an initial screening, and 75 SNPs (group A, 46 newly selected SNPs; groups B, 29 SNPs based on a previous SNP panel) were selected for further statistical analyses. Some SNPs with high heterozygosity from Asian populations were identified. The combined random match probability of the best 40 and 45 SNPs was between 3.16 × 10(-17) and 7.75 × 10(-17) and between 2.33 × 10(-19) and 7.00 × 10(-19), respectively, in all five populations. These loci offer comparable power to short tandem repeats (STRs) for routine forensic profiling. In this study, we demonstrated the population genetic characteristics and forensic parameters of 75 SNPs with high heterozygosity from five population groups. This SNPs panel can provide valuable genotypic information and can be helpful in forensic casework for individual identification among these populations.
Roets-Merken, Lieve M; Zuidema, Sytse U; Vernooij-Dassen, Myrra J F J; Kempen, Gertrudis I J M
2014-11-01
This study investigated the psychometric properties of the Severe Dual Sensory Loss screening tool, a tool designed to help nurses and care assistants to identify hearing, visual and dual sensory impairment in older adults. Construct validity of the Severe Dual Sensory Loss screening tool was evaluated using Crohnbach's alpha and factor analysis. Interrater reliability was calculated using Kappa statistics. To evaluate the predictive validity, sensitivity and specificity were calculated by comparison with the criterion standard assessment for hearing and vision. The criterion used for hearing impairment was a hearing loss of ≥40 decibel measured by pure-tone audiometry, and the criterion for visual impairment was a visual acuity of ≤0.3 diopter or a visual field of ≤0.3°. Feasibility was evaluated by the time needed to fill in the screening tool and the clarity of the instruction and items. Prevalence of dual sensory impairment was calculated. A total of 56 older adults receiving aged care and 12 of their nurses and care assistants participated in the study. Crohnbach's alpha was 0.81 for the hearing subscale and 0.84 for the visual subscale. Factor analysis showed two constructs for hearing and two for vision. Kappa was 0.71 for the hearing subscale and 0.74 for the visual subscale. The predictive validity showed a sensitivity of 0.71 and a specificity of 0.72 for the hearing subscale; and a sensitivity of 0.69 and a specificity of 0.78 for the visual subscale. The optimum cut-off point for each subscale was score 1. The nurses and care assistants reported that the Severe Dual Sensory Loss screening tool was easy to use. The prevalence of hearing and vision impairment was 55% and 29%, respectively, and that of dual sensory impairment was 20%. The Severe Dual Sensory Loss screening tool was compared with the criterion standards for hearing and visual impairment and was found a valid and reliable tool, enabling nurses and care assistants to identify hearing, visual and dual sensory impairment among older adults. Copyright © 2014 Elsevier Ltd. All rights reserved.
Sinking Maps: A Conceptual Tool for Visual Metaphor
ERIC Educational Resources Information Center
Giampa, Joan Marie
2012-01-01
Sinking maps, created by Northern Virginia Community College professor Joan Marie Giampa, are tools that teach fine art students how to construct visual metaphor by conceptually mapping sensory perceptions. Her dissertation answers the question, "Can visual metaphor be conceptually mapped in the art classroom?" In the Prologue, Giampa…
Nieuwenhuis, Maartje A.; Siedlinski, Matteusz; van den Berge, Maarten; Granell, Raquel; Li, Xingnan; Niens, Marijke; van der Vlies, Pieter; Altmüller, Janine; Nürnberg, Peter; Kerkhof, Marjan; van Schayck, Onno C.; Riemersma, Ronald A.; van der Molen, Thys; de Monchy, Jan G.; Bossé, Yohan; Sandford, Andrew; Bruijnzeel-Koomen, Carla A.; van Wijk, Roy G.; ten Hacken, Nick H.; Timens, Wim; Boezen, H. Marike; Henderson, John; Kabesch, Michael; Vonk, Judith M.; Postma, Dirkje S.; Koppelman, Gerard H.
2016-01-01
Background Genome wide association studies (GWAS) of asthma have identified single nucleotide polymorphisms (SNPs) that modestly increase the risk for asthma. This could be due to phenotypic heterogeneity of asthma. Bronchial hyperresponsiveness (BHR) is a phenotypic hallmark of asthma. We aim to identify susceptibility genes for asthma combined with BHR and analyse the presence of cis-eQTLs among replicated SNPs. Secondly, we compare the genetic association of SNPs previously associated with (doctor diagnosed) asthma to our GWAS of asthma with BHR. Methods A GWAS was performed in 920 asthmatics with BHR and 980 controls. Top SNPs of our GWAS were analysed in four replication cohorts and lung cis-eQTL analysis was performed on replicated SNPs. We investigated association of SNPs previously associated with asthma in our data. Results 368 SNPs were followed up for replication. Six SNPs in genes encoding ABI3BP, NAF1, MICA and the 17q21 locus replicated in one or more cohorts, with one locus (17q21) achieving genome wide significance after meta-analysis. Five out of 6 replicated SNPs regulated 35 gene transcripts in whole lung. Eight of 20 asthma associated SNPs from previous GWAS were significantly associated with asthma and BHR. Three SNPs, in IL-33 and GSDMB, showed larger effect sizes in our data compared to published literature. Conclusions Combining GWAS with subsequent lung eQTL analysis revealed disease associated SNPs regulating lung mRNA expression levels of potential new asthma genes. Adding BHR to the asthma definition does not lead to an overall larger genetic effect size than analysing (doctor’s diagnosed) asthma. PMID:27439200
An Interior Signage System for the USAF Academy Hospital
1979-08-01
manner. Graphic Design - Graphic design is a design for visual communication . Graphic Design Tools - There are four basic graphic design tools available...specializes in the design of two dimensional visual communication components. The graphic designer utilizes the four graphic design tools in developing
Takahashi, Chie; Watt, Simon J.
2014-01-01
When we hold an object while looking at it, estimates from visual and haptic cues to size are combined in a statistically optimal fashion, whereby the “weight” given to each signal reflects their relative reliabilities. This allows object properties to be estimated more precisely than would otherwise be possible. Tools such as pliers and tongs systematically perturb the mapping between object size and the hand opening. This could complicate visual-haptic integration because it may alter the reliability of the haptic signal, thereby disrupting the determination of appropriate signal weights. To investigate this we first measured the reliability of haptic size estimates made with virtual pliers-like tools (created using a stereoscopic display and force-feedback robots) with different “gains” between hand opening and object size. Haptic reliability in tool use was straightforwardly determined by a combination of sensitivity to changes in hand opening and the effects of tool geometry. The precise pattern of sensitivity to hand opening, which violated Weber's law, meant that haptic reliability changed with tool gain. We then examined whether the visuo-motor system accounts for these reliability changes. We measured the weight given to visual and haptic stimuli when both were available, again with different tool gains, by measuring the perceived size of stimuli in which visual and haptic sizes were varied independently. The weight given to each sensory cue changed with tool gain in a manner that closely resembled the predictions of optimal sensory integration. The results are consistent with the idea that different tool geometries are modeled by the brain, allowing it to calculate not only the distal properties of objects felt with tools, but also the certainty with which those properties are known. These findings highlight the flexibility of human sensory integration and tool-use, and potentially provide an approach for optimizing the design of visual-haptic devices. PMID:24592245
Liu, Jun-Jun; Shamoun, Simon Francis; Leal, Isabel; Kowbel, Robert; Sumampong, Grace; Zamany, Arezoo
2018-05-01
Characterization of genes involved in differentiation of pathogen species and isolates with variations of virulence traits provides valuable information to control tree diseases for meeting the challenges of sustainable forest health and phytosanitary trade issues. Lack of genetic knowledge and genomic resources hinders novel gene discovery, molecular mechanism studies and development of diagnostic tools in the management of forest pathogens. Here, we report on transcriptome profiling of Heterobasidion occidentale isolates with contrasting virulence levels. Comparative transcriptomic analysis identified orthologous groups exclusive to H. occidentale and its isolates, revealing biological processes involved in the differentiation of isolates. Further bioinformatics analyses identified an H. occidentale secretome, CYPome and other candidate effectors, from which genes with species- and isolate-specific expression were characterized. A large proportion of differentially expressed genes were revealed to have putative activities as cell wall modification enzymes and transcription factors, suggesting their potential roles in virulence and fungal pathogenesis. Next, large numbers of simple sequence repeats (SSRs) and single nucleotide polymorphisms (SNPs) were detected, including more than 14 000 interisolate non-synonymous SNPs. These polymorphic loci and species/isolate-specific genes may contribute to virulence variations and provide ideal DNA markers for development of diagnostic tools and investigation of genetic diversity. © 2018 The Authors. Microbial Biotechnology published by John Wiley & Sons Ltd and Society for Applied Microbiology.
Tillmar, Andreas O; Phillips, Chris
2017-01-01
Advances in massively parallel sequencing technology have enabled the combination of a much-expanded number of DNA markers (notably STRs and SNPs in one or combined multiplexes), with the aim of increasing the weight of evidence in forensic casework. However, when data from multiple loci on the same chromosome are used, genetic linkage can affect the final likelihood calculation. In order to study the effect of linkage for different sets of markers we developed the biostatistical tool ILIR, (Impact of Linkage on forensic markers for Identity and Relationship tests). The ILIR tool can be used to study the overall impact of genetic linkage for an arbitrary set of markers used in forensic testing. Application of ILIR can be useful during marker selection and design of new marker panels, as well as being highly relevant for existing marker sets as a way to properly evaluate the effects of linkage on a case-by-case basis. ILIR, implemented via the open source platform R, includes variation and genomic position reference data for over 40 STRs and 140 SNPs, combined with the ability to include additional forensic markers of interest. The use of the software is demonstrated with examples from several different established marker sets (such as the expanded CODIS core loci) including a review of the interpretation of linked genetic data. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.
Alsaif, Mohammed A.; Al Shammari, Sulaiman A.; Alhamdan, Adel A.
2012-01-01
Introduction Single-nucleotide polymorphisms (SNPs) are biomarkers for exploring the genetic basis of many complex human diseases. The prediction of SNPs is promising in modern genetic analysis but it is still a great challenge to identify the functional SNPs in a disease-related gene. The computational approach has overcome this challenge and an increase in the successful rate of genetic association studies and reduced cost of genotyping have been achieved. The objective of this study is to identify deleterious non-synonymous SNPs (nsSNPs) associated with the COL1A1 gene. Material and methods The SNPs were retrieved from the Single Nucleotide Polymorphism Database (dbSNP). Using I-Mutant, protein stability change was calculated. The potentially functional nsSNPs and their effect on proteins were predicted by PolyPhen and SIFT respectively. FASTSNP was used for estimation of risk score. Results Our analysis revealed 247 SNPs as non-synonymous, out of which 5 nsSNPs were found to be least stable by I-Mutant 2.0 with a DDG value of > –1.0. Four nsSNPs, namely rs17853657, rs17857117, rs57377812 and rs1059454, showed a highly deleterious tolerance index score of 0.00 with a change in their physicochemical properties by the SIFT server. Seven nsSNPs, namely rs1059454, rs8179178, rs17853657, rs17857117, rs72656340, rs72656344 and rs72656351, were found to be probably damaging with a PSIC score difference between 2.0 and 3.5 by the PolyPhen server. Three nsSNPs, namely rs1059454, rs17853657 and rs17857117, were found to be highly polymorphic with a risk score of 3-4 with a possible effect of non-conservative change and splicing regulation by FASTSNP. Conclusions Three nsSNPs, namely rs1059454, rs17853657 and rs17857117, are potential functional polymorphisms that are likely to have a functional impact on the COL1A1 gene. PMID:24273577
Persson, Johanna; Dalholm, Elisabeth Hornyánszky; Johansson, Gerd
2014-01-01
To demonstrate the use of visualization and simulation tools in order to involve stakeholders and inform the process in hospital change processes, illustrated by an empirical study from a children's emergency clinic. Reorganization and redevelopment of a hospital is a complex activity that involves many stakeholders and demands. Visualization and simulation tools have proven useful for involving practitioners and eliciting relevant knowledge. More knowledge is desired about how these tools can be implemented in practice for hospital planning processes. A participatory planning process including practitioners and researchers was executed over a 3-year period to evaluate a combination of visualization and simulation tools to involve stakeholders in the planning process and to elicit knowledge about needs and requirements. The initial clinic proposal from the architect was discarded as a result of the empirical study. Much general knowledge about the needs of the organization was extracted by means of the adopted tools. Some of the tools proved to be more accessible than others for the practitioners participating in the study. The combination of tools added value to the process by presenting information in alternative ways and eliciting questions from different angles. Visualization and simulation tools inform a planning process (or other types of change processes) by providing the means to see beyond present demands and current work structures. Long-term involvement in combination with accessible tools is central for creating a participatory setting where the practitioners' knowledge guides the process. © 2014 Vendome Group, LLC.
Optimal visual-haptic integration with articulated tools.
Takahashi, Chie; Watt, Simon J
2017-05-01
When we feel and see an object, the nervous system integrates visual and haptic information optimally, exploiting the redundancy in multiple signals to estimate properties more precisely than is possible from either signal alone. We examined whether optimal integration is similarly achieved when using articulated tools. Such tools (tongs, pliers, etc) are a defining characteristic of human hand function, but complicate the classical sensory 'correspondence problem' underlying multisensory integration. Optimal integration requires establishing the relationship between signals acquired by different sensors (hand and eye) and, therefore, in fundamentally unrelated units. The system must also determine when signals refer to the same property of the world-seeing and feeling the same thing-and only integrate those that do. This could be achieved by comparing the pattern of current visual and haptic input to known statistics of their normal relationship. Articulated tools disrupt this relationship, however, by altering the geometrical relationship between object properties and hand posture (the haptic signal). We examined whether different tool configurations are taken into account in visual-haptic integration. We indexed integration by measuring the precision of size estimates, and compared our results to optimal predictions from a maximum-likelihood integrator. Integration was near optimal, independent of tool configuration/hand posture, provided that visual and haptic signals referred to the same object in the world. Thus, sensory correspondence was determined correctly (trial-by-trial), taking tool configuration into account. This reveals highly flexible multisensory integration underlying tool use, consistent with the brain constructing internal models of tools' properties.
Genetic polymorphisms associated with breast cancer in malaysian cohort.
Chahil, Jagdish Kaur; Munretnam, Khamsigan; Samsudin, Nurulhafizah; Lye, Say Hean; Hashim, Nikman Adli Nor; Ramzi, Nurul Hanis; Velapasamy, Sharmila; Wee, Ler Lian; Alex, Livy
2015-04-01
Genome-wide association studies have discovered multiple single nucleotide polymorphisms (SNPs) associated with the risk of common diseases. The objective of this study was to demonstrate the replication of previously published SNPs that showed statistical significance for breast cancer in the Malaysian population. In this case-control study, 80 subjects for each group were recruited from various hospitals in Malaysia. A total of 768 SNPs were genotyped and analyzed to distinguish risk and protective alleles. A total of three SNPs were found to be associated with increased risk of breast cancer while six SNPs showed protective effect. All nine were statistically significant SNPs (p ≤ 0.01), five SNPs from previous studies were successfully replicated in our study. Significant modifiable (diet) and non-modifiable (family history of breast cancer in first degree relative) risk factors were also observed. We identified nine SNPs from this study to be either conferring susceptibility or protection to breast cancer which may serve as potential markers in risk prediction.
Gene-environment interaction on neural mechanisms of orthographic processing in Chinese children
Su, Mengmeng; Wang, Jiuju; Maurer, Urs; Zhang, Yuping; Li, Jun; McBride-Chang, Catherine; Tardif, Twila; Liu, Youyi; Shu, Hua
2015-01-01
The ability to process and identify visual words requires efficient orthographic processing of print, consisting of letters in alphabetic languages or characters in Chinese. The N170 is a robust neural marker for orthographic processes. Both genetic and environmental factors, such as home literacy, have been shown to influence orthographic processing at the behavioral level, but their relative contributions and interactions are not well understood. The present study aimed to reveal possible gene-by-environment interactions on orthographic processing at the behavioral and neural level in a normal children sample. Sixty 12 year old Chinese children from a 10-year longitudinal sample underwent an implicit visual-word color decision task on real words and stroke combinations. The ERP analysis focused on the increase of the occipito-temporal N170 to words compared to stroke combinations. The genetic analysis focused on two SNPs (rs1419228, rs1091047) in the gene DCDC2 based on previous findings linking these 2 SNPs to orthographic coding. Home literacy was measured previously as the number of children's books at home, when the children were at the age of 3. Relative to stroke combinations, real words evoked greater N170 in bilateral posterior brain regions. A significant interaction between rs1091047 and home literacy was observed on the changes of N170 comparing real words to stroke combinations in the left hemisphere. Particularly, children carrying the major allele “G” showed a similar N170 effect irrespective of their environment, while children carrying the minor allele “C” showed a smaller N170 effect in low home-literacy environment than those in good environment. PMID:26294811
OpenGl Visualization Tool and Library Version: 1.0
DOE Office of Scientific and Technical Information (OSTI.GOV)
2010-06-22
GLVis is an OpenGL tool for visualization of finite element meshes and functions. When started without any options, GLVis starts a server, which waits for a socket connections and visualizes any recieved data. This way the results of simulations on a remote (parallel) machine can be visualized on the lical user desktop. GLVis can also be used to visualize a mesh with or without a finite element function (solution). It can run a batch sequence of commands (GLVis scripts), or display previously saved socket streams.
Genomic Regions Associated with Root Traits under Drought Stress in Tropical Maize (Zea mays L.)
Zaidi, P. H.; Krishna, Girish; Krishnamurthy, L.; Gajanan, S.; Babu, Raman; Zerka, M.; Vinayan, M. T.; Vivek, B. S.
2016-01-01
An association mapping panel, named as CIMMYT Asia association mapping (CAAM) panel, involving 396 diverse tropical maize lines were phenotyped for various structural and functional traits of roots under drought and well-watered conditions. The experiment was conducted during Kharif (summer-rainy) season of 2012 and 2013 in root phenotyping facility at CIMMYT-Hyderabad, India. The CAAM panel was genotyped to generate 955, 690 SNPs through GBS v2.7 using Illumina Hi-seq 2000/2500 at Institute for Genomic Diversity, Cornell University, Ithaca, NY, USA. GWAS analysis was carried out using 331,390 SNPs filtered from the entire set of SNPs revealed a total of 50 and 67 SNPs significantly associated for root functional (transpiration efficiency, flowering period water use) and structural traits (rooting depth, root dry weight, root length, root volume, root surface area and root length density), respectively. In addition to this, 37 SNPs were identified for grain yield and shoot biomass under well-watered and drought stress. Though many SNPs were found to have significant association with the traits under study, SNPs that were common for more than one trait were discussed in detail. A total 18 SNPs were found to have common association with more than one trait, out of which 12 SNPs were found within or near the various gene functional regions. In this study we attempted to identify the trait specific maize lines based on the presence of favorable alleles for the SNPs associated with multiple traits. Two SNPs S3_128533512 and S7_151238865 were associated with transpiration efficiency, shoot biomass and grain yield under well-watered condition. Based on favorable allele for these SNPs seven inbred lines were identified. Similarly, four lines were identified for transpiration efficiency and shoot biomass under drought stress based on the presence of favorable allele for the common SNPs S1_211520521, S2_20017716, S3_57210184 and S7_130878458 and three lines were identified for flowering period water-use, transpiration efficiency, root dry weight and root volume based on the presence of favorable allele for the common SNPs S3_162065732 and S3_225760139. PMID:27768702
Software attribute visualization for high integrity software
DOE Office of Scientific and Technical Information (OSTI.GOV)
Pollock, G.M.
1998-03-01
This report documents a prototype tool developed to investigate the use of visualization and virtual reality technologies for improving software surety confidence. The tool is utilized within the execution phase of the software life cycle. It provides a capability to monitor an executing program against prespecified requirements constraints provided in a program written in the requirements specification language SAGE. The resulting Software Attribute Visual Analysis Tool (SAVAnT) also provides a technique to assess the completeness of a software specification.
VisAdapt: A Visualization Tool to Support Climate Change Adaptation.
Johansson, Jimmy; Opach, Tomasz; Glaas, Erik; Neset, Tina-Simone; Navarra, Carlo; Linner, Bjorn-Ola; Rod, Jan Ketil
2017-01-01
The web-based visualization VisAdapt tool was developed to help laypeople in the Nordic countries assess how anticipated climate change will impact their homes. The tool guides users through a three-step visual process that helps them explore risks and identify adaptive actions specifically modified to their location and house type. This article walks through the tool's multistep, user-centered design process. Although VisAdapt's target end users are Nordic homeowners, the insights gained from the development process and the lessons learned from the project are applicable to a wide range of domains.
Ishida, Kelly; Cipriano, Talita Ferreira; Rocha, Gustavo Miranda; Weissmüller, Gilberto; Gomes, Fabio; Miranda, Kildare; Rozental, Sonia
2013-01-01
The microbial synthesis of nanoparticles is a green chemistry approach that combines nanotechnology and microbial biotechnology. The aim of this study was to obtain silver nanoparticles (SNPs) using aqueous extract from the filamentous fungus Fusarium oxysporum as an alternative to chemical procedures and to evaluate its antifungal activity. SNPs production increased in a concentration-dependent way up to 1 mM silver nitrate until 30 days of reaction. Monodispersed and spherical SNPs were predominantly produced. After 60 days, it was possible to observe degenerated SNPs with in additional needle morphology. The SNPs showed a high antifungal activity against Candida and Cryptococcus , with minimum inhibitory concentration values ≤ 1.68 µg/mL for both genera. Morphological alterations of Cryptococcus neoformans treated with SNPs were observed such as disruption of the cell wall and cytoplasmic membrane and lost of the cytoplasm content. This work revealed that SNPs can be easily produced by F. oxysporum aqueous extracts and may be a feasible, low-cost, environmentally friendly method for generating stable and uniformly sized SNPs. Finally, we have demonstrated that these SNPs are active against pathogenic fungi, such as Candida and Cryptococcus . PMID:24714966
Ishida, Kelly; Cipriano, Talita Ferreira; Rocha, Gustavo Miranda; Weissmüller, Gilberto; Gomes, Fabio; Miranda, Kildare; Rozental, Sonia
2014-04-01
The microbial synthesis of nanoparticles is a green chemistry approach that combines nanotechnology and microbial biotechnology. The aim of this study was to obtain silver nanoparticles (SNPs) using aqueous extract from the filamentous fungus Fusarium oxysporum as an alternative to chemical procedures and to evaluate its antifungal activity. SNPs production increased in a concentration-dependent way up to 1 mM silver nitrate until 30 days of reaction. Monodispersed and spherical SNPs were predominantly produced. After 60 days, it was possible to observe degenerated SNPs with in additional needle morphology. The SNPs showed a high antifungal activity against Candida and Cryptococcus , with minimum inhibitory concentration values ≤ 1.68 µg/mL for both genera. Morphological alterations of Cryptococcus neoformans treated with SNPs were observed such as disruption of the cell wall and cytoplasmic membrane and lost of the cytoplasm content. This work revealed that SNPs can be easily produced by F. oxysporum aqueous extracts and may be a feasible, low-cost, environmentally friendly method for generating stable and uniformly sized SNPs. Finally, we have demonstrated that these SNPs are active against pathogenic fungi, such as Candida and Cryptococcus.
The 2nd DBCLS BioHackathon: interoperable bioinformatics Web services for integrated applications
2011-01-01
Background The interaction between biological researchers and the bioinformatics tools they use is still hampered by incomplete interoperability between such tools. To ensure interoperability initiatives are effectively deployed, end-user applications need to be aware of, and support, best practices and standards. Here, we report on an initiative in which software developers and genome biologists came together to explore and raise awareness of these issues: BioHackathon 2009. Results Developers in attendance came from diverse backgrounds, with experts in Web services, workflow tools, text mining and visualization. Genome biologists provided expertise and exemplar data from the domains of sequence and pathway analysis and glyco-informatics. One goal of the meeting was to evaluate the ability to address real world use cases in these domains using the tools that the developers represented. This resulted in i) a workflow to annotate 100,000 sequences from an invertebrate species; ii) an integrated system for analysis of the transcription factor binding sites (TFBSs) enriched based on differential gene expression data obtained from a microarray experiment; iii) a workflow to enumerate putative physical protein interactions among enzymes in a metabolic pathway using protein structure data; iv) a workflow to analyze glyco-gene-related diseases by searching for human homologs of glyco-genes in other species, such as fruit flies, and retrieving their phenotype-annotated SNPs. Conclusions Beyond deriving prototype solutions for each use-case, a second major purpose of the BioHackathon was to highlight areas of insufficiency. We discuss the issues raised by our exploration of the problem/solution space, concluding that there are still problems with the way Web services are modeled and annotated, including: i) the absence of several useful data or analysis functions in the Web service "space"; ii) the lack of documentation of methods; iii) lack of compliance with the SOAP/WSDL specification among and between various programming-language libraries; and iv) incompatibility between various bioinformatics data formats. Although it was still difficult to solve real world problems posed to the developers by the biological researchers in attendance because of these problems, we note the promise of addressing these issues within a semantic framework. PMID:21806842
The 2nd DBCLS BioHackathon: interoperable bioinformatics Web services for integrated applications.
Katayama, Toshiaki; Wilkinson, Mark D; Vos, Rutger; Kawashima, Takeshi; Kawashima, Shuichi; Nakao, Mitsuteru; Yamamoto, Yasunori; Chun, Hong-Woo; Yamaguchi, Atsuko; Kawano, Shin; Aerts, Jan; Aoki-Kinoshita, Kiyoko F; Arakawa, Kazuharu; Aranda, Bruno; Bonnal, Raoul Jp; Fernández, José M; Fujisawa, Takatomo; Gordon, Paul Mk; Goto, Naohisa; Haider, Syed; Harris, Todd; Hatakeyama, Takashi; Ho, Isaac; Itoh, Masumi; Kasprzyk, Arek; Kido, Nobuhiro; Kim, Young-Joo; Kinjo, Akira R; Konishi, Fumikazu; Kovarskaya, Yulia; von Kuster, Greg; Labarga, Alberto; Limviphuvadh, Vachiranee; McCarthy, Luke; Nakamura, Yasukazu; Nam, Yunsun; Nishida, Kozo; Nishimura, Kunihiro; Nishizawa, Tatsuya; Ogishima, Soichi; Oinn, Tom; Okamoto, Shinobu; Okuda, Shujiro; Ono, Keiichiro; Oshita, Kazuki; Park, Keun-Joon; Putnam, Nicholas; Senger, Martin; Severin, Jessica; Shigemoto, Yasumasa; Sugawara, Hideaki; Taylor, James; Trelles, Oswaldo; Yamasaki, Chisato; Yamashita, Riu; Satoh, Noriyuki; Takagi, Toshihisa
2011-08-02
The interaction between biological researchers and the bioinformatics tools they use is still hampered by incomplete interoperability between such tools. To ensure interoperability initiatives are effectively deployed, end-user applications need to be aware of, and support, best practices and standards. Here, we report on an initiative in which software developers and genome biologists came together to explore and raise awareness of these issues: BioHackathon 2009. Developers in attendance came from diverse backgrounds, with experts in Web services, workflow tools, text mining and visualization. Genome biologists provided expertise and exemplar data from the domains of sequence and pathway analysis and glyco-informatics. One goal of the meeting was to evaluate the ability to address real world use cases in these domains using the tools that the developers represented. This resulted in i) a workflow to annotate 100,000 sequences from an invertebrate species; ii) an integrated system for analysis of the transcription factor binding sites (TFBSs) enriched based on differential gene expression data obtained from a microarray experiment; iii) a workflow to enumerate putative physical protein interactions among enzymes in a metabolic pathway using protein structure data; iv) a workflow to analyze glyco-gene-related diseases by searching for human homologs of glyco-genes in other species, such as fruit flies, and retrieving their phenotype-annotated SNPs. Beyond deriving prototype solutions for each use-case, a second major purpose of the BioHackathon was to highlight areas of insufficiency. We discuss the issues raised by our exploration of the problem/solution space, concluding that there are still problems with the way Web services are modeled and annotated, including: i) the absence of several useful data or analysis functions in the Web service "space"; ii) the lack of documentation of methods; iii) lack of compliance with the SOAP/WSDL specification among and between various programming-language libraries; and iv) incompatibility between various bioinformatics data formats. Although it was still difficult to solve real world problems posed to the developers by the biological researchers in attendance because of these problems, we note the promise of addressing these issues within a semantic framework.
Graham, N.; Zeman, A.; Young, A.; Patterson, K.; Hodges, J.
1999-01-01
OBJECTIVES—To investigate the roles of visual and tactile information in a dyspraxic patient with corticobasal degeneration (CBD) who showed dramatic facilitation in miming the use of a tool or object when he was given a tool to manipulate; and to study the nature of the praxic and neuropsychological deficits in CBD. METHODS—The subject had clinically diagnosed CBD, and exhibited alien limb behaviour and striking ideomotor dyspraxia. General neuropsychological evaluation focused on constructional and visuospatial abilities, calculation, verbal fluency, episodic and semantic memory, plus spelling and writing because impairments in this domain were presenting complaints. Four experiments assessed the roles of visual and tactile information in the facilitation of motor performance by tools. Experiment 1 evaluated the patient's performance of six limb transitive actions under six conditions: (1) after he described the relevant tool from memory, (2) after he was shown a line drawing of the tool, (3) after he was shown a real exemplar of the tool, (4) after he watched the experimenter perform the action, (5) while he was holding the tool, and (6) immediately after he had performed the action with the tool but with the tool removed from his grasp. Experiment 2 evaluated the use of the same six tools when the patient had tactile but no visual information (while he was blindfolded). Experiments 3 and 4 assessed performance of actions appropriate to the same six tools when the patient had either neutral or inappropriate tactile feedback—that is, while he was holding a non-tool object or a different tool. RESULTS—Miming of tool use was not facilitated by visual input; moreover, lack of visual information in the blindfolded condition did not reduce performance. The principal positive finding was a dramatic facilitation of the patient's ability to demonstrate object use when he was holding either the appropriate tool or a neutral object. Tools inappropriate to the requested action produced involuntary performance of the stimulus relevant action. CONCLUSIONS—Tactile stimulation was paramount in the facilitation of motor performance in tool use by this patient with CBD. This outcome suggests that tactile information should be included in models which hypothesise modality specific inputs to the action production system. Significant impairments in spelling and letter production that have not previously been reported in CBD have also been documented. PMID:10449556
Impact of SNPs on Protein Phosphorylation Status in Rice (Oryza sativa L.).
Lin, Shoukai; Chen, Lijuan; Tao, Huan; Huang, Jian; Xu, Chaoqun; Li, Lin; Ma, Shiwei; Tian, Tian; Liu, Wei; Xue, Lichun; Ai, Yufang; He, Huaqin
2016-11-11
Single nucleotide polymorphisms (SNPs) are widely used in functional genomics and genetics research work. The high-quality sequence of rice genome has provided a genome-wide SNP and proteome resource. However, the impact of SNPs on protein phosphorylation status in rice is not fully understood. In this paper, we firstly updated rice SNP resource based on the new rice genome Ver. 7.0, then systematically analyzed the potential impact of Non-synonymous SNPs (nsSNPs) on the protein phosphorylation status. There were 3,897,312 SNPs in Ver. 7.0 rice genome, among which 9.9% was nsSNPs. Whilst, a total 2,508,261 phosphorylated sites were predicted in rice proteome. Interestingly, we observed that 150,197 (39.1%) nsSNPs could influence protein phosphorylation status, among which 52.2% might induce changes of protein kinase (PK) types for adjacent phosphorylation sites. We constructed a database, SNP_rice, to deposit the updated rice SNP resource and phosSNPs information. It was freely available to academic researchers at http://bioinformatics.fafu.edu.cn. As a case study, we detected five nsSNPs that potentially influenced heterotrimeric G proteins phosphorylation status in rice, indicating that genetic polymorphisms showed impact on the signal transduction by influencing the phosphorylation status of heterotrimeric G proteins. The results in this work could be a useful resource for future experimental identification and provide interesting information for better rice breeding.
The Mission Planning Lab: A Visualization and Analysis Tool
NASA Technical Reports Server (NTRS)
Daugherty, Sarah C.; Cervantes, Benjamin W.
2009-01-01
Simulation and visualization are powerful decision making tools that are time-saving and cost-effective. Space missions pose testing and e valuation challenges that can be overcome through modeling, simulatio n, and visualization of mission parameters. The National Aeronautics and Space Administration?s (NASA) Wallops Flight Facility (WFF) capi talizes on the benefits of modeling, simulation, and visualization to ols through a project initiative called The Mission Planning Lab (MPL ).
Exploratory Climate Data Visualization and Analysis Using DV3D and UVCDAT
NASA Technical Reports Server (NTRS)
Maxwell, Thomas
2012-01-01
Earth system scientists are being inundated by an explosion of data generated by ever-increasing resolution in both global models and remote sensors. Advanced tools for accessing, analyzing, and visualizing very large and complex climate data are required to maintain rapid progress in Earth system research. To meet this need, NASA, in collaboration with the Ultra-scale Visualization Climate Data Analysis Tools (UVCOAT) consortium, is developing exploratory climate data analysis and visualization tools which provide data analysis capabilities for the Earth System Grid (ESG). This paper describes DV3D, a UV-COAT package that enables exploratory analysis of climate simulation and observation datasets. OV3D provides user-friendly interfaces for visualization and analysis of climate data at a level appropriate for scientists. It features workflow inte rfaces, interactive 40 data exploration, hyperwall and stereo visualization, automated provenance generation, and parallel task execution. DV30's integration with CDAT's climate data management system (COMS) and other climate data analysis tools provides a wide range of high performance climate data analysis operations. DV3D expands the scientists' toolbox by incorporating a suite of rich new exploratory visualization and analysis methods for addressing the complexity of climate datasets.
McNally, Colin P.; Eng, Alexander; Noecker, Cecilia; Gagne-Maynard, William C.; Borenstein, Elhanan
2018-01-01
The abundance of both taxonomic groups and gene categories in microbiome samples can now be easily assayed via various sequencing technologies, and visualized using a variety of software tools. However, the assemblage of taxa in the microbiome and its gene content are clearly linked, and tools for visualizing the relationship between these two facets of microbiome composition and for facilitating exploratory analysis of their co-variation are lacking. Here we introduce BURRITO, a web tool for interactive visualization of microbiome multi-omic data with paired taxonomic and functional information. BURRITO simultaneously visualizes the taxonomic and functional compositions of multiple samples and dynamically highlights relationships between taxa and functions to capture the underlying structure of these data. Users can browse for taxa and functions of interest and interactively explore the share of each function attributed to each taxon across samples. BURRITO supports multiple input formats for taxonomic and metagenomic data, allows adjustment of data granularity, and can export generated visualizations as static publication-ready formatted figures. In this paper, we describe the functionality of BURRITO, and provide illustrative examples of its utility for visualizing various trends in the relationship between the composition of taxa and functions in complex microbiomes. PMID:29545787
A validated set of tool pictures with matched objects and non-objects for laterality research.
Verma, Ark; Brysbaert, Marc
2015-01-01
Neuropsychological and neuroimaging research has established that knowledge related to tool use and tool recognition is lateralized to the left cerebral hemisphere. Recently, behavioural studies with the visual half-field technique have confirmed the lateralization. A limitation of this research was that different sets of stimuli had to be used for the comparison of tools to other objects and objects to non-objects. Therefore, we developed a new set of stimuli containing matched triplets of tools, other objects and non-objects. With the new stimulus set, we successfully replicated the findings of no visual field advantage for objects in an object recognition task combined with a significant right visual field advantage for tools in a tool recognition task. The set of stimuli is available as supplemental data to this article.
Application of Multimedia Design Principles to Visuals Used in Course-Books: An Evaluation Tool
ERIC Educational Resources Information Center
Kuzu, Abdullah; Akbulut, Yavuz; Sahin, Mehmet Can
2007-01-01
This paper introduces an evaluation tool prepared to examine the quality of visuals in course-books. The tool is based on Mayer's Cognitive Theory of Multimedia Learning (i.e. Generative Theory) and its principles regarding the correct use of illustrations within text. The reason to generate the tool, the development process along with the…
Zhu, Qian-Hao; Spriggs, Andrew; Taylor, Jennifer M.; Llewellyn, Danny; Wilson, Iain
2014-01-01
Varietal single nucleotide polymorphisms (SNPs) are the differences within one of the two subgenomes between different tetraploid cotton varieties and have not been practically used in cotton genetics and breeding because they are difficult to identify due to low genetic diversity and very high sequence identity between homeologous genes in cotton. We have used transcriptome and restriction site−associated DNA sequencing to identify varietal SNPs among 18 G. hirsutum varieties based on the rationale that varietal SNPs can be more confidently called when flanked by subgenome-specific SNPs. Using transcriptome data, we successfully identified 37,413 varietal SNPs and, of these, 22,121 did not have an additional varietal SNP within their 20-bp flanking regions so can be used in most SNP genotyping assays. From restriction site−associated DNA sequencing data, we identified an additional 3090 varietal SNPs between two of the varieties. Of the 1583 successful SNP assays achieved using different genotyping platforms, 1363 were verified. Many of the SNPs behaved as dominant markers because of coamplification from homeologous loci, but the number of SNPs acting as codominant markers increased when one or more subgenome-specific SNP(s) were incorporated in their assay primers, giving them greater utility for breeding applications. A G. hirsutum genetic map with 1244 SNP markers was constructed covering 5557.42 centiMorgan and used to map qualitative and quantitative traits. This collection of G. hirsutum varietal SNPs complements existing intra-specific SNPs and provides the cotton community with a valuable marker resource applicable to genetic analyses and breeding programs. PMID:25106949
Cytoscape: the network visualization tool for GenomeSpace workflows.
Demchak, Barry; Hull, Tim; Reich, Michael; Liefeld, Ted; Smoot, Michael; Ideker, Trey; Mesirov, Jill P
2014-01-01
Modern genomic analysis often requires workflows incorporating multiple best-of-breed tools. GenomeSpace is a web-based visual workbench that combines a selection of these tools with mechanisms that create data flows between them. One such tool is Cytoscape 3, a popular application that enables analysis and visualization of graph-oriented genomic networks. As Cytoscape runs on the desktop, and not in a web browser, integrating it into GenomeSpace required special care in creating a seamless user experience and enabling appropriate data flows. In this paper, we present the design and operation of the Cytoscape GenomeSpace app, which accomplishes this integration, thereby providing critical analysis and visualization functionality for GenomeSpace users. It has been downloaded over 850 times since the release of its first version in September, 2013.
Cytoscape: the network visualization tool for GenomeSpace workflows
Demchak, Barry; Hull, Tim; Reich, Michael; Liefeld, Ted; Smoot, Michael; Ideker, Trey; Mesirov, Jill P.
2014-01-01
Modern genomic analysis often requires workflows incorporating multiple best-of-breed tools. GenomeSpace is a web-based visual workbench that combines a selection of these tools with mechanisms that create data flows between them. One such tool is Cytoscape 3, a popular application that enables analysis and visualization of graph-oriented genomic networks. As Cytoscape runs on the desktop, and not in a web browser, integrating it into GenomeSpace required special care in creating a seamless user experience and enabling appropriate data flows. In this paper, we present the design and operation of the Cytoscape GenomeSpace app, which accomplishes this integration, thereby providing critical analysis and visualization functionality for GenomeSpace users. It has been downloaded over 850 times since the release of its first version in September, 2013. PMID:25165537
Belle2VR: A Virtual-Reality Visualization of Subatomic Particle Physics in the Belle II Experiment.
Duer, Zach; Piilonen, Leo; Glasson, George
2018-05-01
Belle2VR is an interactive virtual-reality visualization of subatomic particle physics, designed by an interdisciplinary team as an educational tool for learning about and exploring subatomic particle collisions. This article describes the tool, discusses visualization design decisions, and outlines our process for collaborative development.
Learner-Information Interaction: A Macro-Level Framework Characterizing Visual Cognitive Tools
ERIC Educational Resources Information Center
Sedig, Kamran; Liang, Hai-Ning
2008-01-01
Visual cognitive tools (VCTs) are external mental aids that maintain and display visual representations (VRs) of information (i.e., structures, objects, concepts, ideas, and problems). VCTs allow learners to operate upon the VRs to perform epistemic (i.e., reasoning and knowledge-based) activities. In VCTs, the mechanism by which learners operate…
Visual Data Comm: A Tool for Visualizing Data Communication in the Multi Sector Planner Study
NASA Technical Reports Server (NTRS)
Lee, Hwasoo Eric
2010-01-01
Data comm is a new technology proposed in future air transport system as a potential tool to provide comprehensive data connectivity. It is a key enabler to manage 4D trajectory digitally, potentially resulting in improved flight times and increased throughput. Future concepts with data comm integration have been tested in a number of human-in-the-loop studies but analyzing the results has proven to be particularly challenging because future traffic environment in which data comm is fully enabled has assumed high traffic density, resulting in data set with large amount of information. This paper describes the motivation, design, current and potential future application of Visual Data Comm (VDC), a tool for visualizing data developed in Java using Processing library which is a tool package designed for interactive visualization programming. This paper includes an example of an application of VDC on data pertaining to the most recent Multi Sector Planner study, conducted at NASA s Airspace Operations Laboratory in 2009, in which VDC was used to visualize and interpret data comm activities
Norheim, Katrine Brække; Le Hellard, Stephanie; Nordmark, Gunnel; Harboe, Erna; Gøransson, Lasse; Brun, Johan G; Wahren-Herlenius, Marie; Jonsson, Roland; Omdal, Roald
2014-02-01
Fatigue is prevalent and disabling in primary Sjögren's syndrome (pSS). Results from studies in chronic fatigue syndrome (CFS) indicate that genetic variation may influence fatigue. The aim of this study was to investigate single nucleotide polymorphism (SNP) variations in pSS patients with high and low fatigue. A panel of 85 SNPs in 12 genes was selected based on previous studies in CFS. A total of 207 pSS patients and 376 healthy controls were genotyped. One-hundred and ninety-three patients and 70 SNPs in 11 genes were available for analysis after quality control. Patients were dichotomized based on fatigue visual analogue scale (VAS) scores, with VAS <50 denominated "low fatigue" (n = 53) and VAS ≥50 denominated "high fatigue" (n = 140). We detected signals of association with pSS for one SNP in SLC25A40 (unadjusted p = 0.007) and two SNPs in PKN1 (both p = 0.03) in our pSS case versus control analysis. The association with SLC25A40 was stronger when only pSS high fatigue patients were analysed versus controls (p = 0.002). One SNP in PKN1 displayed an association in the case-only analysis of pSS high fatigue versus pSS low fatigue (p = 0.005). This candidate gene study in pSS did reveal a trend for associations between genetic variation in candidate genes and fatigue. The results will need to be replicated. More research on genetic associations with fatigue is warranted, and future trials should include larger cohorts and multicentre collaborations with sharing of genetic material to increase the statistical power.
Troggio, Michela; Surbanovski, Nada; Bianco, Luca; Moretto, Marco; Giongo, Lara; Banchi, Elisa; Viola, Roberto; Fernández, Felicdad Fernández; Costa, Fabrizio; Velasco, Riccardo; Cestaro, Alessandro; Sargent, Daniel James
2013-01-01
High throughput arrays for the simultaneous genotyping of thousands of single-nucleotide polymorphisms (SNPs) have made the rapid genetic characterisation of plant genomes and the development of saturated linkage maps a realistic prospect for many plant species of agronomic importance. However, the correct calling of SNP genotypes in divergent polyploid genomes using array technology can be problematic due to paralogy, and to divergence in probe sequences causing changes in probe binding efficiencies. An Illumina Infinium II whole-genome genotyping array was recently developed for the cultivated apple and used to develop a molecular linkage map for an apple rootstock progeny (M432), but a large proportion of segregating SNPs were not mapped in the progeny, due to unexpected genotype clustering patterns. To investigate the causes of this unexpected clustering we performed BLAST analysis of all probe sequences against the 'Golden Delicious' genome sequence and discovered evidence for paralogous annealing sites and probe sequence divergence for a high proportion of probes contained on the array. Following visual re-evaluation of the genotyping data generated for 8,788 SNPs for the M432 progeny using the array, we manually re-scored genotypes at 818 loci and mapped a further 797 markers to the M432 linkage map. The newly mapped markers included the majority of those that could not be mapped previously, as well as loci that were previously scored as monomorphic, but which segregated due to divergence leading to heterozygosity in probe annealing sites. An evaluation of the 8,788 probes in a diverse collection of Malus germplasm showed that more than half the probes returned genotype clustering patterns that were difficult or impossible to interpret reliably, highlighting implications for the use of the array in genome-wide association studies.
No association of dynamin binding protein (DNMBP) gene SNPs and Alzheimer's disease.
Minster, Ryan L; DeKosky, Steven T; Kamboh, M Ilyas
2008-10-01
A recent scan of single nucleotide polymorphisms (SNPs) on chromosome 10q found significant association of six correlated SNPs with late-onset Alzheimer's disease (AD) among Japanese. We examined the SNP with the highest statistical significance (rs3740058) in a large Caucasian American case-control cohort and the remaining five SNPs in a smaller subset of cases and controls. We observed no association of statistical significance in either the total sample or the APOE*4 non-carriers for any of the SNPs.
Augmenting white cane reliability using smart glove for visually impaired people.
Bernieri, Giuseppe; Faramondi, Luca; Pascucci, Federica
2015-08-01
The independent mobility problem of visually impaired people has been an active research topic in biomedical engineering: although many smart tools have been proposed, traditional tools (e.g., the white cane) continue to play a prominent role. In this paper a low cost smart glove is presented: the key idea is to minimize the impact in using it by combining the traditional tools with a technological device able to improve the movement performance of the visually impaired people.
Spacecraft Guidance, Navigation, and Control Visualization Tool
NASA Technical Reports Server (NTRS)
Mandic, Milan; Acikmese, Behcet; Blackmore, Lars
2011-01-01
G-View is a 3D visualization tool for supporting spacecraft guidance, navigation, and control (GN&C) simulations relevant to small-body exploration and sampling (see figure). The tool is developed in MATLAB using Virtual Reality Toolbox and provides users with the ability to visualize the behavior of their simulations, regardless of which programming language (or machine) is used to generate simulation results. The only requirement is that multi-body simulation data is generated and placed in the proper format before applying G-View.
Interactive visualization of public health indicators to support policymaking: An exploratory study
Zakkar, Moutasem; Sedig, Kamran
2017-01-01
Purpose The purpose of this study is to examine the use of interactive visualizations to represent data/information related to social determinants of health and public health indicators, and to investigate the benefits of such visualizations for health policymaking. Methods: The study developed a prototype for an online interactive visualization tool that represents the social determinants of health. The study participants explored and used the tool. The tool was evaluated using the informal user experience evaluation method. This method involves the prospective users of a tool to use and play with it and their feedback to be collected through interviews. Results: Using visualizations to represent and interact with health indicators has advantages over traditional representation techniques that do not allow users to interact with the information. Communicating healthcare indicators to policymakers is a complex task because of the complexity of the indicators, diversity of audiences, and different audience needs. This complexity can lead to information misinterpretation, which occurs when users of the health data ignore or do not know why, where, and how the data has been produced, or where and how it can be used. Conclusions: Public health policymaking is a complex process, and data is only one element among others needed in this complex process. Researchers and healthcare organizations should conduct a strategic evaluation to assess the usability of interactive visualizations and decision support tools before investing in these tools. Such evaluation should take into consideration the cost, ease of use, learnability, and efficiency of those tools, and the factors that influence policymaking. PMID:29026455
NASA Astrophysics Data System (ADS)
Singh, Tej; Shekhawat, Dharmender Singh; Jyoti, Kumari
2018-05-01
The synthesis of silver nanoparticles (SNPs) by chemical and physical methods produce harmful products which may cause various environmental problems, thus, there is an increasing demand to use ecofriendly methods. Therefore, biosynthesis of SNPs using Justicia adhatoda flower extract is demonstrated in the present study. The biosynthesized SNPs were characterized by UV-visible spectroscopy, Fourier transform-infrared spectroscopy (FTIR), transmission electron microscopy (TEM), selected area electron diffraction (SAED) and atomic force microscopy (AFM) analysis. The result of UV-visible spectroscopy peaked at 417 nm corresponding to the plasmon absorbance of SNPs. The TEM and SAED result reveals the crystalline nature of SNPs. FTIR spectroscopy used to identify the possible biomolecules responsible for the conversion of silver ions to SNPs. The study concluded that Justicia adhatoda flower extract act as an excellent reducing agent and the green synthesized SNPs are safer to the environment.
Fernandez, Nicolas F.; Gundersen, Gregory W.; Rahman, Adeeb; Grimes, Mark L.; Rikova, Klarisa; Hornbeck, Peter; Ma’ayan, Avi
2017-01-01
Most tools developed to visualize hierarchically clustered heatmaps generate static images. Clustergrammer is a web-based visualization tool with interactive features such as: zooming, panning, filtering, reordering, sharing, performing enrichment analysis, and providing dynamic gene annotations. Clustergrammer can be used to generate shareable interactive visualizations by uploading a data table to a web-site, or by embedding Clustergrammer in Jupyter Notebooks. The Clustergrammer core libraries can also be used as a toolkit by developers to generate visualizations within their own applications. Clustergrammer is demonstrated using gene expression data from the cancer cell line encyclopedia (CCLE), original post-translational modification data collected from lung cancer cells lines by a mass spectrometry approach, and original cytometry by time of flight (CyTOF) single-cell proteomics data from blood. Clustergrammer enables producing interactive web based visualizations for the analysis of diverse biological data. PMID:28994825
Visual analytics for aviation safety: A collaborative approach to sensemaking
NASA Astrophysics Data System (ADS)
Wade, Andrew
Visual analytics, the "science of analytical reasoning facilitated by interactive visual interfaces", is more than just visualization. Understanding the human reasoning process is essential for designing effective visualization tools and providing correct analyses. This thesis describes the evolution, application and evaluation of a new method for studying analytical reasoning that we have labeled paired analysis. Paired analysis combines subject matter experts (SMEs) and tool experts (TE) in an analytic dyad, here used to investigate aircraft maintenance and safety data. The method was developed and evaluated using interviews, pilot studies and analytic sessions during an internship at the Boeing Company. By enabling a collaborative approach to sensemaking that can be captured by researchers, paired analysis yielded rich data on human analytical reasoning that can be used to support analytic tool development and analyst training. Keywords: visual analytics, paired analysis, sensemaking, boeing, collaborative analysis.
Evolutionary evidence of the effect of rare variants on disease etiology.
Gorlov, I P; Gorlova, O Y; Frazier, M L; Spitz, M R; Amos, C I
2011-03-01
The common disease/common variant hypothesis has been popular for describing the genetic architecture of common human diseases for several years. According to the originally stated hypothesis, one or a few common genetic variants with a large effect size control the risk of common diseases. A growing body of evidence, however, suggests that rare single-nucleotide polymorphisms (SNPs), i.e. those with a minor allele frequency of less than 5%, are also an important component of the genetic architecture of common human diseases. In this study, we analyzed the relevance of rare SNPs to the risk of common diseases from an evolutionary perspective and found that rare SNPs are more likely than common SNPs to be functional and tend to have a stronger effect size than do common SNPs. This observation, and the fact that most of the SNPs in the human genome are rare, suggests that rare SNPs are a crucial element of the genetic architecture of common human diseases. We propose that the next generation of genomic studies should focus on analyzing rare SNPs. Further, targeting patients with a family history of the disease, an extreme phenotype, or early disease onset may facilitate the detection of risk-associated rare SNPs. © 2010 John Wiley & Sons A/S.
Sabir, Aneela; Shafiq, Muhammad; Islam, Atif; Jabeen, Faiza; Shafeeq, Amir; Ahmad, Adnan; Zahid Butt, Muhammad Taqi; Jacob, Karl I; Jamil, Tahir
2016-01-20
Thermally-induced phase separation (TIPS) method was used to synthesize polymer matrix (PM) membranes for reverse osmosis from cellulose acetate/polyethylene glycol (CA/PEG300) conjugated with silica nanoparticles (SNPs). Experimental data showed that the conjugation of SNPs changed the surface properties as dense and asymmetric composite structure. The results were explicitly determined by the permeability flux and salt rejection efficiency of the PM-SNPs membranes. The effect of SNPs conjugation on MgSO4 salt rejection was more significant in magnitude than on permeation flux i.e. 2.38 L/m(2)h. FTIR verified that SNPs were successfully conjugated on the surface of PM membrane. DSC of PM-SNPs shows an improved Tg from 76.2 to 101.8 °C for PM and PM-S4 respectively. Thermal stability of the PM-SNPs membranes was observed by TGA which was significantly enhanced with the conjugation of SNPs. The micrographs of SEM and AFM showed the morphological changes and increase in the valley and ridges on membrane surface. Experimental data showed that the PM-S4 (0.4 wt% SNPs) membrane has maximum salt rejection capacity and was selected as an optimal membrane. Copyright © 2015 Elsevier Ltd. All rights reserved.
Vallée Marcotte, Bastien; Cormier, Hubert; Guénard, Frédéric; Rudkowska, Iwona; Lemieux, Simone; Couture, Patrick; Vohl, Marie-Claude
2016-01-01
A recent genome-wide association study (GWAS) by our group identified 13 loci associated with the plasma triglyceride (TG) response to omega-3 (n-3) fatty acid (FA) supplementation. This study aimed to test whether single-nucleotide polymorphisms (SNPs) within the IQCJ, NXPH1, PHF17 and MYB genes are associated with the plasma TG response to an n-3 FA supplementation. A total of 208 subjects followed a 6-week n-3 FA supplementation of 5 g/day of fish oil (1.9-2.2 g of eicosapentaenoic acid and 1.1 g of docosahexaenoic acid). Measurements of plasma lipids were made before and after the supplementation. Sixty-seven tagged SNPs were selected to increase the density of markers near GWAS hits. In a repeated model, independent effects of the genotype and the gene-supplementation interaction were associated with plasma TG. Genotype effects were observed with two SNPs of NXPH1, and gene-diet interactions were observed with ten SNPs of IQCJ, four SNPs of NXPH1 and three SNPs of MYB. Positive and negative responders showed different genotype frequencies with nine SNPs of IQCJ, two SNPs of NXPH1 and two SNPs of MYB. Fine mapping in GWAS-associated loci allowed the identification of SNPs partly explaining the large interindividual variability observed in plasma TG levels in response to an n-3 FA supplementation. © 2016 S. Karger AG, Basel.
Linkage Disequilibrium and Inversion-Typing of the Drosophila melanogaster Genome Reference Panel
Houle, David; Márquez, Eladio J.
2015-01-01
We calculated the linkage disequilibrium between all pairs of variants in the Drosophila Genome Reference Panel with minor allele count ≥5. We used r2 ≥ 0.5 as the cutoff for a highly correlated SNP. We make available the list of all highly correlated SNPs for use in association studies. Seventy-six percent of variant SNPs are highly correlated with at least one other SNP, and the mean number of highly correlated SNPs per variant over the whole genome is 83.9. Disequilibrium between distant SNPs is also common when minor allele frequency (MAF) is low: 37% of SNPs with MAF < 0.1 are highly correlated with SNPs more than 100 kb distant. Although SNPs within regions with polymorphic inversions are highly correlated with somewhat larger numbers of SNPs, and these correlated SNPs are on average farther away, the probability that a SNP in such regions is highly correlated with at least one other SNP is very similar to SNPs outside inversions. Previous karyotyping of the DGRP lines has been inconsistent, and we used LD and genotype to investigate these discrepancies. When previous studies agreed on inversion karyotype, our analysis was almost perfectly concordant with those assignments. In discordant cases, and for inversion heterozygotes, our results suggest errors in two previous analyses or discordance between genotype and karyotype. Heterozygosities of chromosome arms are, in many cases, surprisingly highly correlated, suggesting strong epsistatic selection during the inbreeding and maintenance of the DGRP lines. PMID:26068573
Bipartite Community Structure of eQTLs.
Platig, John; Castaldi, Peter J; DeMeo, Dawn; Quackenbush, John
2016-09-01
Genome Wide Association Studies (GWAS) and expression quantitative trait locus (eQTL) analyses have identified genetic associations with a wide range of human phenotypes. However, many of these variants have weak effects and understanding their combined effect remains a challenge. One hypothesis is that multiple SNPs interact in complex networks to influence functional processes that ultimately lead to complex phenotypes, including disease states. Here we present CONDOR, a method that represents both cis- and trans-acting SNPs and the genes with which they are associated as a bipartite graph and then uses the modular structure of that graph to place SNPs into a functional context. In applying CONDOR to eQTLs in chronic obstructive pulmonary disease (COPD), we found the global network "hub" SNPs were devoid of disease associations through GWAS. However, the network was organized into 52 communities of SNPs and genes, many of which were enriched for genes in specific functional classes. We identified local hubs within each community ("core SNPs") and these were enriched for GWAS SNPs for COPD and many other diseases. These results speak to our intuition: rather than single SNPs influencing single genes, we see groups of SNPs associated with the expression of families of functionally related genes and that disease SNPs are associated with the perturbation of those functions. These methods are not limited in their application to COPD and can be used in the analysis of a wide variety of disease processes and other phenotypic traits.
Screening and Evaluation of Deleterious SNPs in APOE Gene of Alzheimer's Disease.
Masoodi, Tariq Ahmad; Al Shammari, Sulaiman A; Al-Muammar, May N; Alhamdan, Adel A
2012-01-01
Introduction. Apolipoprotein E (APOE) is an important risk factor for Alzheimer's disease (AD) and is present in 30-50% of patients who develop late-onset AD. Several single-nucleotide polymorphisms (SNPs) are present in APOE gene which act as the biomarkers for exploring the genetic basis of this disease. The objective of this study is to identify deleterious nsSNPs associated with APOE gene. Methods. The SNPs were retrieved from dbSNP. Using I-Mutant, protein stability change was calculated. The potentially functional nonsynonymous (ns) SNPs and their effect on protein was predicted by PolyPhen and SIFT, respectively. FASTSNP was used for functional analysis and estimation of risk score. The functional impact on the APOE protein was evaluated by using Swiss PDB viewer and NOMAD-Ref server. Results. Six nsSNPs were found to be least stable by I-Mutant 2.0 with DDG value of >-1.0. Four nsSNPs showed a highly deleterious tolerance index score of 0.00. Nine nsSNPs were found to be probably damaging with position-specific independent counts (PSICs) score of ≥2.0. Seven nsSNPs were found to be highly polymorphic with a risk score of 3-4. The total energies and root-mean-square deviation (RMSD) values were higher for three mutant-type structures compared to the native modeled structure. Conclusion. We concluded that three nsSNPs, namely, rs11542041, rs11542040, and rs11542034, to be potentially functional polymorphic.
Linkage Disequilibrium and Inversion-Typing of the Drosophila melanogaster Genome Reference Panel.
Houle, David; Márquez, Eladio J
2015-06-10
We calculated the linkage disequilibrium between all pairs of variants in the Drosophila Genome Reference Panel with minor allele count ≥5. We used r(2) ≥ 0.5 as the cutoff for a highly correlated SNP. We make available the list of all highly correlated SNPs for use in association studies. Seventy-six percent of variant SNPs are highly correlated with at least one other SNP, and the mean number of highly correlated SNPs per variant over the whole genome is 83.9. Disequilibrium between distant SNPs is also common when minor allele frequency (MAF) is low: 37% of SNPs with MAF < 0.1 are highly correlated with SNPs more than 100 kb distant. Although SNPs within regions with polymorphic inversions are highly correlated with somewhat larger numbers of SNPs, and these correlated SNPs are on average farther away, the probability that a SNP in such regions is highly correlated with at least one other SNP is very similar to SNPs outside inversions. Previous karyotyping of the DGRP lines has been inconsistent, and we used LD and genotype to investigate these discrepancies. When previous studies agreed on inversion karyotype, our analysis was almost perfectly concordant with those assignments. In discordant cases, and for inversion heterozygotes, our results suggest errors in two previous analyses or discordance between genotype and karyotype. Heterozygosities of chromosome arms are, in many cases, surprisingly highly correlated, suggesting strong epsistatic selection during the inbreeding and maintenance of the DGRP lines. Copyright © 2015 Houle and Márquez.
Igloo-Plot: a tool for visualization of multidimensional datasets.
Kuntal, Bhusan K; Ghosh, Tarini Shankar; Mande, Sharmila S
2014-01-01
Advances in science and technology have resulted in an exponential growth of multivariate (or multi-dimensional) datasets which are being generated from various research areas especially in the domain of biological sciences. Visualization and analysis of such data (with the objective of uncovering the hidden patterns therein) is an important and challenging task. We present a tool, called Igloo-Plot, for efficient visualization of multidimensional datasets. The tool addresses some of the key limitations of contemporary multivariate visualization and analysis tools. The visualization layout, not only facilitates an easy identification of clusters of data-points having similar feature compositions, but also the 'marker features' specific to each of these clusters. The applicability of the various functionalities implemented herein is demonstrated using several well studied multi-dimensional datasets. Igloo-Plot is expected to be a valuable resource for researchers working in multivariate data mining studies. Igloo-Plot is available for download from: http://metagenomics.atc.tcs.com/IglooPlot/. Copyright © 2014 Elsevier Inc. All rights reserved.
Tan, Xiang-Lin; Moyer, Ann M.; Fridley, Brooke L.; Schaid, Daniel J.; Niu, Nifang; Batzler, Anthony J.; Jenkins, Gregory D.; Abo, Ryan P.; Li, Liang; Cunningham, Julie M.; Sun, Zhifu; Yang, Ping; Wang, Liewei
2011-01-01
Purpose Inherited variability in the prognosis of lung cancer patients treated with platinum-based chemotherapy has been widely investigated. However, the overall contribution of genetic variation to platinum response is not well established. To identify novel candidate SNPs/genes, we performed a genome-wide association study (GWAS) for cisplatin cytotoxicity using lymphoblastoid cell lines (LCLs), followed by an association study of selected SNPs from the GWAS with overall survival (OS) in lung cancer patients. Experimental Design GWAS for cisplatin were performed with 283 ethnically diverse LCLs. 168 top SNPs were genotyped in 222 small cell and 961 non-small cell lung cancer (SCLC, NSCLC) patients treated with platinum-based therapy. Association of the SNPs with OS was determined using the Cox regression model. Selected candidate genes were functionally validated by siRNA knockdown in human lung cancer cells. Results Among 157 successfully genotyped SNPs, 9 and 10 SNPs were top SNPs associated with OS for patients with NSCLC and SCLC, respectively, although they were not significant after adjusting for multiple testing. Fifteen genes, including 7 located within 200 kb up or downstream of the four top SNPs and 8 genes for which expression was correlated with three SNPs in LCLs were selected for siRNA screening. Knockdown of DAPK3 and METTL6, for which expression levels were correlated with the rs11169748 and rs2440915 SNPs, significantly decreased cisplatin sensitivity in lung cancer cells. Conclusions This series of clinical and complementary laboratory-based functional studies identified several candidate genes/SNPs that might help predict treatment outcomes for platinum-based therapy of lung cancer. PMID:21775533
Geographic differences in allele frequencies of susceptibility SNPs for cardiovascular disease
2011-01-01
Background We hypothesized that the frequencies of risk alleles of SNPs mediating susceptibility to cardiovascular diseases differ among populations of varying geographic origin and that population-specific selection has operated on some of these variants. Methods From the database of genome-wide association studies (GWAS), we selected 36 cardiovascular phenotypes including coronary heart disease, hypertension, and stroke, as well as related quantitative traits (eg, body mass index and plasma lipid levels). We identified 292 SNPs in 270 genes associated with a disease or trait at P < 5 × 10-8. As part of the Human Genome-Diversity Project (HGDP), 158 (54.1%) of these SNPs have been genotyped in 938 individuals belonging to 52 populations from seven geographic areas. A measure of population differentiation, FST, was calculated to quantify differences in risk allele frequencies (RAFs) among populations and geographic areas. Results Large differences in RAFs were noted in populations of Africa, East Asia, America and Oceania, when compared with other geographic regions. The mean global FST (0.1042) for 158 SNPs among the populations was not significantly higher than the mean global FST of 158 autosomal SNPs randomly sampled from the HGDP database. Significantly higher global FST (P < 0.05) was noted in eight SNPs, based on an empirical distribution of global FST of 2036 putatively neutral SNPs. For four of these SNPs, additional evidence of selection was noted based on the integrated Haplotype Score. Conclusion Large differences in RAFs for a set of common SNPs that influence risk of cardiovascular disease were noted between the major world populations. Pairwise comparisons revealed RAF differences for at least eight SNPs that might be due to population-specific selection or demographic factors. These findings are relevant to a better understanding of geographic variation in the prevalence of cardiovascular disease. PMID:21507254
Mahmood, Khalid; Højland, Dorte H; Asp, Torben; Kristensen, Michael
2016-01-01
Insecticide resistance in the housefly, Musca domestica, has been investigated for more than 60 years. It will enter a new era after the recent publication of the housefly genome and the development of multiple next generation sequencing technologies. The genetic background of the xenobiotic response can now be investigated in greater detail. Here, we investigate the 454-pyrosequencing transcriptome of the spinosad-resistant 791spin strain in relation to the housefly genome with focus on P450 genes. The de novo assembly of clean reads gave 35,834 contigs consisting of 21,780 sequences of the spinosad resistant strain. The 3,648 sequences were annotated with an enzyme code EC number and were mapped to 124 KEGG pathways with metabolic processes as most highly represented pathway. One hundred and twenty contigs were annotated as P450s covering 44 different P450 genes of housefly. Eight differentially expressed P450s genes were identified and investigated for SNPs, CpG islands and common regulatory motifs in promoter and coding regions. Functional annotation clustering of metabolic related genes and motif analysis of P450s revealed their association with epigenetic, transcription and gene expression related functions. The sequence variation analysis resulted in 12 SNPs and eight of them found in cyp6d1. There is variation in location, size and frequency of CpG islands and specific motifs were also identified in these P450s. Moreover, identified motifs were associated to GO terms and transcription factors using bioinformatic tools. Transcriptome data of a spinosad resistant strain provide together with genome data fundamental support for future research to understand evolution of resistance in houseflies. Here, we report for the first time the SNPs, CpG islands and common regulatory motifs in differentially expressed P450s. Taken together our findings will serve as a stepping stone to advance understanding of the mechanism and role of P450s in xenobiotic detoxification.
Impact of pre-imputation SNP-filtering on genotype imputation results
2014-01-01
Background Imputation of partially missing or unobserved genotypes is an indispensable tool for SNP data analyses. However, research and understanding of the impact of initial SNP-data quality control on imputation results is still limited. In this paper, we aim to evaluate the effect of different strategies of pre-imputation quality filtering on the performance of the widely used imputation algorithms MaCH and IMPUTE. Results We considered three scenarios: imputation of partially missing genotypes with usage of an external reference panel, without usage of an external reference panel, as well as imputation of completely un-typed SNPs using an external reference panel. We first created various datasets applying different SNP quality filters and masking certain percentages of randomly selected high-quality SNPs. We imputed these SNPs and compared the results between the different filtering scenarios by using established and newly proposed measures of imputation quality. While the established measures assess certainty of imputation results, our newly proposed measures focus on the agreement with true genotypes. These measures showed that pre-imputation SNP-filtering might be detrimental regarding imputation quality. Moreover, the strongest drivers of imputation quality were in general the burden of missingness and the number of SNPs used for imputation. We also found that using a reference panel always improves imputation quality of partially missing genotypes. MaCH performed slightly better than IMPUTE2 in most of our scenarios. Again, these results were more pronounced when using our newly defined measures of imputation quality. Conclusion Even a moderate filtering has a detrimental effect on the imputation quality. Therefore little or no SNP filtering prior to imputation appears to be the best strategy for imputing small to moderately sized datasets. Our results also showed that for these datasets, MaCH performs slightly better than IMPUTE2 in most scenarios at the cost of increased computing time. PMID:25112433
Vinitha, A; Kutty, V Raman; Vivekanand, A; Reshmi, G; Divya, G; Sumi, S; Santosh, K R; Pratapachandran, N S; Ajit, Mullassari S; Kartha, C C; Ramachandran, Surya
2016-01-01
Plasma level of cyclophilin A is a promising marker of vascular disease in patients with type 2 diabetes. Genetic variants in the peptidylprolyl isomerase A gene, encoding human cyclophilin may alter protein synthesis thus affecting its activity, function, and circulating plasma levels. We examined the effect of single-nucleotide polymorphisms (SNPs) within the PPIA gene on plasma levels of cyclophilin A and coupled this with status of vascular disease in patients with and without type 2 diabetes in 212 South Indian subjects. The regulatory region of PPIA gene was sequenced for SNPs. The association of SNPs with known blood markers of type 2 diabetes and coronary artery disease such as HbA1c, low- and high-density lipoproteins, triglycerides, fasting and postprandial blood sugar levels, and cyclophilin A were probed. We identified three SNPs namely, rs6850: A > G; (AG/-) c.*227_*228delAG and (-/T) c.*318_*319insT. Welchs two-sample t test indicated an association of SNP rs6850: A > G, located at the 5' UTR region with increased plasma levels of cyclophilin A in patients with coronary artery disease and with coronary artery disease associated with diabetes. The presence of rs6850: A > G variant was significantly associated with coronary artery disease irrespective of whether the patients had diabetes or not. In silico analysis of the sequence using different tools and matrix libraries did not predict any significant differential binding sites for rs6850: A > G, c.*227_*228delAG and c.*318_*319insT. Our results indicate that the SNP rs6850: A > G is associated with increased risk for elevated plasma levels of cyclophilin A and coronary artery disease in patients with and without type 2 diabetes.
CloVR-Comparative: automated, cloud-enabled comparative microbial genome sequence analysis pipeline.
Agrawal, Sonia; Arze, Cesar; Adkins, Ricky S; Crabtree, Jonathan; Riley, David; Vangala, Mahesh; Galens, Kevin; Fraser, Claire M; Tettelin, Hervé; White, Owen; Angiuoli, Samuel V; Mahurkar, Anup; Fricke, W Florian
2017-04-27
The benefit of increasing genomic sequence data to the scientific community depends on easy-to-use, scalable bioinformatics support. CloVR-Comparative combines commonly used bioinformatics tools into an intuitive, automated, and cloud-enabled analysis pipeline for comparative microbial genomics. CloVR-Comparative runs on annotated complete or draft genome sequences that are uploaded by the user or selected via a taxonomic tree-based user interface and downloaded from NCBI. CloVR-Comparative runs reference-free multiple whole-genome alignments to determine unique, shared and core coding sequences (CDSs) and single nucleotide polymorphisms (SNPs). Output includes short summary reports and detailed text-based results files, graphical visualizations (phylogenetic trees, circular figures), and a database file linked to the Sybil comparative genome browser. Data up- and download, pipeline configuration and monitoring, and access to Sybil are managed through CloVR-Comparative web interface. CloVR-Comparative and Sybil are distributed as part of the CloVR virtual appliance, which runs on local computers or the Amazon EC2 cloud. Representative datasets (e.g. 40 draft and complete Escherichia coli genomes) are processed in <36 h on a local desktop or at a cost of <$20 on EC2. CloVR-Comparative allows anybody with Internet access to run comparative genomics projects, while eliminating the need for on-site computational resources and expertise.
Pruna, Ricard; Ribas, Jordi; Montoro, Jose Bruno; Artells, Rosa
2015-02-02
The prevention, diagnosis, and management of non-contact musculoskeletal soft tissue injuries (NCMSTIs) related to participation in sports are key components of sport and exercise medicine. Epidemiological data have demonstrated the existence of interindividual differences in the severity of NCMSTIs, indicating that these injuries occur as a consequence of both extrinsic and intrinsic factors, including genetic variations. We have collected data on NCMSTIs suffered by 73 elite players of White, black African and Hispanic ethnicity of European football over the course of three consecutive seasons. We have also examined eight single nucleotide polymorphisms (SNPs) in genes related to tissue recovery and tissue repair in blood drawn from the players and correlated our findings with type and severity of injuries in each ethnic group. The frequency of the SNPs varied among the three ethnic sub-groups (p<0.0001). Among Whites, a significant relationship was observed between ligament injuries and ELN (p=0.001) and between tendinous injuries and ELN (p=0.05) and IGF2 (p=0.05). Among Hispanics, there was a significant relation between muscle injuries and ELN (p=0.032) and IGF2 (p=0.016). Interracial genotypic differences may be important in the study of NCMSTIs. A genetic profile based on SNPs may be useful tool to describe each individual's injuribility risk and provide specific treatment and preventive care for football players. Copyright © 2013 Elsevier España, S.L.U. All rights reserved.
De Wit, Pierre; Palumbi, Stephen R
2013-06-01
Global climate change is projected to accelerate during the next century, altering oceanic patterns in temperature, pH and oxygen concentrations. Documenting patterns of genetic adaptation to these variables in locations that currently experience geographic variation in them is an important tool in understanding the potential for natural selection to allow populations to adapt as climate change proceeds. We sequenced the mantle transcriptome of 39 red abalone (Haliotis rufescens) individuals from three regions (Monterey Bay, Sonoma, north of Cape Mendocino) distinct in temperature, aragonite saturation, exposure to hypoxia and disease pressure along the California coast. Among 1.17 × 10(6) Single Nucleotide Polymorphisms (SNPs) identified in this study (1.37% of the transcriptome), 21 579 could be genotyped for all individuals. A principal components analysis concluded that the vast majority of SNPs show no population structure from Monterey, California to the Oregon border, in corroboration with several previous studies. In contrast, an FST outlier analysis indicated 691 SNPs as exhibiting significantly higher than expected differentiation (experiment-wide P < 0.05). From these, it was possible to identify 163 genes through BLAST annotation, 34 of which contained more than one outlier SNP. A large number of these genes are involved in biomineralization, energy metabolism, heat-, disease- or hypoxia-tolerance. These genes are candidate loci for spatial adaptation to geographic variation that is likely to increase in the future. © 2012 John Wiley & Sons Ltd.
Guo, Jie; Shi, Weiping; Zhang, Zheng; Cheng, Jingye; Sun, Daizhen; Yu, Jin; Li, Xinlei; Guo, Pingyi; Hao, Chenyang
2018-02-20
Yield improvement is an ever-important objective of wheat breeding. Studying and understanding the phenotypes and genotypes of yield-related traits has potential for genetic improvement of crops. The genotypes of 215 wheat cultivars including 11 founder parents and 106 derivatives were analyzed by the 9 K wheat SNP iSelect assay. A total of 4138 polymorphic single nucleotide polymorphism (SNP) loci were detected on 21 chromosomes, of which 3792 were mapped to single chromosome locations. All genotypes were phenotyped for six yield-related traits including plant height (PH), spike length (SL), spikelet number per spike (SNPS), kernel number per spike (KNPS), kernel weight per spike (KWPS), and thousand kernel weight (TKW) in six irrigated environments. Genome-wide association analysis detected 117 significant associations of 76 SNPs on 15 chromosomes with phenotypic explanation rates (R 2 ) ranging from 2.03 to 12.76%. In comparing allelic variation between founder parents and their derivatives (106) and other cultivars (98) using the 76 associated SNPs, we found that the region 116.0-133.2 cM on chromosome 5A in founder parents and derivatives carried alleles positively influencing kernel weight per spike (KWPS), rarely found in other cultivars. The identified favorable alleles could mark important chromosome regions in derivatives that were inherited from founder parents. Our results unravel the genetic of yield in founder genotypes, and provide tools for marker-assisted selection for yield improvement.
Chatsuriyawong, Siriporn; Gozal, David; Kheirandish-Gozal, Leila; Bhattacharjee, Rakesh; Khalyfa, Ahamed A; Wang, Yang; Sukhumsirichart, Wasana; Khalyfa, Abdelnaby
2013-09-06
Obstructive sleep apnea (OSA) is associated with adverse and interdependent cognitive and cardiovascular consequences. Increasing evidence suggests that nitric oxide synthase (NOS) and endothelin family (EDN) genes underlie mechanistic aspects of OSA-associated morbidities. We aimed to identify single nucleotide polymorphisms (SNPs) in the NOS family (3 isoforms), and EDN family (3 isoforms) to identify potential associations of these SNPs in children with OSA. A pediatric community cohort (ages 5-10 years) enriched for snoring underwent overnight polysomnographic (NPSG) and a fasting morning blood draw. The diagnostic criteria for OSA were an obstructive apnea-hypopnea Index (AHI) >2/h total sleep time (TST), snoring during the night, and a nadir oxyhemoglobin saturation <92%. Control children were defined as non-snoring children with AHI <2/h TST (NOSA). Endothelial function was assessed using a modified post-occlusive hyperemic test. The time to peak reperfusion (Tmax) was considered as the indicator for normal endothelial function (NEF; Tmax<45 sec), or ED (Tmax ≥ 45 sec). Genomic DNA from peripheral blood was extracted and allelic frequencies were assessed for, NOS1 (209 SNPs), NOS2 (122 SNPs), NOS3 (50 SNPs), EDN1 (43 SNPs), EDN2 (48 SNPs), EDN3 (14 SNPs), endothelin receptor A, EDNRA, (27 SNPs), and endothelin receptor B, EDNRB (23 SNPs) using a custom SNPs array. The relative frequencies of NOS-1,-2, and -3, and EDN-1,-2,-3,-EDNRA, and-EDNRB genotypes were evaluated in 608 subjects [128 with OSA, and 480 without OSA (NOSA)]. Furthermore, subjects with OSA were divided into 2 subgroups: OSA with normal endothelial function (OSA-NEF), and OSA with endothelial dysfunction (OSA-ED). Linkage disequilibrium was analyzed using Haploview version 4.2 software. For NOSA vs. OSA groups, 15 differentially distributed SNPs for NOS1 gene, and 1 SNP for NOS3 emerged, while 4 SNPs for EDN1 and 1 SNP for both EDN2 and EDN3 were identified. However, in the smaller sub-group for whom endothelial function was available, none of the significant SNPs was retained due to lack of statistical power. Differences in the distribution of polymorphisms among NOS and EDN gene families suggest that these SNPs could play a contributory role in the pathophysiology and risk of OSA-induced cardiovascular morbidity. Thus, analysis of genotype-phenotype interactions in children with OSA may assist in the formulation of categorical risk estimates.
Molecules to maps: tools for visualization and interaction in support of computational biology.
Kraemer, E T; Ferrin, T E
1998-01-01
The volume of data produced by genome projects, X-ray crystallography, NMR spectroscopy, and electron and confocal microscopy present the bioinformatics community with new challenges for analyzing, understanding, and exchanging this data. At the 1998 Pacific Symposium on Biocomputing, a track entitled 'Molecules to Maps: Tools for Visualization and Interaction in Computational Biology' provided tool developers and users with the opportunity to discuss advances in tools and techniques to assist scientists in evaluating, absorbing, navigating, and correlating this sea of information, through visualization and user interaction. In this paper we present these advances and discuss some of the challenges that remain to be solved.
Searching for SNPs with cloud computing
2009-01-01
As DNA sequencing outpaces improvements in computer speed, there is a critical need to accelerate tasks like alignment and SNP calling. Crossbow is a cloud-computing software tool that combines the aligner Bowtie and the SNP caller SOAPsnp. Executing in parallel using Hadoop, Crossbow analyzes data comprising 38-fold coverage of the human genome in three hours using a 320-CPU cluster rented from a cloud computing service for about $85. Crossbow is available from http://bowtie-bio.sourceforge.net/crossbow/. PMID:19930550
Visual business ecosystem intelligence: lessons from the field.
Basole, Rahul C
2014-01-01
Macroscopic insight into business ecosystems is becoming increasingly important. With the emergence of new digital business data, opportunities exist to develop rich, interactive visual-analytics tools. Georgia Institute of Technology researchers have been developing and implementing visual business ecosystem intelligence tools in corporate settings. This article discusses the challenges they faced, the lessons learned, and opportunities for future research.
ERIC Educational Resources Information Center
Kaiser, Justin T.; Herzberg, Tina S.
2017-01-01
Introduction: This study analyzed survey responses from 314 teachers of students with visual impairments regarding the tools and procedures used in completing functional vision assessments (FVAs). Methods: Teachers of students with visual impairments in the United States and Canada completed an online survey during spring 2016. Results: The…
... Doing AMIGAS Stay Informed Cancer Home Uterine Cancer Statistics Language: English (US) Español (Spanish) Recommend on Facebook ... the most commonly diagnosed gynecologic cancer. U.S. Cancer Statistics Data Visualizations Tool The Data Visualizations tool makes ...
DOE Office of Scientific and Technical Information (OSTI.GOV)
Minelli, Annalisa, E-mail: Annalisa.Minelli@univ-brest.fr; Marchesini, Ivan, E-mail: Ivan.Marchesini@irpi.cnr.it; Taylor, Faith E., E-mail: Faith.Taylor@kcl.ac.uk
Although there are clear economic and environmental incentives for producing energy from solar and wind power, there can be local opposition to their installation due to their impact upon the landscape. To date, no international guidelines exist to guide quantitative visual impact assessment of these facilities, making the planning process somewhat subjective. In this paper we demonstrate the development of a method and an Open Source GIS tool to quantitatively assess the visual impact of these facilities using line-of-site techniques. The methods here build upon previous studies by (i) more accurately representing the shape of energy producing facilities, (ii) takingmore » into account the distortion of the perceived shape and size of facilities caused by the location of the observer, (iii) calculating the possible obscuring of facilities caused by terrain morphology and (iv) allowing the combination of various facilities to more accurately represent the landscape. The tool has been applied to real and synthetic case studies and compared to recently published results from other models, and demonstrates an improvement in accuracy of the calculated visual impact of facilities. The tool is named r.wind.sun and is freely available from GRASS GIS AddOns. - Highlights: • We develop a tool to quantify wind turbine and photovoltaic panel visual impact. • The tool is freely available to download and edit as a module of GRASS GIS. • The tool takes into account visual distortion of the shape and size of objects. • The accuracy of calculation of visual impact is improved over previous methods.« less
Savant Genome Browser 2: visualization and analysis for population-scale genomics.
Fiume, Marc; Smith, Eric J M; Brook, Andrew; Strbenac, Dario; Turner, Brian; Mezlini, Aziz M; Robinson, Mark D; Wodak, Shoshana J; Brudno, Michael
2012-07-01
High-throughput sequencing (HTS) technologies are providing an unprecedented capacity for data generation, and there is a corresponding need for efficient data exploration and analysis capabilities. Although most existing tools for HTS data analysis are developed for either automated (e.g. genotyping) or visualization (e.g. genome browsing) purposes, such tools are most powerful when combined. For example, integration of visualization and computation allows users to iteratively refine their analyses by updating computational parameters within the visual framework in real-time. Here we introduce the second version of the Savant Genome Browser, a standalone program for visual and computational analysis of HTS data. Savant substantially improves upon its predecessor and existing tools by introducing innovative visualization modes and navigation interfaces for several genomic datatypes, and synergizing visual and automated analyses in a way that is powerful yet easy even for non-expert users. We also present a number of plugins that were developed by the Savant Community, which demonstrate the power of integrating visual and automated analyses using Savant. The Savant Genome Browser is freely available (open source) at www.savantbrowser.com.
Savant Genome Browser 2: visualization and analysis for population-scale genomics
Smith, Eric J. M.; Brook, Andrew; Strbenac, Dario; Turner, Brian; Mezlini, Aziz M.; Robinson, Mark D.; Wodak, Shoshana J.; Brudno, Michael
2012-01-01
High-throughput sequencing (HTS) technologies are providing an unprecedented capacity for data generation, and there is a corresponding need for efficient data exploration and analysis capabilities. Although most existing tools for HTS data analysis are developed for either automated (e.g. genotyping) or visualization (e.g. genome browsing) purposes, such tools are most powerful when combined. For example, integration of visualization and computation allows users to iteratively refine their analyses by updating computational parameters within the visual framework in real-time. Here we introduce the second version of the Savant Genome Browser, a standalone program for visual and computational analysis of HTS data. Savant substantially improves upon its predecessor and existing tools by introducing innovative visualization modes and navigation interfaces for several genomic datatypes, and synergizing visual and automated analyses in a way that is powerful yet easy even for non-expert users. We also present a number of plugins that were developed by the Savant Community, which demonstrate the power of integrating visual and automated analyses using Savant. The Savant Genome Browser is freely available (open source) at www.savantbrowser.com. PMID:22638571
NASA Astrophysics Data System (ADS)
Keika, Kunihiro; Miyoshi, Yoshizumi; Machida, Shinobu; Ieda, Akimasa; Seki, Kanako; Hori, Tomoaki; Miyashita, Yukinaga; Shoji, Masafumi; Shinohara, Iku; Angelopoulos, Vassilis; Lewis, Jim W.; Flores, Aaron
2017-12-01
This paper introduces ISEE_3D, an interactive visualization tool for three-dimensional plasma velocity distribution functions, developed by the Institute for Space-Earth Environmental Research, Nagoya University, Japan. The tool provides a variety of methods to visualize the distribution function of space plasma: scatter, volume, and isosurface modes. The tool also has a wide range of functions, such as displaying magnetic field vectors and two-dimensional slices of distributions to facilitate extensive analysis. The coordinate transformation to the magnetic field coordinates is also implemented in the tool. The source codes of the tool are written as scripts of a widely used data analysis software language, Interactive Data Language, which has been widespread in the field of space physics and solar physics. The current version of the tool can be used for data files of the plasma distribution function from the Geotail satellite mission, which are publicly accessible through the Data Archives and Transmission System of the Institute of Space and Astronautical Science (ISAS)/Japan Aerospace Exploration Agency (JAXA). The tool is also available in the Space Physics Environment Data Analysis Software to visualize plasma data from the Magnetospheric Multiscale and the Time History of Events and Macroscale Interactions during Substorms missions. The tool is planned to be applied to data from other missions, such as Arase (ERG) and Van Allen Probes after replacing or adding data loading plug-ins. This visualization tool helps scientists understand the dynamics of space plasma better, particularly in the regions where the magnetohydrodynamic approximation is not valid, for example, the Earth's inner magnetosphere, magnetopause, bow shock, and plasma sheet.
Monitoring an Online Course with the GISMO Tool: A Case Study
ERIC Educational Resources Information Center
Mazza, Riccardo; Botturi, Luca
2007-01-01
This article presents GISMO, a novel, open source, graphic student-tracking tool integrated into Moodle. GISMO represents a further step in information visualization applied to education, and also a novelty in the field of learning management systems applications. The visualizations of the tool, its uses and the benefits it can bring are…
NASA Astrophysics Data System (ADS)
Borkin, Michelle A.
Visualization is a powerful tool for data exploration and analysis. With data ever-increasing in quantity and becoming integrated into our daily lives, having effective visualizations is necessary. But how does one design an effective visualization? To answer this question we need to understand how humans perceive, process, and understand visualizations. Through visualization evaluation studies we can gain deeper insight into the basic perception and cognition theory of visualizations, both through domain-specific case studies as well as generalized laboratory experiments. This dissertation presents the results of four evaluation studies, each of which contributes new knowledge to the theory of perception and cognition of visualizations. The results of these studies include a deeper clearer understanding of how color, data representation dimensionality, spatial layout, and visual complexity affect a visualization's effectiveness, as well as how visualization types and visual attributes affect the memorability of a visualization. We first present the results of two domain-specific case study evaluations. The first study is in the field of biomedicine in which we developed a new heart disease diagnostic tool, and conducted a study to evaluate the effectiveness of 2D versus 3D data representations as well as color maps. In the second study, we developed a new visualization tool for filesystem provenance data with applications in computer science and the sciences more broadly. We additionally developed a new time-based hierarchical node grouping method. We then conducted a study to evaluate the effectiveness of the new tool with its radial layout versus the conventional node-link diagram, and the new node grouping method. Finally, we discuss the results of two generalized studies designed to understand what makes a visualization memorable. In the first evaluation we focused on visualization memorability and conducted an online study using Amazon's Mechanical Turk with hundreds of users and thousands of visualizations. For the second evaluation we designed an eye-tracking laboratory study to gain insight into precisely which elements of a visualization contribute to memorability as well as visualization recognition and recall.
Visual Analysis of Air Traffic Data
NASA Technical Reports Server (NTRS)
Albrecht, George Hans; Pang, Alex
2012-01-01
In this paper, we present visual analysis tools to help study the impact of policy changes on air traffic congestion. The tools support visualization of time-varying air traffic density over an area of interest using different time granularity. We use this visual analysis platform to investigate how changing the aircraft separation volume can reduce congestion while maintaining key safety requirements. The same platform can also be used as a decision aid for processing requests for unmanned aerial vehicle operations.
NASA Astrophysics Data System (ADS)
Marco Figuera, R.; Pham Huu, B.; Rossi, A. P.; Minin, M.; Flahaut, J.; Halder, A.
2018-01-01
The lack of open-source tools for hyperspectral data visualization and analysis creates a demand for new tools. In this paper we present the new PlanetServer, a set of tools comprising a web Geographic Information System (GIS) and a recently developed Python Application Programming Interface (API) capable of visualizing and analyzing a wide variety of hyperspectral data from different planetary bodies. Current WebGIS open-source tools are evaluated in order to give an overview and contextualize how PlanetServer can help in this matters. The web client is thoroughly described as well as the datasets available in PlanetServer. Also, the Python API is described and exposed the reason of its development. Two different examples of mineral characterization of different hydrosilicates such as chlorites, prehnites and kaolinites in the Nili Fossae area on Mars are presented. As the obtained results show positive outcome in hyperspectral analysis and visualization compared to previous literature, we suggest using the PlanetServer approach for such investigations.
Resilience to the contralateral visual field bias as a window into object representations
Garcea, Frank E.; Kristensen, Stephanie; Almeida, Jorge; Mahon, Bradford Z.
2016-01-01
Viewing images of manipulable objects elicits differential blood oxygen level-dependent (BOLD) contrast across parietal and dorsal occipital areas of the human brain that support object-directed reaching, grasping, and complex object manipulation. However, it is unknown which object-selective regions of parietal cortex receive their principal inputs from the ventral object-processing pathway and which receive their inputs from the dorsal object-processing pathway. Parietal areas that receive their inputs from the ventral visual pathway, rather than from the dorsal stream, will have inputs that are already filtered through object categorization and identification processes. This predicts that parietal regions that receive inputs from the ventral visual pathway should exhibit object-selective responses that are resilient to contralateral visual field biases. To test this hypothesis, adult participants viewed images of tools and animals that were presented to the left or right visual fields during functional magnetic resonance imaging (fMRI). We found that the left inferior parietal lobule showed robust tool preferences independently of the visual field in which tool stimuli were presented. In contrast, a region in posterior parietal/dorsal occipital cortex in the right hemisphere exhibited an interaction between visual field and category: tool-preferences were strongest contralateral to the stimulus. These findings suggest that action knowledge accessed in the left inferior parietal lobule operates over inputs that are abstracted from the visual input and contingent on analysis by the ventral visual pathway, consistent with its putative role in supporting object manipulation knowledge. PMID:27160998
Genome-wide scan for commons SNPs affecting bovine leukemia virus infection level in dairy cattle.
Carignano, Hugo A; Roldan, Dana L; Beribe, María J; Raschia, María A; Amadio, Ariel; Nani, Juan P; Gutierrez, Gerónimo; Alvarez, Irene; Trono, Karina; Poli, Mario A; Miretti, Marcos M
2018-02-13
Bovine leukemia virus (BLV) infection is omnipresent in dairy herds causing direct economic losses due to trade restrictions and lymphosarcoma-related deaths. Milk production drops and increase in the culling rate are also relevant and usually neglected. The BLV provirus persists throughout a lifetime and an inter-individual variation is observed in the level of infection (LI) in vivo. High LI is strongly correlated with disease progression and BLV transmission among herd mates. In a context of high prevalence, classical control strategies are economically prohibitive. Alternatively, host genomics studies aiming to dissect loci associated with LI are potentially useful tools for genetic selection programs tending to abrogate the viral spreading. The LI was measured through the proviral load (PVL) set-point and white blood cells (WBC) counts. The goals of this work were to gain insight into the contribution of SNPs (bovine 50KSNP panel) on LI variability and to identify genomics regions underlying this trait. We quantified anti-p24 response and total leukocytes count in peripheral blood from 1800 cows and used these to select 800 individuals with extreme phenotypes in WBCs and PVL. Two case-control genomic association studies using linear mixed models (LMMs) considering population stratification were performed. The proportion of the variance captured by all QC-passed SNPs represented 0.63 (SE ± 0.14) of the phenotypic variance for PVL and 0.56 (SE ± 0.15) for WBCs. Overall, significant associations (Bonferroni's corrected -log 10 p > 5.94) were shared for both phenotypes by 24 SNPs within the Bovine MHC. Founder haplotypes were used to measure the linkage disequilibrium (LD) extent (r 2 = 0.22 ± 0.27 at inter-SNP distance of 25-50 kb). The SNPs and LD blocks indicated genes potentially associated with LI in infected cows: i.e. relevant immune response related genes (DQA1, DRB3, BOLA-A, LTA, LTB, TNF, IER3, GRP111, CRISP1), several genes involved in cell cytoskeletal reorganization (CD2AP, PKHD1, FLOT1, TUBB5) and modelling of the extracellular matrix (TRAM2, TNXB). Host transcription factors (TFs) were also highlighted (TFAP2D; ABT1, GCM1, PRRC2A). Data obtained represent a step forward to understand the biology of BLV-bovine interaction, and provide genetic information potentially applicable to selective breeding programs.
Leonenko, Ganna; Di Florio, Arianna; Allardyce, Judith; Forty, Liz; Knott, Sarah; Jones, Lisa; Gordon-Smith, Katherine; Owen, Michael J; Jones, Ian; Walters, James; Craddock, Nick; O'Donovan, Michael C; Escott-Price, Valentina
2018-06-01
The etiologies of bipolar disorder (BD) and schizophrenia include a large number of common risk alleles, many of which are shared across the disorders. BD is clinically heterogeneous and it has been postulated that the pattern of symptoms is in part determined by the particular risk alleles carried, and in particular, that risk alleles also confer liability to schizophrenia influence psychotic symptoms in those with BD. To investigate links between psychotic symptoms in BD and schizophrenia risk alleles we employed a data-driven approach in a genotyped and deeply phenotyped sample of subjects with BD. We used sparse canonical correlation analysis (sCCA) (Witten, Tibshirani, & Hastie, ) to analyze 30 psychotic symptoms, assessed with the OPerational CRITeria checklist, and 82 independent genome-wide significant single nucleotide polymorphisms (SNPs) identified by the Schizophrenia Working group of the Psychiatric Genomics Consortium for which we had data in our BD sample (3,903 subjects). As a secondary analysis, we applied sCCA to larger groups of SNPs, and also to groups of symptoms defined according to a published factor analyses of schizophrenia. sCCA analysis based on individual psychotic symptoms revealed a significant association (p = .033), with the largest weights attributed to a variant on chromosome 3 (rs11411529), chr3:180594593, build 37) and delusions of influence, bizarre behavior and grandiose delusions. sCCA analysis using the same set of SNPs supported association with the same SNP and the group of symptoms defined "factor 3" (p = .012). A significant association was also observed to the "factor 3" phenotype group when we included a greater number of SNPs that were less stringently associated with schizophrenia; although other SNPs contributed to the significant multivariate association result, the greatest weight remained assigned to rs11411529. Our results suggest that the canonical correlation is a useful tool to explore phenotype-genotype relationships. To the best of our knowledge, this is the first study to apply this approach to complex, polygenic psychiatric traits. The sparse canonical correlation approach offers the potential to include a larger number of fine-grained systematic descriptors, and to include genetic markers associated with other disorders that are genetically correlated with BD. © 2018 The Authors. American Journal of Medical Genetics Part B: Neuropsychiatric Genetics Published by Wiley Periodicals, Inc.
FPV: fast protein visualization using Java 3D.
Can, Tolga; Wang, Yujun; Wang, Yuan-Fang; Su, Jianwen
2003-05-22
Many tools have been developed to visualize protein structures. Tools that have been based on Java 3D((TM)) are compatible among different systems and they can be run remotely through web browsers. However, using Java 3D for visualization has some performance issues with it. The primary concerns about molecular visualization tools based on Java 3D are in their being slow in terms of interaction speed and in their inability to load large molecules. This behavior is especially apparent when the number of atoms to be displayed is huge, or when several proteins are to be displayed simultaneously for comparison. In this paper we present techniques for organizing a Java 3D scene graph to tackle these problems. We have developed a protein visualization system based on Java 3D and these techniques. We demonstrate the effectiveness of the proposed method by comparing the visualization component of our system with two other Java 3D based molecular visualization tools. In particular, for van der Waals display mode, with the efficient organization of the scene graph, we could achieve up to eight times improvement in rendering speed and could load molecules three times as large as the previous systems could. EPV is freely available with source code at the following URL: http://www.cs.ucsb.edu/~tcan/fpv/
DOE Office of Scientific and Technical Information (OSTI.GOV)
Gillen, David S.
Analysis activities for Nonproliferation and Arms Control verification require the use of many types of data. Tabular structured data, such as Excel spreadsheets and relational databases, have traditionally been used for data mining activities, where specific queries are issued against data to look for matching results. The application of visual analytics tools to structured data enables further exploration of datasets to promote discovery of previously unknown results. This paper discusses the application of a specific visual analytics tool to datasets related to the field of Arms Control and Nonproliferation to promote the use of visual analytics more broadly in thismore » domain. Visual analytics focuses on analytical reasoning facilitated by interactive visual interfaces (Wong and Thomas 2004). It promotes exploratory analysis of data, and complements data mining technologies where known patterns can be mined for. Also with a human in the loop, they can bring in domain knowledge and subject matter expertise. Visual analytics has not widely been applied to this domain. In this paper, we will focus on one type of data: structured data, and show the results of applying a specific visual analytics tool to answer questions in the Arms Control and Nonproliferation domain. We chose to use the T.Rex tool, a visual analytics tool developed at PNNL, which uses a variety of visual exploration patterns to discover relationships in structured datasets, including a facet view, graph view, matrix view, and timeline view. The facet view enables discovery of relationships between categorical information, such as countries and locations. The graph tool visualizes node-link relationship patterns, such as the flow of materials being shipped between parties. The matrix visualization shows highly correlated categories of information. The timeline view shows temporal patterns in data. In this paper, we will use T.Rex with two different datasets to demonstrate how interactive exploration of the data can aid an analyst with arms control and nonproliferation verification activities. Using a dataset from PIERS (PIERS 2014), we will show how container shipment imports and exports can aid an analyst in understanding the shipping patterns between two countries. We will also use T.Rex to examine a collection of research publications from the IAEA International Nuclear Information System (IAEA 2014) to discover collaborations of concern. We hope this paper will encourage the use of visual analytics structured data analytics in the field of nonproliferation and arms control verification. Our paper outlines some of the challenges that exist before broad adoption of these kinds of tools can occur and offers next steps to overcome these challenges.« less
ProteoLens: a visual analytic tool for multi-scale database-driven biological network data mining.
Huan, Tianxiao; Sivachenko, Andrey Y; Harrison, Scott H; Chen, Jake Y
2008-08-12
New systems biology studies require researchers to understand how interplay among myriads of biomolecular entities is orchestrated in order to achieve high-level cellular and physiological functions. Many software tools have been developed in the past decade to help researchers visually navigate large networks of biomolecular interactions with built-in template-based query capabilities. To further advance researchers' ability to interrogate global physiological states of cells through multi-scale visual network explorations, new visualization software tools still need to be developed to empower the analysis. A robust visual data analysis platform driven by database management systems to perform bi-directional data processing-to-visualizations with declarative querying capabilities is needed. We developed ProteoLens as a JAVA-based visual analytic software tool for creating, annotating and exploring multi-scale biological networks. It supports direct database connectivity to either Oracle or PostgreSQL database tables/views, on which SQL statements using both Data Definition Languages (DDL) and Data Manipulation languages (DML) may be specified. The robust query languages embedded directly within the visualization software help users to bring their network data into a visualization context for annotation and exploration. ProteoLens supports graph/network represented data in standard Graph Modeling Language (GML) formats, and this enables interoperation with a wide range of other visual layout tools. The architectural design of ProteoLens enables the de-coupling of complex network data visualization tasks into two distinct phases: 1) creating network data association rules, which are mapping rules between network node IDs or edge IDs and data attributes such as functional annotations, expression levels, scores, synonyms, descriptions etc; 2) applying network data association rules to build the network and perform the visual annotation of graph nodes and edges according to associated data values. We demonstrated the advantages of these new capabilities through three biological network visualization case studies: human disease association network, drug-target interaction network and protein-peptide mapping network. The architectural design of ProteoLens makes it suitable for bioinformatics expert data analysts who are experienced with relational database management to perform large-scale integrated network visual explorations. ProteoLens is a promising visual analytic platform that will facilitate knowledge discoveries in future network and systems biology studies.
Matheson, Heath E; Buxbaum, Laurel J; Thompson-Schill, Sharon L
2017-11-01
Our use of tools is situated in different contexts. Prior evidence suggests that diverse regions within the ventral and dorsal streams represent information supporting common tool use. However, given the flexibility of object concepts, these regions may be tuned to different types of information when generating novel or uncommon uses of tools. To investigate this, we collected fMRI data from participants who reported common or uncommon tool uses in response to visually presented familiar objects. We performed a pattern dissimilarity analysis in which we correlated cortical patterns with behavioral measures of visual, action, and category information. The results showed that evoked cortical patterns within the dorsal tool use network reflected action and visual information to a greater extent in the uncommon use group, whereas evoked neural patterns within the ventral tool use network reflected categorical information more strongly in the common use group. These results reveal the flexibility of cortical representations of tool use and the situated nature of cortical representations more generally.
efficient association study design via power-optimized tag SNP selection
HAN, BUHM; KANG, HYUN MIN; SEO, MYEONG SEONG; ZAITLEN, NOAH; ESKIN, ELEAZAR
2008-01-01
Discovering statistical correlation between causal genetic variation and clinical traits through association studies is an important method for identifying the genetic basis of human diseases. Since fully resequencing a cohort is prohibitively costly, genetic association studies take advantage of local correlation structure (or linkage disequilibrium) between single nucleotide polymorphisms (SNPs) by selecting a subset of SNPs to be genotyped (tag SNPs). While many current association studies are performed using commercially available high-throughput genotyping products that define a set of tag SNPs, choosing tag SNPs remains an important problem for both custom follow-up studies as well as designing the high-throughput genotyping products themselves. The most widely used tag SNP selection method optimizes over the correlation between SNPs (r2). However, tag SNPs chosen based on an r2 criterion do not necessarily maximize the statistical power of an association study. We propose a study design framework that chooses SNPs to maximize power and efficiently measures the power through empirical simulation. Empirical results based on the HapMap data show that our method gains considerable power over a widely used r2-based method, or equivalently reduces the number of tag SNPs required to attain the desired power of a study. Our power-optimized 100k whole genome tag set provides equivalent power to the Affymetrix 500k chip for the CEU population. For the design of custom follow-up studies, our method provides up to twice the power increase using the same number of tag SNPs as r2-based methods. Our method is publicly available via web server at http://design.cs.ucla.edu. PMID:18702637
Yu, Yang; Wei, Jiankai; Zhang, Xiaojun; Liu, Jingwen; Liu, Chengzhang; Li, Fuhua; Xiang, Jianhai
2014-01-01
The application of next generation sequencing technology has greatly facilitated high throughput single nucleotide polymorphism (SNP) discovery and genotyping in genetic research. In the present study, SNPs were discovered based on two transcriptomes of Litopenaeus vannamei (L. vannamei) generated from Illumina sequencing platform HiSeq 2000. One transcriptome of L. vannamei was obtained through sequencing on the RNA from larvae at mysis stage and its reference sequence was de novo assembled. The data from another transcriptome were downloaded from NCBI and the reads of the two transcriptomes were mapped separately to the assembled reference by BWA. SNP calling was performed using SAMtools. A total of 58,717 and 36,277 SNPs with high quality were predicted from the two transcriptomes, respectively. SNP calling was also performed using the reads of two transcriptomes together, and a total of 96,040 SNPs with high quality were predicted. Among these 96,040 SNPs, 5,242 and 29,129 were predicted as non-synonymous and synonymous SNPs respectively. Characterization analysis of the predicted SNPs in L. vannamei showed that the estimated SNP frequency was 0.21% (one SNP per 476 bp) and the estimated ratio for transition to transversion was 2.0. Fifty SNPs were randomly selected for validation by Sanger sequencing after PCR amplification and 76% of SNPs were confirmed, which indicated that the SNPs predicted in this study were reliable. These SNPs will be very useful for genetic study in L. vannamei, especially for the high density linkage map construction and genome-wide association studies. PMID:24498047
Khatkar, Mehar S.; Zenger, Kyall R.; Hobbs, Matthew; Hawken, Rachel J.; Cavanagh, Julie A. L.; Barris, Wes; McClintock, Alexander E.; McClintock, Sara; Thomson, Peter C.; Tier, Bruce; Nicholas, Frank W.; Raadsma, Herman W.
2007-01-01
Analysis of data on 1000 Holstein–Friesian bulls genotyped for 15,036 single-nucleotide polymorphisms (SNPs) has enabled genomewide identification of haplotype blocks and tag SNPs. A final subset of 9195 SNPs in Hardy–Weinberg equilibrium and mapped on autosomes on the bovine sequence assembly (release Btau 3.1) was used in this study. The average intermarker spacing was 251.8 kb. The average minor allele frequency (MAF) was 0.29 (0.05–0.5). Following recent precedents in human HapMap studies, a haplotype block was defined where 95% of combinations of SNPs within a region are in very high linkage disequilibrium. A total of 727 haplotype blocks consisting of ≥3 SNPs were identified. The average block length was 69.7 ± 7.7 kb, which is ∼5–10 times larger than in humans. These blocks comprised a total of 2964 SNPs and covered 50,638 kb of the sequence map, which constitutes 2.18% of the length of all autosomes. A set of tag SNPs, which will be useful for further fine-mapping studies, has been identified. Overall, the results suggest that as many as 75,000–100,000 tag SNPs would be needed to track all important haplotype blocks in the bovine genome. This would require ∼250,000 SNPs in the discovery phase. PMID:17435229
NASA Astrophysics Data System (ADS)
Suaste-Gomez, Ernesto; Leybon, Jaime I.; Rodriguez, D.
1998-07-01
Visual scanpath has been an important work applied in neuro- ophthalmic and psychological studies. This is because it has been working like a tool to validate some pathologies such as visual perception in color or black/white images; color blindness; etc. On the other hand, this tool has reached a big field of applications such as marketing. The scanpath over a specific picture, shows the observer interest in color, shapes, letter size, etc.; even tough the picture be among a group of images, this tool has demonstrated to be helpful to catch people interest over a specific advertisement.
USDA-ARS?s Scientific Manuscript database
The dissection of complex traits of economic importance for the pig industry requires the availability of a significant number of genetic markers, such as SNPs. This study was conducted in order to discover thousands of porcine SNPs using next generation sequencing technologies and use those SNPs, a...
Rasulov, Bakhtiyor; Rustamova, Nigora; Yili, Abulimiti; Zhao, Hai-Qing; Aisa, Haji A
2016-07-01
Silver nanoparticles (SNPs) were synthesized on the basis of exopolysaccharides (low and high molar mass) of diazotrophic Bradyrhizobium japonicum 36 strain. The synthesis of SNPs was carried out by direct reduction of silver nitrate with ethanol-insoluble (high molar mass, HMW) and ethanol-soluble (low molar mass, LMW) fractions of exopolysaccharides (EPS), produced by diazotrophic strain B. japonicum 36. SNPs were characterized using UV-vis spectroscopy, transmission electron microscopy (TEM), X-ray diffraction (XRD), and Fourier transform infrared spectroscopy (FTIR). SNPs synthesized on the basis of LMW EPS absorbed radiation in the visible regions of 420 nm, whereas SNPs based on the HMW EPS have a wavelength maximum at 450 nm because of the strong SPR transition. Moreover, the antibacterial and antifungal activities of the SNPs were examined in vitro against Escherichia coli, Staphylococcus aureus, and Candida albicans. SNPs synthesized on the basis of LMW EPS were active than those synthesized on the basis of HMW EPS. Besides, UV-visible spectroscopic evaluation confirmed that SNPs synthesized on the basis of LMW EPS were far more stable than those obtained on the basis of HMW EPS.
A periodic pattern of SNPs in the human genome
Madsen, Bo Eskerod; Villesen, Palle; Wiuf, Carsten
2007-01-01
By surveying a filtered, high-quality set of SNPs in the human genome, we have found that SNPs positioned 1, 2, 4, 6, or 8 bp apart are more frequent than SNPs positioned 3, 5, 7, or 9 bp apart. The observed pattern is not restricted to genomic regions that are known to cause sequencing or alignment errors, for example, transposable elements (SINE, LINE, and LTR), tandem repeats, and large duplicated regions. However, we found that the pattern is almost entirely confined to what we define as “periodic DNA.” Periodic DNA is a genomic region with a high degree of periodicity in nucleotide usage. It turned out that periodic DNA is mainly small regions (average length 16.9 bp), widely distributed in the genome. Furthermore, periodic DNA has a 1.8 times higher SNP density than the rest of the genome and SNPs inside periodic DNA have a significantly higher genotyping error rate than SNPs outside periodic DNA. Our results suggest that not all SNPs in the human genome are created by independent single nucleotide mutations, and that care should be taken in analysis of SNPs from periodic DNA. The latter may have important consequences for SNP and association studies. PMID:17673700
Inferring Alcoholism SNPs and Regulatory Chemical Compounds Based on Ensemble Bayesian Network.
Chen, Huan; Sun, Jiatong; Jiang, Hong; Wang, Xianyue; Wu, Lingxiang; Wu, Wei; Wang, Qh
2017-01-01
The disturbance of consciousness is one of the most common symptoms of those have alcoholism and may cause disability and mortality. Previous studies indicated that several single nucleotide polymorphisms (SNP) increase the susceptibility of alcoholism. In this study, we utilized the Ensemble Bayesian Network (EBN) method to identify causal SNPs of alcoholism based on the verified GAW14 data. We built a Bayesian network combining random process and greedy search by using Genetic Analysis Workshop 14 (GAW14) dataset to establish EBN of SNPs. Then we predicted the association between SNPs and alcoholism by determining Bayes' prior probability. Thirteen out of eighteen SNPs directly connected with alcoholism were found concordance with potential risk regions of alcoholism in OMIM database. As many SNPs were found contributing to alteration on gene expression, known as expression quantitative trait loci (eQTLs), we further sought to identify chemical compounds acting as regulators of alcoholism genes captured by causal SNPs. Chloroprene and valproic acid were identified as the expression regulators for genes C11orf66 and SALL3 which were captured by alcoholism SNPs, respectively. Copyright© Bentham Science Publishers; For any queries, please email at epub@benthamscience.org.
Design and implementation of visualization methods for the CHANGES Spatial Decision Support System
NASA Astrophysics Data System (ADS)
Cristal, Irina; van Westen, Cees; Bakker, Wim; Greiving, Stefan
2014-05-01
The CHANGES Spatial Decision Support System (SDSS) is a web-based system aimed for risk assessment and the evaluation of optimal risk reduction alternatives at local level as a decision support tool in long-term natural risk management. The SDSS use multidimensional information, integrating thematic, spatial, temporal and documentary data. The role of visualization in this context becomes of vital importance for efficiently representing each dimension. This multidimensional aspect of the required for the system risk information, combined with the diversity of the end-users imposes the use of sophisticated visualization methods and tools. The key goal of the present work is to exploit efficiently the large amount of data in relation to the needs of the end-user, utilizing proper visualization techniques. Three main tasks have been accomplished for this purpose: categorization of the end-users, the definition of system's modules and the data definition. The graphical representation of the data and the visualization tools were designed to be relevant to the data type and the purpose of the analysis. Depending on the end-users category, each user should have access to different modules of the system and thus, to the proper visualization environment. The technologies used for the development of the visualization component combine the latest and most innovative open source JavaScript frameworks, such as OpenLayers 2.13.1, ExtJS 4 and GeoExt 2. Moreover, the model-view-controller (MVC) pattern is used in order to ensure flexibility of the system at the implementation level. Using the above technologies, the visualization techniques implemented so far offer interactive map navigation, querying and comparison tools. The map comparison tools are of great importance within the SDSS and include the following: swiping tool for comparison of different data of the same location; raster subtraction for comparison of the same phenomena varying in time; linked views for comparison of data from different locations and a time slider tool for monitoring changes in spatio-temporal data. All these techniques are part of the interactive interface of the system and make use of spatial and spatio-temporal data. Further significant aspects of the visualization component include conventional cartographic techniques and visualization of non-spatial data. The main expectation from the present work is to offer efficient visualization of risk-related data in order to facilitate the decision making process, which is the final purpose of the CHANGES SDSS. This work is part of the "CHANGES" project, funded by the European Community's 7th Framework Programme.
Qiu, Chao; Chang, Ranran; Yang, Jie; Ge, Shengju; Xiong, Liu; Zhao, Mei; Li, Man; Sun, Qingjie
2017-04-15
Essential oils (EOs), including menthone, oregano, cinnamon, lavender, and citral, are natural products that have antimicrobial and antioxidant activities. However, extremely low water solubility, and easy degradation by heat, restrict their application. The aim of this work was to evaluate the enhancement in antioxidative and antimicrobial activities of EOs encapsulated in starch nanoparticles (SNPs) prepared by short glucan chains. For the first time, we have successfully fabricated menthone-loaded SNPs (SNPs-M) at different complexation temperatures (30, 60, and 90°C) by an in situ nanoprecipitation method. The SNPs-M displayed spherical shapes, and the particle sizes ranged from 93 to 113nm. The encapsulation efficiency (EE) of SNPs-M increased significantly with an increase in complexation temperature, and the maximum EE was 86.6%. The SNPs-M formed at 90°C had high crystallization and thermal stability. The durations of the antioxidant and antimicrobial activities of EOs was extended by their encapsulation in the SNPs. Copyright © 2016 Elsevier Ltd. All rights reserved.
Heterospecific SNP diversity in humans and rhesus macaque (Macaca mulatta)
Ng, Jillian; Trask, Jessica Satkoski; Smith, David Glenn; Kanthaswamy, Sree
2018-01-01
Background Conservation of single nucleotide polymorphisms (SNPs) between human and other primates (i.e., heterospecific SNPs) in candidate genes can be used to assess the utility of those organisms as models for human biomedical research. Methods 59,691 heterospecific SNPs in 22 rhesus macaques and 20 humans were analyzed for human trait associations and 4,207 heterospecific SNPs biallelic in both taxa were compared for genetic variation. Results Variation comparisons at the 4,207 SNPs showed that humans were more genetically diverse than rhesus macaques with observed and expected heterozygosities of 0.337 and 0.323 versus 0.119 and 0.102, and minor allele frequencies of 0.239 and 0.063, respectively. 431 of the 59,691 heterospecific SNPs are reportedly associated with human-specific traits. Conclusion While comparisons between human and rhesus macaque genomes are plausible, functional studies of heterospecific SNPs are necessary to determine whether rhesus macaque alleles are associated with the same phenotypes as their corresponding human alleles. PMID:25963897
Genotyping in the cloud with Crossbow.
Gurtowski, James; Schatz, Michael C; Langmead, Ben
2012-09-01
Crossbow is a scalable, portable, and automatic cloud computing tool for identifying SNPs from high-coverage, short-read resequencing data. It is built on Apache Hadoop, an implementation of the MapReduce software framework. Hadoop allows Crossbow to distribute read alignment and SNP calling subtasks over a cluster of commodity computers. Two robust tools, Bowtie and SOAPsnp, implement the fundamental alignment and variant calling operations respectively, and have demonstrated capabilities within Crossbow of analyzing approximately one billion short reads per hour on a commodity Hadoop cluster with 320 cores. Through protocol examples, this unit will demonstrate the use of Crossbow for identifying variations in three different operating modes: on a Hadoop cluster, on a single computer, and on the Amazon Elastic MapReduce cloud computing service.
The DiaCog: A Prototype Tool for Visualizing Online Dialog Games' Interactions
ERIC Educational Resources Information Center
Yengin, Ilker; Lazarevic, Bojan
2014-01-01
This paper proposes and explains the design of a prototype learning tool named the DiaCog. The DiaCog visualizes dialog interactions within an online dialog game by using dynamically created cognitive maps. As a purposefully designed tool for enhancing learning effectiveness the DiaCog might be applicable to dialogs at discussion boards within a…
Using Drawing Technology to Assess Students' Visualizations of Chemical Reaction Processes
ERIC Educational Resources Information Center
Chang, Hsin-Yi; Quintana, Chris; Krajcik, Joseph
2014-01-01
In this study, we investigated how students used a drawing tool to visualize their ideas of chemical reaction processes. We interviewed 30 students using thinking-aloud and retrospective methods and provided them with a drawing tool. We identified four types of connections the students made as they used the tool: drawing on existing knowledge,…
Data Visualization: An Exploratory Study into the Software Tools Used by Businesses
ERIC Educational Resources Information Center
Diamond, Michael; Mattia, Angela
2017-01-01
Data visualization is a key component to business and data analytics, allowing analysts in businesses to create tools such as dashboards for business executives. Various software packages allow businesses to create these tools in order to manipulate data for making informed business decisions. The focus is to examine what skills employers are…
A Visual Tool for Computer Supported Learning: The Robot Motion Planning Example
ERIC Educational Resources Information Center
Elnagar, Ashraf; Lulu, Leena
2007-01-01
We introduce an effective computer aided learning visual tool (CALVT) to teach graph-based applications. We present the robot motion planning problem as an example of such applications. The proposed tool can be used to simulate and/or further to implement practical systems in different areas of computer science such as graphics, computational…
The generation of criteria for selecting analytical tools for landscape management
Marilyn Duffey-Armstrong
1979-01-01
This paper presents an approach to generating criteria for selecting the analytical tools used to assess visual resources for various landscape management tasks. The approach begins by first establishing the overall parameters for the visual assessment task, and follows by defining the primary requirements of the various sets of analytical tools to be used. Finally,...
Data Visualization: An Exploratory Study into the Software Tools Used by Businesses
ERIC Educational Resources Information Center
Diamond, Michael; Mattia, Angela
2015-01-01
Data visualization is a key component to business and data analytics, allowing analysts in businesses to create tools such as dashboards for business executives. Various software packages allow businesses to create these tools in order to manipulate data for making informed business decisions. The focus is to examine what skills employers are…
Data Presentation and Visualization (DPV) Interface Control Document
NASA Technical Reports Server (NTRS)
Mazzone, Rebecca A.; Conroy, Michael P.
2015-01-01
Data Presentation and Visualization (DPV) is a subset of the modeling and simulation (M&S) capabilities at Kennedy Space Center (KSC) that endeavors to address the challenges of how to present and share simulation output for analysts, stakeholders, decision makers, and other interested parties. DPV activities focus on the development and provision of visualization tools to meet the objectives identified above, as well as providing supporting tools and capabilities required to make its visualization products available and accessible across NASA.
Chang, Cheng; Xu, Kaikun; Guo, Chaoping; Wang, Jinxia; Yan, Qi; Zhang, Jian; He, Fuchu; Zhu, Yunping
2018-05-22
Compared with the numerous software tools developed for identification and quantification of -omics data, there remains a lack of suitable tools for both downstream analysis and data visualization. To help researchers better understand the biological meanings in their -omics data, we present an easy-to-use tool, named PANDA-view, for both statistical analysis and visualization of quantitative proteomics data and other -omics data. PANDA-view contains various kinds of analysis methods such as normalization, missing value imputation, statistical tests, clustering and principal component analysis, as well as the most commonly-used data visualization methods including an interactive volcano plot. Additionally, it provides user-friendly interfaces for protein-peptide-spectrum representation of the quantitative proteomics data. PANDA-view is freely available at https://sourceforge.net/projects/panda-view/. 1987ccpacer@163.com and zhuyunping@gmail.com. Supplementary data are available at Bioinformatics online.
A Visualization Tool for Integrating Research Results at an Underground Mine
NASA Astrophysics Data System (ADS)
Boltz, S.; Macdonald, B. D.; Orr, T.; Johnson, W.; Benton, D. J.
2016-12-01
Researchers with the National Institute for Occupational Safety and Health are conducting research at a deep, underground metal mine in Idaho to develop improvements in ground control technologies that reduce the effects of dynamic loading on mine workings, thereby decreasing the risk to miners. This research is multifaceted and includes: photogrammetry, microseismic monitoring, geotechnical instrumentation, and numerical modeling. When managing research involving such a wide range of data, understanding how the data relate to each other and to the mining activity quickly becomes a daunting task. In an effort to combine this diverse research data into a single, easy-to-use system, a three-dimensional visualization tool was developed. The tool was created using the Unity3d video gaming engine and includes the mine development entries, production stopes, important geologic structures, and user-input research data. The tool provides the user with a first-person, interactive experience where they are able to walk through the mine as well as navigate the rock mass surrounding the mine to view and interpret the imported data in the context of the mine and as a function of time. The tool was developed using data from a single mine; however, it is intended to be a generic tool that can be easily extended to other mines. For example, a similar visualization tool is being developed for an underground coal mine in Colorado. The ultimate goal is for NIOSH researchers and mine personnel to be able to use the visualization tool to identify trends that may not otherwise be apparent when viewing the data separately. This presentation highlights the features and capabilities of the mine visualization tool and explains how it may be used to more effectively interpret data and reduce the risk of ground fall hazards to underground miners.
Nguyen, Thanh-Tung; Huang, Joshua; Wu, Qingyao; Nguyen, Thuy; Li, Mark
2015-01-01
Single-nucleotide polymorphisms (SNPs) selection and identification are the most important tasks in Genome-wide association data analysis. The problem is difficult because genome-wide association data is very high dimensional and a large portion of SNPs in the data is irrelevant to the disease. Advanced machine learning methods have been successfully used in Genome-wide association studies (GWAS) for identification of genetic variants that have relatively big effects in some common, complex diseases. Among them, the most successful one is Random Forests (RF). Despite of performing well in terms of prediction accuracy in some data sets with moderate size, RF still suffers from working in GWAS for selecting informative SNPs and building accurate prediction models. In this paper, we propose to use a new two-stage quality-based sampling method in random forests, named ts-RF, for SNP subspace selection for GWAS. The method first applies p-value assessment to find a cut-off point that separates informative and irrelevant SNPs in two groups. The informative SNPs group is further divided into two sub-groups: highly informative and weak informative SNPs. When sampling the SNP subspace for building trees for the forest, only those SNPs from the two sub-groups are taken into account. The feature subspaces always contain highly informative SNPs when used to split a node at a tree. This approach enables one to generate more accurate trees with a lower prediction error, meanwhile possibly avoiding overfitting. It allows one to detect interactions of multiple SNPs with the diseases, and to reduce the dimensionality and the amount of Genome-wide association data needed for learning the RF model. Extensive experiments on two genome-wide SNP data sets (Parkinson case-control data comprised of 408,803 SNPs and Alzheimer case-control data comprised of 380,157 SNPs) and 10 gene data sets have demonstrated that the proposed model significantly reduced prediction errors and outperformed most existing the-state-of-the-art random forests. The top 25 SNPs in Parkinson data set were identified by the proposed model including four interesting genes associated with neurological disorders. The presented approach has shown to be effective in selecting informative sub-groups of SNPs potentially associated with diseases that traditional statistical approaches might fail. The new RF works well for the data where the number of case-control objects is much smaller than the number of SNPs, which is a typical problem in gene data and GWAS. Experiment results demonstrated the effectiveness of the proposed RF model that outperformed the state-of-the-art RFs, including Breiman's RF, GRRF and wsRF methods.
Integrating Visualizations into Modeling NEST Simulations
Nowke, Christian; Zielasko, Daniel; Weyers, Benjamin; Peyser, Alexander; Hentschel, Bernd; Kuhlen, Torsten W.
2015-01-01
Modeling large-scale spiking neural networks showing realistic biological behavior in their dynamics is a complex and tedious task. Since these networks consist of millions of interconnected neurons, their simulation produces an immense amount of data. In recent years it has become possible to simulate even larger networks. However, solutions to assist researchers in understanding the simulation's complex emergent behavior by means of visualization are still lacking. While developing tools to partially fill this gap, we encountered the challenge to integrate these tools easily into the neuroscientists' daily workflow. To understand what makes this so challenging, we looked into the workflows of our collaborators and analyzed how they use the visualizations to solve their daily problems. We identified two major issues: first, the analysis process can rapidly change focus which requires to switch the visualization tool that assists in the current problem domain. Second, because of the heterogeneous data that results from simulations, researchers want to relate data to investigate these effectively. Since a monolithic application model, processing and visualizing all data modalities and reflecting all combinations of possible workflows in a holistic way, is most likely impossible to develop and to maintain, a software architecture that offers specialized visualization tools that run simultaneously and can be linked together to reflect the current workflow, is a more feasible approach. To this end, we have developed a software architecture that allows neuroscientists to integrate visualization tools more closely into the modeling tasks. In addition, it forms the basis for semantic linking of different visualizations to reflect the current workflow. In this paper, we present this architecture and substantiate the usefulness of our approach by common use cases we encountered in our collaborative work. PMID:26733860
ATS displays: A reasoning visualization tool for expert systems
NASA Technical Reports Server (NTRS)
Selig, William John; Johannes, James D.
1990-01-01
Reasoning visualization is a useful tool that can help users better understand the inherently non-sequential logic of an expert system. While this is desirable in most all expert system applications, it is especially so for such critical systems as those destined for space-based operations. A hierarchical view of the expert system reasoning process and some characteristics of these various levels is presented. Also presented are Abstract Time Slice (ATS) displays, a tool to visualize the plethora of interrelated information available at the host inferencing language level of reasoning. The usefulness of this tool is illustrated with some examples from a prototype potable water expert system for possible use aboard Space Station Freedom.
D-peaks: a visual tool to display ChIP-seq peaks along the genome.
Brohée, Sylvain; Bontempi, Gianluca
2012-01-01
ChIP-sequencing is a method of choice to localize the positions of protein binding sites on DNA on a whole genomic scale. The deciphering of the sequencing data produced by this novel technique is challenging and it is achieved by their rigorous interpretation using dedicated tools and adapted visualization programs. Here, we present a bioinformatics tool (D-peaks) that adds several possibilities (including, user-friendliness, high-quality, relative position with respect to the genomic features) to the well-known visualization browsers or databases already existing. D-peaks is directly available through its web interface http://rsat.ulb.ac.be/dpeaks/ as well as a command line tool.
Rallis, Austin; Fercho, Kelene A; Bosch, Taylor J; Baugh, Lee A
2018-01-31
Tool use is associated with three visual streams-dorso-dorsal, ventro-dorsal, and ventral visual streams. These streams are involved in processing online motor planning, action semantics, and tool semantics features, respectively. Little is known about the way in which the brain represents virtual tools. To directly assess this question, a virtual tool paradigm was created that provided the ability to manipulate tool components in isolation of one another. During functional magnetic resonance imaging (fMRI), adult participants performed a series of virtual tool manipulation tasks in which vision and movement kinematics of the tool were manipulated. Reaction time and hand movement direction were monitored while the tasks were performed. Functional imaging revealed that activity within all three visual streams was present, in a similar pattern to what would be expected with physical tool use. However, a previously unreported network of right-hemisphere activity was found including right inferior parietal lobule, middle and superior temporal gyri and supramarginal gyrus - regions well known to be associated with tool processing within the left hemisphere. These results provide evidence that both virtual and physical tools are processed within the same brain regions, though virtual tools recruit bilateral tool processing regions to a greater extent than physical tools. Copyright © 2017 Elsevier Ltd. All rights reserved.
Utilizing the protein corona around silica nanoparticles for dual drug loading and release
NASA Astrophysics Data System (ADS)
Shahabi, Shakiba; Treccani, Laura; Dringen, Ralf; Rezwan, Kurosch
2015-10-01
A protein corona forms spontaneously around silica nanoparticles (SNPs) in serum-containing media. To test whether this protein corona can be utilized for the loading and release of anticancer drugs we incorporated the hydrophilic doxorubicin, the hydrophobic meloxicam as well as their combination in the corona around SNPs. The application of corona-covered SNPs to osteosarcoma cells revealed that drug-free particles did not affect the cell viability. In contrast, SNPs carrying a protein corona with doxorubicin or meloxicam lowered the cell proliferation in a concentration-dependent manner. In addition, these particles had an even greater antiproliferative potential than the respective concentrations of free drugs. The best antiproliferative effects were observed for SNPs containing both doxorubicin and meloxicam in their corona. Co-localization studies revealed the presence of doxorubicin fluorescence in the nucleus and lysosomes of cells exposed to doxorubicin-containing coated SNPs, suggesting that endocytotic uptake of the SNPs facilitates the cellular accumulation of the drug. Our data demonstrate that the protein corona, which spontaneously forms around nanoparticles, can be efficiently exploited for loading the particles with multiple drugs for therapeutic purposes. As drugs are efficiently released from such particles they may have a great potential for nanomedical applications.A protein corona forms spontaneously around silica nanoparticles (SNPs) in serum-containing media. To test whether this protein corona can be utilized for the loading and release of anticancer drugs we incorporated the hydrophilic doxorubicin, the hydrophobic meloxicam as well as their combination in the corona around SNPs. The application of corona-covered SNPs to osteosarcoma cells revealed that drug-free particles did not affect the cell viability. In contrast, SNPs carrying a protein corona with doxorubicin or meloxicam lowered the cell proliferation in a concentration-dependent manner. In addition, these particles had an even greater antiproliferative potential than the respective concentrations of free drugs. The best antiproliferative effects were observed for SNPs containing both doxorubicin and meloxicam in their corona. Co-localization studies revealed the presence of doxorubicin fluorescence in the nucleus and lysosomes of cells exposed to doxorubicin-containing coated SNPs, suggesting that endocytotic uptake of the SNPs facilitates the cellular accumulation of the drug. Our data demonstrate that the protein corona, which spontaneously forms around nanoparticles, can be efficiently exploited for loading the particles with multiple drugs for therapeutic purposes. As drugs are efficiently released from such particles they may have a great potential for nanomedical applications. Electronic supplementary information (ESI) available. See DOI: 10.1039/c5nr04726a
Østergaard, Søren D.; Mukherjee, Shubhabrata; Sharp, Stephen J.; Proitsi, Petroula; Lotta, Luca A.; Day, Felix; Perry, John R. B.; Boehme, Kevin L.; Walter, Stefan; Kauwe, John S.; Gibbons, Laura E.; Larson, Eric B.; Powell, John F.; Langenberg, Claudia; Crane, Paul K.; Wareham, Nicholas J.; Scott, Robert A.
2015-01-01
Background Potentially modifiable risk factors including obesity, diabetes, hypertension, and smoking are associated with Alzheimer disease (AD) and represent promising targets for intervention. However, the causality of these associations is unclear. We sought to assess the causal nature of these associations using Mendelian randomization (MR). Methods and Findings We used SNPs associated with each risk factor as instrumental variables in MR analyses. We considered type 2 diabetes (T2D, N SNPs = 49), fasting glucose (N SNPs = 36), insulin resistance (N SNPs = 10), body mass index (BMI, N SNPs = 32), total cholesterol (N SNPs = 73), HDL-cholesterol (N SNPs = 71), LDL-cholesterol (N SNPs = 57), triglycerides (N SNPs = 39), systolic blood pressure (SBP, N SNPs = 24), smoking initiation (N SNPs = 1), smoking quantity (N SNPs = 3), university completion (N SNPs = 2), and years of education (N SNPs = 1). We calculated MR estimates of associations between each exposure and AD risk using an inverse-variance weighted approach, with summary statistics of SNP–AD associations from the International Genomics of Alzheimer’s Project, comprising a total of 17,008 individuals with AD and 37,154 cognitively normal elderly controls. We found that genetically predicted higher SBP was associated with lower AD risk (odds ratio [OR] per standard deviation [15.4 mm Hg] of SBP [95% CI]: 0.75 [0.62–0.91]; p = 3.4 × 10−3). Genetically predicted higher SBP was also associated with a higher probability of taking antihypertensive medication (p = 6.7 × 10−8). Genetically predicted smoking quantity was associated with lower AD risk (OR per ten cigarettes per day [95% CI]: 0.67 [0.51–0.89]; p = 6.5 × 10−3), although we were unable to stratify by smoking history; genetically predicted smoking initiation was not associated with AD risk (OR = 0.70 [0.37, 1.33]; p = 0.28). We saw no evidence of causal associations between glycemic traits, T2D, BMI, or educational attainment and risk of AD (all p > 0.1). Potential limitations of this study include the small proportion of intermediate trait variance explained by genetic variants and other implicit limitations of MR analyses. Conclusions Inherited lifetime exposure to higher SBP is associated with lower AD risk. These findings suggest that higher blood pressure—or some environmental exposure associated with higher blood pressure, such as use of antihypertensive medications—may reduce AD risk. PMID:26079503
Anand, Sonia S; Xie, Changchun; Paré, Guillaume; Montpetit, Alexandre; Rangarajan, Sumathy; McQueen, Matthew J; Cordell, Heather J; Keavney, Bernard; Yusuf, Salim; Hudson, Thomas J; Engert, James C
2009-02-01
Myocardial infarction (MI) is a leading cause of death globally, but specific genetic variants that influence MI and MI risk factors have not been assessed on a global basis. We included 8795 individuals of European, South Asian, Arab, Iranian, and Nepalese origin from the INTERHEART case-control study that genotyped 1536 single-nucleotide polymorphisms (SNPs) from 103 genes. One hundred and two SNPs were nominally associated with MI, but the statistical significance did not remain after adjustment for multiple testing. A subset of 940 SNPs from 69 genes were tested against MI risk factors. One hundred and sixty-three SNPs were nominally associated with a MI risk factor and 13 remained significant after adjusting for multiple testing. Of these 13, 11 were associated with apolipoprotein (Apo) B/A1 levels: 8 SNPs from 3 genes were associated with Apo B, and 3 cholesteryl ester transfer protein SNPs were associated with Apo A1. Seven of 8 of the SNPs associated with Apo B levels were nominally associated with MI (P<0.05), whereas none of the 3 cholesteryl ester transfer protein SNPs were associated with MI (P> or =0.17). Of the 3 SNPs most significantly associated with MI, rs7412, which defines the Apo E2 isoform, was associated with both a lower Apo B/A1 ratio (P=1.0x10(-7)) and lower MI risk (P=0.0004). Two low-density lipoprotein receptor variants, 1 intronic (rs6511720) and 1 in the 3' untranslated region (rs1433099) were both associated with a lower Apo B/A1 ratio (P<1.0x10(-5)) and a lower risk of MI (P=0.004 and P=0.003, respectively). Thirteen common SNPs were associated with MI risk factors. Importantly, SNPs associated with Apo B levels were associated with MI, whereas SNPs associated with Apo A1 levels were not. The Apo E isoform, and 2 common low-density lipoprotein receptor variants (rs1433099 and rs6511720) influence MI risk in this multiethnic sample.
Chen, Zhanghua; Pereira, Mark A.; Seielstad, Mark; Koh, Woon-Puay; Tai, E. Shyong; Teo, Yik-Ying; Liu, Jianjun; Hsu, Chris; Wang, Renwei; Odegaard, Andrew O.; Thyagarajan, Bharat; Koratkar, Revati; Yuan, Jian-Min; Gross, Myron D.; Stram, Daniel O.
2014-01-01
Background Genome-wide association studies (GWAS) have identified genetic factors in type 2 diabetes (T2D), mostly among individuals of European ancestry. We tested whether previously identified T2D-associated single nucleotide polymorphisms (SNPs) replicate and whether SNPs in regions near known T2D SNPs were associated with T2D within the Singapore Chinese Health Study. Methods 2338 cases and 2339 T2D controls from the Singapore Chinese Health Study were genotyped for 507,509 SNPs. Imputation extended the genotyped SNPs to 7,514,461 with high estimated certainty (r2>0.8). Replication of known index SNP associations in T2D was attempted. Risk scores were computed as the sum of index risk alleles. SNPs in regions ±100 kb around each index were tested for associations with T2D in conditional fine-mapping analysis. Results Of 69 index SNPs, 20 were genotyped directly and genotypes at 35 others were well imputed. Among the 55 SNPs with data, disease associations were replicated (at p<0.05) for 15 SNPs, while 32 more were directionally consistent with previous reports. Risk score was a significant predictor with a 2.03 fold higher risk CI (1.69–2.44) of T2D comparing the highest to lowest quintile of risk allele burden (p = 5.72×10−14). Two improved SNPs around index rs10923931 and 5 new candidate SNPs around indices rs10965250 and rs1111875 passed simple Bonferroni corrections for significance in conditional analysis. Nonetheless, only a small fraction (2.3% on the disease liability scale) of T2D burden in Singapore is explained by these SNPs. Conclusions While diabetes risk in Singapore Chinese involves genetic variants, most disease risk remains unexplained. Further genetic work is ongoing in the Singapore Chinese population to identify unique common variants not already seen in earlier studies. However rapid increases in T2D risk have occurred in recent decades in this population, indicating that dynamic environmental influences and possibly gene by environment interactions complicate the genetic architecture of this disease. PMID:24520337
Chen, Zhanghua; Pereira, Mark A; Seielstad, Mark; Koh, Woon-Puay; Tai, E Shyong; Teo, Yik-Ying; Liu, Jianjun; Hsu, Chris; Wang, Renwei; Odegaard, Andrew O; Thyagarajan, Bharat; Koratkar, Revati; Yuan, Jian-Min; Gross, Myron D; Stram, Daniel O
2014-01-01
Genome-wide association studies (GWAS) have identified genetic factors in type 2 diabetes (T2D), mostly among individuals of European ancestry. We tested whether previously identified T2D-associated single nucleotide polymorphisms (SNPs) replicate and whether SNPs in regions near known T2D SNPs were associated with T2D within the Singapore Chinese Health Study. 2338 cases and 2339 T2D controls from the Singapore Chinese Health Study were genotyped for 507,509 SNPs. Imputation extended the genotyped SNPs to 7,514,461 with high estimated certainty (r(2)>0.8). Replication of known index SNP associations in T2D was attempted. Risk scores were computed as the sum of index risk alleles. SNPs in regions ± 100 kb around each index were tested for associations with T2D in conditional fine-mapping analysis. Of 69 index SNPs, 20 were genotyped directly and genotypes at 35 others were well imputed. Among the 55 SNPs with data, disease associations were replicated (at p<0.05) for 15 SNPs, while 32 more were directionally consistent with previous reports. Risk score was a significant predictor with a 2.03 fold higher risk CI (1.69-2.44) of T2D comparing the highest to lowest quintile of risk allele burden (p = 5.72 × 10(-14)). Two improved SNPs around index rs10923931 and 5 new candidate SNPs around indices rs10965250 and rs1111875 passed simple Bonferroni corrections for significance in conditional analysis. Nonetheless, only a small fraction (2.3% on the disease liability scale) of T2D burden in Singapore is explained by these SNPs. While diabetes risk in Singapore Chinese involves genetic variants, most disease risk remains unexplained. Further genetic work is ongoing in the Singapore Chinese population to identify unique common variants not already seen in earlier studies. However rapid increases in T2D risk have occurred in recent decades in this population, indicating that dynamic environmental influences and possibly gene by environment interactions complicate the genetic architecture of this disease.
Alam, Zaid; Peddinti, Gopal
2017-01-01
Abstract The advent of polypharmacology paradigm in drug discovery calls for novel chemoinformatic tools for analyzing compounds’ multi-targeting activities. Such tools should provide an intuitive representation of the chemical space through capturing and visualizing underlying patterns of compound similarities linked to their polypharmacological effects. Most of the existing compound-centric chemoinformatics tools lack interactive options and user interfaces that are critical for the real-time needs of chemical biologists carrying out compound screening experiments. Toward that end, we introduce C-SPADE, an open-source exploratory web-tool for interactive analysis and visualization of drug profiling assays (biochemical, cell-based or cell-free) using compound-centric similarity clustering. C-SPADE allows the users to visually map the chemical diversity of a screening panel, explore investigational compounds in terms of their similarity to the screening panel, perform polypharmacological analyses and guide drug-target interaction predictions. C-SPADE requires only the raw drug profiling data as input, and it automatically retrieves the structural information and constructs the compound clusters in real-time, thereby reducing the time required for manual analysis in drug development or repurposing applications. The web-tool provides a customizable visual workspace that can either be downloaded as figure or Newick tree file or shared as a hyperlink with other users. C-SPADE is freely available at http://cspade.fimm.fi/. PMID:28472495
Experience with Using Multiple Types of Visual Educational Tools during Problem-Based Learning.
Kang, Bong Jin
2012-06-01
This study describes the experience of using multiple types of visual educational tools in the setting of problem-based learning (PBL). The author intends to demonstrate their roles in diverse and efficient ways of clinical reasoning and problem solving. Visual educational tools were introduced in a lecture that included their various types, possible benefits, and some examples. Each group made one mechanistic case diagram per week, and each student designed one diagnostic schema or therapeutic algorithm per week, based on their learning issues. The students were also told to provide commentary, which was intended to give insights into their truthfulness. Subsequently, the author administered a questionnaire about the usefulness and weakness of visual educational tools and the difficulties with performing the work. Also, the qualities of the products were assessed by the author. There were many complaints about the adequacy of the introduction of visual educational tools, also revealed by the many initial inappropriate types of products. However, the exercise presentation in the first week improved the level of understanding regarding their purposes and the method of design. In general, students agreed on the benefits of their help in providing a deep understanding of the cases and the possibility of solving clinical problems efficiently. The commentary was helpful in evaluating the truthfulness of their efforts. Students gave suggestions for increasing the percentage of their scores, considering the efforts. Using multiple types of visual educational tools during PBL can be useful in understanding the diverse routes of clinical reasoning and clinical features.
Altools: a user friendly NGS data analyser.
Camiolo, Salvatore; Sablok, Gaurav; Porceddu, Andrea
2016-02-17
Genotyping by re-sequencing has become a standard approach to estimate single nucleotide polymorphism (SNP) diversity, haplotype structure and the biodiversity and has been defined as an efficient approach to address geographical population genomics of several model species. To access core SNPs and insertion/deletion polymorphisms (indels), and to infer the phyletic patterns of speciation, most such approaches map short reads to the reference genome. Variant calling is important to establish patterns of genome-wide association studies (GWAS) for quantitative trait loci (QTLs), and to determine the population and haplotype structure based on SNPs, thus allowing content-dependent trait and evolutionary analysis. Several tools have been developed to investigate such polymorphisms as well as more complex genomic rearrangements such as copy number variations, presence/absence variations and large deletions. The programs available for this purpose have different strengths (e.g. accuracy, sensitivity and specificity) and weaknesses (e.g. low computation speed, complex installation procedure and absence of a user-friendly interface). Here we introduce Altools, a software package that is easy to install and use, which allows the precise detection of polymorphisms and structural variations. Altools uses the BWA/SAMtools/VarScan pipeline to call SNPs and indels, and the dnaCopy algorithm to achieve genome segmentation according to local coverage differences in order to identify copy number variations. It also uses insert size information from the alignment of paired-end reads and detects potential large deletions. A double mapping approach (BWA/BLASTn) identifies precise breakpoints while ensuring rapid elaboration. Finally, Altools implements several processes that yield deeper insight into the genes affected by the detected polymorphisms. Altools was used to analyse both simulated and real next-generation sequencing (NGS) data and performed satisfactorily in terms of positive predictive values, sensitivity, the identification of large deletion breakpoints and copy number detection. Altools is fast, reliable and easy to use for the mining of NGS data. The software package also attempts to link identified polymorphisms and structural variants to their biological functions thus providing more valuable information than similar tools.
2011-01-01
Background Elucidation of molecular mechanism of silver nanoparticles (SNPs) biosynthesis is important to control its size, shape and monodispersity. The evaluation of molecular mechanism of biosynthesis of SNPs is of prime importance for the commercialization and methodology development for controlling the shape and size (uniform distribution) of SNPs. The unicellular algae Chlamydomonas reinhardtii was exploited as a model system to elucidate the role of cellular proteins in SNPs biosynthesis. Results The C. reinhardtii cell free extract (in vitro) and in vivo cells mediated synthesis of silver nanoparticles reveals SNPs of size range 5 ± 1 to 15 ± 2 nm and 5 ± 1 to 35 ± 5 nm respectively. In vivo biosynthesized SNPs were localized in the peripheral cytoplasm and at one side of flagella root, the site of pathway of ATP transport and its synthesis related enzymes. This provides an evidence for the involvement of oxidoreductive proteins in biosynthesis and stabilization of SNPs. Alteration in size distribution and decrease of synthesis rate of SNPs in protein-depleted fractions confirmed the involvement of cellular proteins in SNPs biosynthesis. Spectroscopic and SDS-PAGE analysis indicate the association of various proteins on C. reinhardtii mediated in vivo and in vitro biosynthesized SNPs. We have identified various cellular proteins associated with biosynthesized (in vivo and in vitro) SNPs by using MALDI-MS-MS, like ATP synthase, superoxide dismutase, carbonic anhydrase, ferredoxin-NADP+ reductase, histone etc. However, these proteins were not associated on the incubation of pre-synthesized silver nanoparticles in vitro. Conclusion Present study provides the indication of involvement of molecular machinery and various cellular proteins in the biosynthesis of silver nanoparticles. In this report, the study is mainly focused towards understanding the role of diverse cellular protein in the synthesis and capping of silver nanoparticles using C. reinhardtii as a model system. PMID:22152042
Replication of Caucasian loci associated with bone mineral density in Koreans.
Kim, Y A; Choi, H J; Lee, J Y; Han, B G; Shin, C S; Cho, N H
2013-10-01
Most bone mineral density (BMD) loci were reported in Caucasian genome-wide association studies (GWAS). This study investigated the association between 59 known BMD loci (+200 suggestive SNPs) and DXA-derived BMD in East Asian population with respect to sex and site specificity. We also identified four novel BMD candidate loci from the suggestive SNPs. Most GWAS have reported BMD-related variations in Caucasian populations. This study investigates whether the BMD loci discovered in Caucasian GWAS are also associated with BMD in East Asian ethnic samples. A total of 2,729 unrelated Korean individuals from a population-based cohort were analyzed. We selected 747 single-nucleotide polymorphisms (SNPs). These markers included 547 SNPs from 59 loci with genome-wide significance (GWS, p value less than 5 × 10(-8)) levels and 200 suggestive SNPs that showed weaker BMD association with p value less than 5 × 10(-5). After quality control, 535 GWS SNPs and 182 suggestive SNPs were included in the replication analysis. Of the 535 GWS SNPs, 276 from 25 loci were replicated (p < 0.05) in the Korean population with 51.6 % replication rate. Of the 182 suggestive variants, 16 were replicated (p < 0.05, 8.8 % of replication rate), and five reached a significant combined p value (less than 7.0 × 10(-5), 0.05/717 SNPs, corrected for multiple testing). Two markers (rs11711157, rs3732477) are for the same signal near the gene CPN2 (carboxypeptidase N, polypeptide 2). The other variants, rs6436440 and rs2291296, were located in the genes AP1S3 (adaptor-related protein complex 1, sigma 3 subunit) and RARB (retinoic acid receptor, beta). Our results illustrate ethnic differences in BMD susceptibility genes and underscore the need for further genetic studies in each ethnic group. We were also able to replicate some SNPs with suggestive associations. These SNPs may be BMD-related genetic markers and should be further investigated.
DOE Office of Scientific and Technical Information (OSTI.GOV)
King, Zachary A.; Drager, Andreas; Ebrahim, Ali
Escher is a web application for visualizing data on biological pathways. Three key features make Escher a uniquely effective tool for pathway visualization. First, users can rapidly design new pathway maps. Escher provides pathway suggestions based on user data and genome-scale models, so users can draw pathways in a semi-automated way. Second, users can visualize data related to genes or proteins on the associated reactions and pathways, using rules that define which enzymes catalyze each reaction. Thus, users can identify trends in common genomic data types (e.g. RNA-Seq, proteomics, ChIP)—in conjunction with metabolite- and reaction-oriented data types (e.g. metabolomics, fluxomics).more » Third, Escher harnesses the strengths of web technologies (SVG, D3, developer tools) so that visualizations can be rapidly adapted, extended, shared, and embedded. This paper provides examples of each of these features and explains how the development approach used for Escher can be used to guide the development of future visualization tools.« less
King, Zachary A.; Dräger, Andreas; Ebrahim, Ali; Sonnenschein, Nikolaus; Lewis, Nathan E.; Palsson, Bernhard O.
2015-01-01
Escher is a web application for visualizing data on biological pathways. Three key features make Escher a uniquely effective tool for pathway visualization. First, users can rapidly design new pathway maps. Escher provides pathway suggestions based on user data and genome-scale models, so users can draw pathways in a semi-automated way. Second, users can visualize data related to genes or proteins on the associated reactions and pathways, using rules that define which enzymes catalyze each reaction. Thus, users can identify trends in common genomic data types (e.g. RNA-Seq, proteomics, ChIP)—in conjunction with metabolite- and reaction-oriented data types (e.g. metabolomics, fluxomics). Third, Escher harnesses the strengths of web technologies (SVG, D3, developer tools) so that visualizations can be rapidly adapted, extended, shared, and embedded. This paper provides examples of each of these features and explains how the development approach used for Escher can be used to guide the development of future visualization tools. PMID:26313928
Stereoscopic applications for design visualization
NASA Astrophysics Data System (ADS)
Gilson, Kevin J.
2007-02-01
Advances in display technology and 3D design visualization applications have made real-time stereoscopic visualization of architectural and engineering projects a reality. Parsons Brinkerhoff (PB) is a transportation consulting firm that has used digital visualization tools from their inception and has helped pioneer the application of those tools to large scale infrastructure projects. PB is one of the first Architecture/Engineering/Construction (AEC) firms to implement a CAVE- an immersive presentation environment that includes stereoscopic rear-projection capability. The firm also employs a portable stereoscopic front-projection system, and shutter-glass systems for smaller groups. PB is using commercial real-time 3D applications in combination with traditional 3D modeling programs to visualize and present large AEC projects to planners, clients and decision makers in stereo. These presentations create more immersive and spatially realistic presentations of the proposed designs. This paper will present the basic display tools and applications, and the 3D modeling techniques PB is using to produce interactive stereoscopic content. The paper will discuss several architectural and engineering design visualizations we have produced.
King, Zachary A.; Drager, Andreas; Ebrahim, Ali; ...
2015-08-27
Escher is a web application for visualizing data on biological pathways. Three key features make Escher a uniquely effective tool for pathway visualization. First, users can rapidly design new pathway maps. Escher provides pathway suggestions based on user data and genome-scale models, so users can draw pathways in a semi-automated way. Second, users can visualize data related to genes or proteins on the associated reactions and pathways, using rules that define which enzymes catalyze each reaction. Thus, users can identify trends in common genomic data types (e.g. RNA-Seq, proteomics, ChIP)—in conjunction with metabolite- and reaction-oriented data types (e.g. metabolomics, fluxomics).more » Third, Escher harnesses the strengths of web technologies (SVG, D3, developer tools) so that visualizations can be rapidly adapted, extended, shared, and embedded. This paper provides examples of each of these features and explains how the development approach used for Escher can be used to guide the development of future visualization tools.« less
Interactive 3D visualization for theoretical virtual observatories
NASA Astrophysics Data System (ADS)
Dykes, T.; Hassan, A.; Gheller, C.; Croton, D.; Krokos, M.
2018-06-01
Virtual observatories (VOs) are online hubs of scientific knowledge. They encompass a collection of platforms dedicated to the storage and dissemination of astronomical data, from simple data archives to e-research platforms offering advanced tools for data exploration and analysis. Whilst the more mature platforms within VOs primarily serve the observational community, there are also services fulfilling a similar role for theoretical data. Scientific visualization can be an effective tool for analysis and exploration of data sets made accessible through web platforms for theoretical data, which often contain spatial dimensions and properties inherently suitable for visualization via e.g. mock imaging in 2D or volume rendering in 3D. We analyse the current state of 3D visualization for big theoretical astronomical data sets through scientific web portals and virtual observatory services. We discuss some of the challenges for interactive 3D visualization and how it can augment the workflow of users in a virtual observatory context. Finally we showcase a lightweight client-server visualization tool for particle-based data sets, allowing quantitative visualization via data filtering, highlighting two example use cases within the Theoretical Astrophysical Observatory.
Wiebrands, Michael; Malajczuk, Chris J; Woods, Andrew J; Rohl, Andrew L; Mancera, Ricardo L
2018-06-21
Molecular graphics systems are visualization tools which, upon integration into a 3D immersive environment, provide a unique virtual reality experience for research and teaching of biomolecular structure, function and interactions. We have developed a molecular structure and dynamics application, the Molecular Dynamics Visualization tool, that uses the Unity game engine combined with large scale, multi-user, stereoscopic visualization systems to deliver an immersive display experience, particularly with a large cylindrical projection display. The application is structured to separate the biomolecular modeling and visualization systems. The biomolecular model loading and analysis system was developed as a stand-alone C# library and provides the foundation for the custom visualization system built in Unity. All visual models displayed within the tool are generated using Unity-based procedural mesh building routines. A 3D user interface was built to allow seamless dynamic interaction with the model while being viewed in 3D space. Biomolecular structure analysis and display capabilities are exemplified with a range of complex systems involving cell membranes, protein folding and lipid droplets.
Huber, Timothy C; Krishnaraj, Arun; Monaghan, Dayna; Gaskin, Cree M
2018-05-18
Due to mandates from recent legislation, clinical decision support (CDS) software is being adopted by radiology practices across the country. This software provides imaging study decision support for referring providers at the point of order entry. CDS systems produce a large volume of data, providing opportunities for research and quality improvement. In order to better visualize and analyze trends in this data, an interactive data visualization dashboard was created using a commercially available data visualization platform. Following the integration of a commercially available clinical decision support product into the electronic health record, a dashboard was created using a commercially available data visualization platform (Tableau, Seattle, WA). Data generated by the CDS were exported from the data warehouse, where they were stored, into the platform. This allowed for real-time visualization of the data generated by the decision support software. The creation of the dashboard allowed the output from the CDS platform to be more easily analyzed and facilitated hypothesis generation. Integrating data visualization tools into clinical decision support tools allows for easier data analysis and can streamline research and quality improvement efforts.
Johnson, Eric O; Hancock, Dana B; Levy, Joshua L; Gaddis, Nathan C; Saccone, Nancy L; Bierut, Laura J; Page, Grier P
2013-05-01
A great promise of publicly sharing genome-wide association data is the potential to create composite sets of controls. However, studies often use different genotyping arrays, and imputation to a common set of SNPs has shown substantial bias: a problem which has no broadly applicable solution. Based on the idea that using differing genotyped SNP sets as inputs creates differential imputation errors and thus bias in the composite set of controls, we examined the degree to which each of the following occurs: (1) imputation based on the union of genotyped SNPs (i.e., SNPs available on one or more arrays) results in bias, as evidenced by spurious associations (type 1 error) between imputed genotypes and arbitrarily assigned case/control status; (2) imputation based on the intersection of genotyped SNPs (i.e., SNPs available on all arrays) does not evidence such bias; and (3) imputation quality varies by the size of the intersection of genotyped SNP sets. Imputations were conducted in European Americans and African Americans with reference to HapMap phase II and III data. Imputation based on the union of genotyped SNPs across the Illumina 1M and 550v3 arrays showed spurious associations for 0.2 % of SNPs: ~2,000 false positives per million SNPs imputed. Biases remained problematic for very similar arrays (550v1 vs. 550v3) and were substantial for dissimilar arrays (Illumina 1M vs. Affymetrix 6.0). In all instances, imputing based on the intersection of genotyped SNPs (as few as 30 % of the total SNPs genotyped) eliminated such bias while still achieving good imputation quality.
Abnet, Christian C.; Wang, Zhaoming; Song, Xin; Hu, Nan; Zhou, Fu-You; Freedman, Neal D.; Li, Xue-Min; Yu, Kai; Shu, Xiao-Ou; Yuan, Jian-Min; Zheng, Wei; Dawsey, Sanford M.; Liao, Linda M.; Lee, Maxwell P.; Ding, Ti; Qiao, You-Lin; Gao, Yu-Tang; Koh, Woon-Puay; Xiang, Yong-Bing; Tang, Ze-Zhong; Fan, Jin-Hu; Chung, Charles C.; Wang, Chaoyu; Wheeler, William; Yeager, Meredith; Yuenger, Jeff; Hutchinson, Amy; Jacobs, Kevin B.; Giffen, Carol A.; Burdett, Laurie; Fraumeni, Joseph F.; Tucker, Margaret A.; Chow, Wong-Ho; Zhao, Xue-Ke; Li, Jiang-Man; Li, Ai-Li; Sun, Liang-Dan; Wei, Wu; Li, Ji-Lin; Zhang, Peng; Li, Hong-Lei; Cui, Wen-Yan; Wang, Wei-Peng; Liu, Zhi-Cai; Yang, Xia; Fu, Wen-Jing; Cui, Ji-Li; Lin, Hong-Li; Zhu, Wen-Liang; Liu, Min; Chen, Xi; Chen, Jie; Guo, Li; Han, Jing-Jing; Zhou, Sheng-Li; Huang, Jia; Wu, Yue; Yuan, Chao; Huang, Jing; Ji, Ai-Fang; Kul, Jian-Wei; Fan, Zhong-Min; Wang, Jian-Po; Zhang, Dong-Yun; Zhang, Lian-Qun; Zhang, Wei; Chen, Yuan-Fang; Ren, Jing-Li; Li, Xiu-Min; Dong, Jin-Cheng; Xing, Guo-Lan; Guo, Zhi-Gang; Yang, Jian-Xue; Mao, Yi-Ming; Yuan, Yuan; Guo, Er-Tao; Zhang, Wei; Hou, Zhi-Chao; Liu, Jing; Li, Yan; Tang, Sa; Chang, Jia; Peng, Xiu-Qin; Han, Min; Yin, Wan-Li; Liu, Ya-Li; Hu, Yan-Long; Liu, Yu; Yang, Liu-Qin; Zhu, Fu-Guo; Yang, Xiu-Feng; Feng, Xiao-Shan; Wang, Zhou; Li, Yin; Gao, She-Gan; Liu, Hai-Lin; Yuan, Ling; Jin, Yan; Zhang, Yan-Rui; Sheyhidin, Ilyar; Li, Feng; Chen, Bao-Ping; Ren, Shu-Wei; Liu, Bin; Li, Dan; Zhang, Gao-Fu; Yue, Wen-Bin; Feng, Chang-Wei; Qige, Qirenwang; Zhao, Jian-Ting; Yang, Wen-Jun; Lei, Guang-Yan; Chen, Long-Qi; Li, En-Min; Xu, Li-Yan; Wu, Zhi-Yong; Bao, Zhi-Qin; Chen, Ji-Li; Li, Xian-Chang; Zhuang, Xiang; Zhou, Ying-Fa; Zuo, Xian-Bo; Dong, Zi-Ming; Wang, Lu-Wen; Fan, Xue-Pin; Wang, Jin; Zhou, Qi; Ma, Guo-Shun; Zhang, Qin-Xian; Liu, Hai; Jian, Xin-Ying; Lian, Sin-Yong; Wang, Jin-Sheng; Chang, Fu-Bao; Lu, Chang-Dong; Miao, Jian-Jun; Chen, Zhi-Guo; Wang, Ran; Guo, Ming; Fan, Zeng-Lin; Tao, Ping; Liu, Tai-Jing; Wei, Jin-Chang; Kong, Qing-Peng; Fan, Lei; Wang, Xian-Zeng; Gao, Fu-Sheng; Wang, Tian-Yun; Xie, Dong; Wang, Li; Chen, Shu-Qing; Yang, Wan-Cai; Hong, Jun-Yan; Wang, Liang; Qiu, Song-Liang; Goldstein, Alisa M.; Yuan, Zhi-Qing; Chanock, Stephen J.; Zhang, Xue-Jun; Taylor, Philip R.; Wang, Li-Dong
2012-01-01
Genome-wide association studies have identified susceptibility loci for esophageal squamous cell carcinoma (ESCC). We conducted a meta-analysis of all single-nucleotide polymorphisms (SNPs) that showed nominally significant P-values in two previously published genome-wide scans that included a total of 2961 ESCC cases and 3400 controls. The meta-analysis revealed five SNPs at 2q33 with P< 5 × 10−8, and the strongest signal was rs13016963, with a combined odds ratio (95% confidence interval) of 1.29 (1.19–1.40) and P= 7.63 × 10−10. An imputation analysis of 4304 SNPs at 2q33 suggested a single association signal, and the strongest imputed SNP associations were similar to those from the genotyped SNPs. We conducted an ancestral recombination graph analysis with 53 SNPs to identify one or more haplotypes that harbor the variants directly responsible for the detected association signal. This showed that the five SNPs exist in a single haplotype along with 45 imputed SNPs in strong linkage disequilibrium, and the strongest candidate was rs10201587, one of the genotyped SNPs. Our meta-analysis found genome-wide significant SNPs at 2q33 that map to the CASP8/ALS2CR12/TRAK2 gene region. Variants in CASP8 have been extensively studied across a spectrum of cancers with mixed results. The locus we identified appears to be distinct from the widely studied rs3834129 and rs1045485 SNPs in CASP8. Future studies of esophageal and other cancers should focus on comprehensive sequencing of this 2q33 locus and functional analysis of rs13016963 and rs10201587 and other strongly correlated variants. PMID:22323360
Abnet, Christian C; Wang, Zhaoming; Song, Xin; Hu, Nan; Zhou, Fu-You; Freedman, Neal D; Li, Xue-Min; Yu, Kai; Shu, Xiao-Ou; Yuan, Jian-Min; Zheng, Wei; Dawsey, Sanford M; Liao, Linda M; Lee, Maxwell P; Ding, Ti; Qiao, You-Lin; Gao, Yu-Tang; Koh, Woon-Puay; Xiang, Yong-Bing; Tang, Ze-Zhong; Fan, Jin-Hu; Chung, Charles C; Wang, Chaoyu; Wheeler, William; Yeager, Meredith; Yuenger, Jeff; Hutchinson, Amy; Jacobs, Kevin B; Giffen, Carol A; Burdett, Laurie; Fraumeni, Joseph F; Tucker, Margaret A; Chow, Wong-Ho; Zhao, Xue-Ke; Li, Jiang-Man; Li, Ai-Li; Sun, Liang-Dan; Wei, Wu; Li, Ji-Lin; Zhang, Peng; Li, Hong-Lei; Cui, Wen-Yan; Wang, Wei-Peng; Liu, Zhi-Cai; Yang, Xia; Fu, Wen-Jing; Cui, Ji-Li; Lin, Hong-Li; Zhu, Wen-Liang; Liu, Min; Chen, Xi; Chen, Jie; Guo, Li; Han, Jing-Jing; Zhou, Sheng-Li; Huang, Jia; Wu, Yue; Yuan, Chao; Huang, Jing; Ji, Ai-Fang; Kul, Jian-Wei; Fan, Zhong-Min; Wang, Jian-Po; Zhang, Dong-Yun; Zhang, Lian-Qun; Zhang, Wei; Chen, Yuan-Fang; Ren, Jing-Li; Li, Xiu-Min; Dong, Jin-Cheng; Xing, Guo-Lan; Guo, Zhi-Gang; Yang, Jian-Xue; Mao, Yi-Ming; Yuan, Yuan; Guo, Er-Tao; Zhang, Wei; Hou, Zhi-Chao; Liu, Jing; Li, Yan; Tang, Sa; Chang, Jia; Peng, Xiu-Qin; Han, Min; Yin, Wan-Li; Liu, Ya-Li; Hu, Yan-Long; Liu, Yu; Yang, Liu-Qin; Zhu, Fu-Guo; Yang, Xiu-Feng; Feng, Xiao-Shan; Wang, Zhou; Li, Yin; Gao, She-Gan; Liu, Hai-Lin; Yuan, Ling; Jin, Yan; Zhang, Yan-Rui; Sheyhidin, Ilyar; Li, Feng; Chen, Bao-Ping; Ren, Shu-Wei; Liu, Bin; Li, Dan; Zhang, Gao-Fu; Yue, Wen-Bin; Feng, Chang-Wei; Qige, Qirenwang; Zhao, Jian-Ting; Yang, Wen-Jun; Lei, Guang-Yan; Chen, Long-Qi; Li, En-Min; Xu, Li-Yan; Wu, Zhi-Yong; Bao, Zhi-Qin; Chen, Ji-Li; Li, Xian-Chang; Zhuang, Xiang; Zhou, Ying-Fa; Zuo, Xian-Bo; Dong, Zi-Ming; Wang, Lu-Wen; Fan, Xue-Pin; Wang, Jin; Zhou, Qi; Ma, Guo-Shun; Zhang, Qin-Xian; Liu, Hai; Jian, Xin-Ying; Lian, Sin-Yong; Wang, Jin-Sheng; Chang, Fu-Bao; Lu, Chang-Dong; Miao, Jian-Jun; Chen, Zhi-Guo; Wang, Ran; Guo, Ming; Fan, Zeng-Lin; Tao, Ping; Liu, Tai-Jing; Wei, Jin-Chang; Kong, Qing-Peng; Fan, Lei; Wang, Xian-Zeng; Gao, Fu-Sheng; Wang, Tian-Yun; Xie, Dong; Wang, Li; Chen, Shu-Qing; Yang, Wan-Cai; Hong, Jun-Yan; Wang, Liang; Qiu, Song-Liang; Goldstein, Alisa M; Yuan, Zhi-Qing; Chanock, Stephen J; Zhang, Xue-Jun; Taylor, Philip R; Wang, Li-Dong
2012-05-01
Genome-wide association studies have identified susceptibility loci for esophageal squamous cell carcinoma (ESCC). We conducted a meta-analysis of all single-nucleotide polymorphisms (SNPs) that showed nominally significant P-values in two previously published genome-wide scans that included a total of 2961 ESCC cases and 3400 controls. The meta-analysis revealed five SNPs at 2q33 with P< 5 × 10(-8), and the strongest signal was rs13016963, with a combined odds ratio (95% confidence interval) of 1.29 (1.19-1.40) and P= 7.63 × 10(-10). An imputation analysis of 4304 SNPs at 2q33 suggested a single association signal, and the strongest imputed SNP associations were similar to those from the genotyped SNPs. We conducted an ancestral recombination graph analysis with 53 SNPs to identify one or more haplotypes that harbor the variants directly responsible for the detected association signal. This showed that the five SNPs exist in a single haplotype along with 45 imputed SNPs in strong linkage disequilibrium, and the strongest candidate was rs10201587, one of the genotyped SNPs. Our meta-analysis found genome-wide significant SNPs at 2q33 that map to the CASP8/ALS2CR12/TRAK2 gene region. Variants in CASP8 have been extensively studied across a spectrum of cancers with mixed results. The locus we identified appears to be distinct from the widely studied rs3834129 and rs1045485 SNPs in CASP8. Future studies of esophageal and other cancers should focus on comprehensive sequencing of this 2q33 locus and functional analysis of rs13016963 and rs10201587 and other strongly correlated variants.
Carty, Cara L; Buzková, Petra; Fornage, Myriam; Franceschini, Nora; Cole, Shelley; Heiss, Gerardo; Hindorff, Lucia A; Howard, Barbara V; Mann, Sue; Martin, Lisa W; Zhang, Ying; Matise, Tara C; Prentice, Ross; Reiner, Alexander P; Kooperberg, Charles
2012-04-01
Genome-wide association studies (GWAS) have identified loci associated with ischemic stroke (IS) and cardiovascular disease (CVD) in European-descent individuals, but their replication in different populations has been largely unexplored. Nine single nucleotide polymorphisms (SNPs) selected from GWAS and meta-analyses of stroke, and 86 SNPs previously associated with myocardial infarction and CVD risk factors, including blood lipids (high density lipoprotein [HDL], low density lipoprotein [LDL], and triglycerides), type 2 diabetes, and body mass index (BMI), were investigated for associations with incident IS in European Americans (EA) N=26 276, African-Americans (AA) N=8970, and American Indians (AI) N=3570 from the Population Architecture using Genomics and Epidemiology Study. Ancestry-specific fixed effects meta-analysis with inverse variance weighting was used to combine study-specific log hazard ratios from Cox proportional hazards models. Two of 9 stroke SNPs (rs783396 and rs1804689) were significantly associated with [corrected] IS hazard in AA; none were significant in this large EA cohort. Of 73 CVD risk factor SNPs tested in EA, 2 (HDL and triglycerides SNPs) were associated with IS. In AA, SNPs associated with LDL, HDL, and BMI were significantly associated with IS (3 of 86 SNPs tested). Out of 58 SNPs tested in AI, 1 LDL SNP was significantly associated with IS. Our analyses showing lack of replication in spite of reasonable power for many stroke SNPs and differing results by ancestry highlight the need to follow up on GWAS findings and conduct genetic association studies in diverse populations. We found modest IS associations with BMI and lipids SNPs, though these findings require confirmation.
Genome-wide association study of sporadic brain arteriovenous malformations.
Weinsheimer, Shantel; Bendjilali, Nasrine; Nelson, Jeffrey; Guo, Diana E; Zaroff, Jonathan G; Sidney, Stephen; McCulloch, Charles E; Al-Shahi Salman, Rustam; Berg, Jonathan N; Koeleman, Bobby P C; Simon, Matthias; Bostroem, Azize; Fontanella, Marco; Sturiale, Carmelo L; Pola, Roberto; Puca, Alfredo; Lawton, Michael T; Young, William L; Pawlikowska, Ludmila; Klijn, Catharina J M; Kim, Helen
2016-09-01
The pathogenesis of sporadic brain arteriovenous malformations (BAVMs) remains unknown, but studies suggest a genetic component. We estimated the heritability of sporadic BAVM and performed a genome-wide association study (GWAS) to investigate association of common single nucleotide polymorphisms (SNPs) with risk of sporadic BAVM in the international, multicentre Genetics of Arteriovenous Malformation (GEN-AVM) consortium. The Caucasian discovery cohort included 515 BAVM cases and 1191 controls genotyped using Affymetrix genome-wide SNP arrays. Genotype data were imputed to 1000 Genomes Project data, and well-imputed SNPs (>0.01 minor allele frequency) were analysed for association with BAVM. 57 top BAVM-associated SNPs (51 SNPs with p<10(-05) or p<10(-04) in candidate pathway genes, and 6 candidate BAVM SNPs) were tested in a replication cohort including 608 BAVM cases and 744 controls. The estimated heritability of BAVM was 17.6% (SE 8.9%, age and sex-adjusted p=0.015). None of the SNPs were significantly associated with BAVM in the replication cohort after correction for multiple testing. 6 SNPs had a nominal p<0.1 in the replication cohort and map to introns in EGFEM1P, SP4 and CDKAL1 or near JAG1 and BNC2. Of the 6 candidate SNPs, 2 in ACVRL1 and MMP3 had a nominal p<0.05 in the replication cohort. We performed the first GWAS of sporadic BAVM in the largest BAVM cohort assembled to date. No GWAS SNPs were replicated, suggesting that common SNPs do not contribute strongly to BAVM susceptibility. However, heritability estimates suggest a modest but significant genetic contribution. Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://www.bmj.com/company/products-services/rights-and-licensing/
Visualizing railroad operations : a tool for planning and monitoring railroad traffic
DOT National Transportation Integrated Search
2009-01-01
This report provides an overview of the development and technology transfer of the Railroad Traffic Planner application, a visualization tool with string line diagrams that show train positions over time. The Railroad Traffic Planner provides support...
Vanbellingen, Tim; Schumacher, Rahel; Eggenberger, Noëmi; Hopfner, Simone; Cazzoli, Dario; Preisig, Basil C; Bertschi, Manuel; Nyffeler, Thomas; Gutbrod, Klemens; Bassetti, Claudio L; Bohlhalter, Stephan; Müri, René M
2015-05-01
According to the direct matching hypothesis, perceived movements automatically activate existing motor components through matching of the perceived gesture and its execution. The aim of the present study was to test the direct matching hypothesis by assessing whether visual exploration behavior correlate with deficits in gestural imitation in left hemisphere damaged (LHD) patients. Eighteen LHD patients and twenty healthy control subjects took part in the study. Gesture imitation performance was measured by the test for upper limb apraxia (TULIA). Visual exploration behavior was measured by an infrared eye-tracking system. Short videos including forty gestures (20 meaningless and 20 communicative gestures) were presented. Cumulative fixation duration was measured in different regions of interest (ROIs), namely the face, the gesturing hand, the body, and the surrounding environment. Compared to healthy subjects, patients fixated significantly less the ROIs comprising the face and the gesturing hand during the exploration of emblematic and tool-related gestures. Moreover, visual exploration of tool-related gestures significantly correlated with tool-related imitation as measured by TULIA in LHD patients. Patients and controls did not differ in the visual exploration of meaningless gestures, and no significant relationships were found between visual exploration behavior and the imitation of emblematic and meaningless gestures in TULIA. The present study thus suggests that altered visual exploration may lead to disturbed imitation of tool related gestures, however not of emblematic and meaningless gestures. Consequently, our findings partially support the direct matching hypothesis. Copyright © 2015 Elsevier Ltd. All rights reserved.
Visualization of Documents and Concepts in Neuroinformatics with the 3D-SE Viewer
Naud, Antoine; Usui, Shiro; Ueda, Naonori; Taniguchi, Tatsuki
2007-01-01
A new interactive visualization tool is proposed for mining text data from various fields of neuroscience. Applications to several text datasets are presented to demonstrate the capability of the proposed interactive tool to visualize complex relationships between pairs of lexical entities (with some semantic contents) such as terms, keywords, posters, or papers' abstracts. Implemented as a Java applet, this tool is based on the spherical embedding (SE) algorithm, which was designed for the visualization of bipartite graphs. Items such as words and documents are linked on the basis of occurrence relationships, which can be represented in a bipartite graph. These items are visualized by embedding the vertices of the bipartite graph on spheres in a three-dimensional (3-D) space. The main advantage of the proposed visualization tool is that 3-D layouts can convey more information than planar or linear displays of items or graphs. Different kinds of information extracted from texts, such as keywords, indexing terms, or topics are visualized, allowing interactive browsing of various fields of research featured by keywords, topics, or research teams. A typical use of the 3D-SE viewer is quick browsing of topics displayed on a sphere, then selecting one or several item(s) displays links to related terms on another sphere representing, e.g., documents or abstracts, and provides direct online access to the document source in a database, such as the Visiome Platform or the SfN Annual Meeting. Developed as a Java applet, it operates as a tool on top of existing resources. PMID:18974802
Visualization of Documents and Concepts in Neuroinformatics with the 3D-SE Viewer.
Naud, Antoine; Usui, Shiro; Ueda, Naonori; Taniguchi, Tatsuki
2007-01-01
A new interactive visualization tool is proposed for mining text data from various fields of neuroscience. Applications to several text datasets are presented to demonstrate the capability of the proposed interactive tool to visualize complex relationships between pairs of lexical entities (with some semantic contents) such as terms, keywords, posters, or papers' abstracts. Implemented as a Java applet, this tool is based on the spherical embedding (SE) algorithm, which was designed for the visualization of bipartite graphs. Items such as words and documents are linked on the basis of occurrence relationships, which can be represented in a bipartite graph. These items are visualized by embedding the vertices of the bipartite graph on spheres in a three-dimensional (3-D) space. The main advantage of the proposed visualization tool is that 3-D layouts can convey more information than planar or linear displays of items or graphs. Different kinds of information extracted from texts, such as keywords, indexing terms, or topics are visualized, allowing interactive browsing of various fields of research featured by keywords, topics, or research teams. A typical use of the 3D-SE viewer is quick browsing of topics displayed on a sphere, then selecting one or several item(s) displays links to related terms on another sphere representing, e.g., documents or abstracts, and provides direct online access to the document source in a database, such as the Visiome Platform or the SfN Annual Meeting. Developed as a Java applet, it operates as a tool on top of existing resources.
NASA Astrophysics Data System (ADS)
Eliazar, Iddo
2016-07-01
The study of socioeconomic inequality is of substantial importance, scientific and general alike. The graphic visualization of inequality is commonly conveyed by Lorenz curves. While Lorenz curves are a highly effective statistical tool for quantifying the distribution of wealth in human societies, they are less effective a tool for the visual depiction of socioeconomic inequality. This paper introduces an alternative to Lorenz curves-the hill curves. On the one hand, the hill curves are a potent scientific tool: they provide detailed scans of the rich-poor gaps in human societies under consideration, and are capable of accommodating infinitely many degrees of freedom. On the other hand, the hill curves are a powerful infographic tool: they visualize inequality in a most vivid and tangible way, with no quantitative skills that are required in order to grasp the visualization. The application of hill curves extends far beyond socioeconomic inequality. Indeed, the hill curves are highly effective 'hyperspectral' measures of statistical variability that are applicable in the context of size distributions at large. This paper establishes the notion of hill curves, analyzes them, and describes their application in the context of general size distributions.
Visual Information for the Desktop, version 1.0
DOE Office of Scientific and Technical Information (OSTI.GOV)
2006-03-29
VZIN integrates visual analytics capabilities into popular desktop tools to aid a user in searching and understanding an information space. VZIN allows users to Drag-Drop-Visualize-Explore-Organize information within tools such as Microsoft Office, Windows Explorer, Excel, and Outlook. VZIN is tailorable to specific client or industry requirements. VZIN follows the desktop metaphors so that advanced analytical capabilities are available with minimal user training.
From a Gloss to a Learning Tool: Does Visual Aids Enhance Better Sentence Comprehension?
ERIC Educational Resources Information Center
Sato, Takeshi; Suzuki, Akio
2012-01-01
The aim of this study is to optimize CALL environments as a learning tool rather than a gloss, focusing on the learning of polysemous words which refer to spatial relationship between objects. A lot of research has already been conducted to examine the efficacy of visual glosses while reading L2 texts and has reported that visual glosses can be…
ERIC Educational Resources Information Center
Altunay Arslantekin, Banu
2017-01-01
Purpose: Visually impaired people are weak in terms of their learning words and concepts by hearing them and their experience of the world with their bodies. In addition to developing a standardized assessment tool in the Development of Orientation and Mobility Skill Assessment Tool (OMSAT/YOBDA) for Visually Impaired Students Project, supported…
CTViz: A tool for the visualization of transport in nanocomposites.
Beach, Benjamin; Brown, Joshua; Tarlton, Taylor; Derosa, Pedro A
2016-05-01
A visualization tool (CTViz) for charge transport processes in 3-D hybrid materials (nanocomposites) was developed, inspired by the need for a graphical application to assist in code debugging and data presentation of an existing in-house code. As the simulation code grew, troubleshooting problems grew increasingly difficult without an effective way to visualize 3-D samples and charge transport in those samples. CTViz is able to produce publication and presentation quality visuals of the simulation box, as well as static and animated visuals of the paths of individual carriers through the sample. CTViz was designed to provide a high degree of flexibility in the visualization of the data. A feature that characterizes this tool is the use of shade and transparency levels to highlight important details in the morphology or in the transport paths by hiding or dimming elements of little relevance to the current view. This is fundamental for the visualization of 3-D systems with complex structures. The code presented here provides these required capabilities, but has gone beyond the original design and could be used as is or easily adapted for the visualization of other particulate transport where transport occurs on discrete paths. Copyright © 2016 Elsevier Inc. All rights reserved.
A variant reference data set for the Africanized honeybee, Apis mellifera
Kadri, Samir M.; Harpur, Brock A.; Orsi, Ricardo O.; Zayed, Amro
2016-01-01
The Africanized honeybee (AHB) is a population of Apis mellifera found in the Americas. AHBs originated in 1956 in Rio Clara, Brazil where imported African A. m. scutellata escaped and hybridized with local populations of European A. mellifera. Africanized populations can now be found from Northern Argentina to the Southern United States. AHBs—often referred to as ‘Killer Bees’— are a major concern to the beekeeping industry as well as a model for the evolutionary genetics of colony defence. We performed high coverage pooled-resequencing of 360 diploid workers from 30 Brazilian AHB colonies using Illumina Hi-Seq (150 bp PE). This yielded a high density SNP data set with an average read depth at each site of 20.25 reads. With 3,606,720 SNPs and 155,336 SNPs within 11,365 genes, this data set is the largest genomic resource available for AHBs and will enable high-resolution studies of the population dynamics, evolution, and genetics of this successful biological invader, in addition to facilitating the development of SNP-based tools for identifying AHBs. PMID:27824336
Pruna, Ricard; Til, Lluis; Artells, Rosa
2014-01-01
Summary Platelet-rich plasma (PRP) is a new powerful biological tool in sports medicine, when used to treat tendon, ligament and muscle injuries. PRP is a fraction of autologous whole blood containing an increased number of platelets and a wide variety of cytokines that can improve and accelerate the healing of various tissues. An analysis of the literature shows promising pre-clinical results for PRP treatment, but there is a lack of solid clinical proof to support its use in sports medicine, and in fact, clinical findings on individual responses to PRP treatment are contradictory. These contradictions may be due to interindividual differences in the presence of single nucleotide polymorphisms (SNPs) in genes related to PRPs and/or their receptors. These SNPs can determine a greater or lesser response to this treatment and consequently a shorter or longer recovery time. We have focused our attention in the study of genes related to PRP with the aim to develope a genetic profile that will identify the individuals and injuries most likely to benefit from PRP treatment. PMID:24932449
Rasal, Kiran D; Shah, Tejas M; Vaidya, Megha; Jakhesara, Subhash J; Joshi, Chaitanya G
2015-06-01
The recent advances in high throughput sequencing technology accelerate possible ways for the study of genome wide variation in several organisms and associated consequences. In the present study, mutations in TGFBR3 showing significant association with FCR trait in chicken during exome sequencing were further analyzed. Out of four SNPs, one nsSNP p.Val451Leu was found in the coding region of TGFBR3. In silico tools such as SnpSift and PANTHER predicted it as deleterious (0.04) and to be tolerated, respectively, while I-Mutant revealed that protein stability decreased. The TGFBR3 I-TASSER model has a C-score of 0.85, which was validated using PROCHECK. Based on MD simulation, mutant protein structure deviated from native with RMSD 0.08 Å due to change in the H-bonding distances of mutant residue. The docking of TGFBR3 with interacting TGFBR2 inferred that mutant required more global energy. Therefore, the present study will provide useful information about functional SNPs that have an impact on FCR traits.
A variant reference data set for the Africanized honeybee, Apis mellifera.
Kadri, Samir M; Harpur, Brock A; Orsi, Ricardo O; Zayed, Amro
2016-11-08
The Africanized honeybee (AHB) is a population of Apis mellifera found in the Americas. AHBs originated in 1956 in Rio Clara, Brazil where imported African A. m. scutellata escaped and hybridized with local populations of European A. mellifera. Africanized populations can now be found from Northern Argentina to the Southern United States. AHBs-often referred to as 'Killer Bees'- are a major concern to the beekeeping industry as well as a model for the evolutionary genetics of colony defence. We performed high coverage pooled-resequencing of 360 diploid workers from 30 Brazilian AHB colonies using Illumina Hi-Seq (150 bp PE). This yielded a high density SNP data set with an average read depth at each site of 20.25 reads. With 3,606,720 SNPs and 155,336 SNPs within 11,365 genes, this data set is the largest genomic resource available for AHBs and will enable high-resolution studies of the population dynamics, evolution, and genetics of this successful biological invader, in addition to facilitating the development of SNP-based tools for identifying AHBs.
Population Structure With Localized Haplotype Clusters
Browning, Sharon R.; Weir, Bruce S.
2010-01-01
We propose a multilocus version of FST and a measure of haplotype diversity using localized haplotype clusters. Specifically, we use haplotype clusters identified with BEAGLE, which is a program implementing a hidden Markov model for localized haplotype clustering and performing several functions including inference of haplotype phase. We apply this methodology to HapMap phase 3 data. With this haplotype-cluster approach, African populations have highest diversity and lowest divergence from the ancestral population, East Asian populations have lowest diversity and highest divergence, and other populations (European, Indian, and Mexican) have intermediate levels of diversity and divergence. These relationships accord with expectation based on other studies and accepted models of human history. In contrast, the population-specific FST estimates obtained directly from single-nucleotide polymorphisms (SNPs) do not reflect such expected relationships. We show that ascertainment bias of SNPs has less impact on the proposed haplotype-cluster-based FST than on the SNP-based version, which provides a potential explanation for these results. Thus, these new measures of FST and haplotype-cluster diversity provide an important new tool for population genetic analysis of high-density SNP data. PMID:20457877
Development and use of molecular markers: past and present.
Grover, Atul; Sharma, P C
2016-01-01
Molecular markers, due to their stability, cost-effectiveness and ease of use provide an immensely popular tool for a variety of applications including genome mapping, gene tagging, genetic diversity diversity, phylogenetic analysis and forensic investigations. In the last three decades, a number of molecular marker techniques have been developed and exploited worldwide in different systems. However, only a handful of these techniques, namely RFLPs, RAPDs, AFLPs, ISSRs, SSRs and SNPs have received global acceptance. A recent revolution in DNA sequencing techniques has taken the discovery and application of molecular markers to high-throughput and ultrahigh-throughput levels. Although, the choice of marker will obviously depend on the targeted use, microsatellites, SNPs and genotyping by sequencing (GBS) largely fulfill most of the user requirements. Further, modern transcriptomic and functional markers will lead the ventures onto high-density genetic map construction, identification of QTLs, breeding and conservation strategies in times to come in combination with other high throughput techniques. This review presents an overview of different marker technologies and their variants with a comparative account of their characteristic features and applications.
Different Strokes for Different Folks: Visual Presentation Design between Disciplines
Gomez, Steven R.; Jianu, Radu; Ziemkiewicz, Caroline; Guo, Hua; Laidlaw, David H.
2015-01-01
We present an ethnographic study of design differences in visual presentations between academic disciplines. Characterizing design conventions between users and data domains is an important step in developing hypotheses, tools, and design guidelines for information visualization. In this paper, disciplines are compared at a coarse scale between four groups of fields: social, natural, and formal sciences; and the humanities. Two commonplace presentation types were analyzed: electronic slideshows and whiteboard “chalk talks”. We found design differences in slideshows using two methods – coding and comparing manually-selected features, like charts and diagrams, and an image-based analysis using PCA called eigenslides. In whiteboard talks with controlled topics, we observed design behaviors, including using representations and formalisms from a participant’s own discipline, that suggest authors might benefit from novel assistive tools for designing presentations. Based on these findings, we discuss opportunities for visualization ethnography and human-centered authoring tools for visual information. PMID:26357149
Icarus: visualizer for de novo assembly evaluation.
Mikheenko, Alla; Valin, Gleb; Prjibelski, Andrey; Saveliev, Vladislav; Gurevich, Alexey
2016-11-01
: Data visualization plays an increasingly important role in NGS data analysis. With advances in both sequencing and computational technologies, it has become a new bottleneck in genomics studies. Indeed, evaluation of de novo genome assemblies is one of the areas that can benefit from the visualization. However, even though multiple quality assessment methods are now available, existing visualization tools are hardly suitable for this purpose. Here, we present Icarus-a novel genome visualizer for accurate assessment and analysis of genomic draft assemblies, which is based on the tool QUAST. Icarus can be used in studies where a related reference genome is available, as well as for non-model organisms. The tool is available online and as a standalone application. http://cab.spbu.ru/software/icarus CONTACT: aleksey.gurevich@spbu.ruSupplementary information: Supplementary data are available at Bioinformatics online. © The Author 2016. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.
Integrating advanced visualization technology into the planetary Geoscience workflow
NASA Astrophysics Data System (ADS)
Huffman, John; Forsberg, Andrew; Loomis, Andrew; Head, James; Dickson, James; Fassett, Caleb
2011-09-01
Recent advances in computer visualization have allowed us to develop new tools for analyzing the data gathered during planetary missions, which is important, since these data sets have grown exponentially in recent years to tens of terabytes in size. As part of the Advanced Visualization in Solar System Exploration and Research (ADVISER) project, we utilize several advanced visualization techniques created specifically with planetary image data in mind. The Geoviewer application allows real-time active stereo display of images, which in aggregate have billions of pixels. The ADVISER desktop application platform allows fast three-dimensional visualization of planetary images overlain on digital terrain models. Both applications include tools for easy data ingest and real-time analysis in a programmatic manner. Incorporation of these tools into our everyday scientific workflow has proved important for scientific analysis, discussion, and publication, and enabled effective and exciting educational activities for students from high school through graduate school.
Different Strokes for Different Folks: Visual Presentation Design between Disciplines.
Gomez, S R; Jianu, R; Ziemkiewicz, C; Guo, Hua; Laidlaw, D H
2012-12-01
We present an ethnographic study of design differences in visual presentations between academic disciplines. Characterizing design conventions between users and data domains is an important step in developing hypotheses, tools, and design guidelines for information visualization. In this paper, disciplines are compared at a coarse scale between four groups of fields: social, natural, and formal sciences; and the humanities. Two commonplace presentation types were analyzed: electronic slideshows and whiteboard "chalk talks". We found design differences in slideshows using two methods - coding and comparing manually-selected features, like charts and diagrams, and an image-based analysis using PCA called eigenslides. In whiteboard talks with controlled topics, we observed design behaviors, including using representations and formalisms from a participant's own discipline, that suggest authors might benefit from novel assistive tools for designing presentations. Based on these findings, we discuss opportunities for visualization ethnography and human-centered authoring tools for visual information.
Wang, Yinghua; Yan, Jiaqing; Wen, Jianbin; Yu, Tao; Li, Xiaoli
2016-01-01
Before epilepsy surgeries, intracranial electroencephalography (iEEG) is often employed in function mapping and epileptogenic foci localization. Although the implanted electrodes provide crucial information for epileptogenic zone resection, a convenient clinical tool for electrode position registration and Brain Function Mapping (BFM) visualization is still lacking. In this study, we developed a BFM Tool, which facilitates electrode position registration and BFM visualization, with an application to epilepsy surgeries. The BFM Tool mainly utilizes electrode location registration and function mapping based on pre-defined brain models from other software. In addition, the electrode node and mapping properties, such as the node size/color, edge color/thickness, mapping method, can be adjusted easily using the setting panel. Moreover, users may manually import/export location and connectivity data to generate figures for further application. The role of this software is demonstrated by a clinical study of language area localization. The BFM Tool helps clinical doctors and researchers visualize implanted electrodes and brain functions in an easy, quick and flexible manner. Our tool provides convenient electrode registration, easy brain function visualization, and has good performance. It is clinical-oriented and is easy to deploy and use. The BFM tool is suitable for epilepsy and other clinical iEEG applications.
Wang, Yinghua; Yan, Jiaqing; Wen, Jianbin; Yu, Tao; Li, Xiaoli
2016-01-01
Objects: Before epilepsy surgeries, intracranial electroencephalography (iEEG) is often employed in function mapping and epileptogenic foci localization. Although the implanted electrodes provide crucial information for epileptogenic zone resection, a convenient clinical tool for electrode position registration and Brain Function Mapping (BFM) visualization is still lacking. In this study, we developed a BFM Tool, which facilitates electrode position registration and BFM visualization, with an application to epilepsy surgeries. Methods: The BFM Tool mainly utilizes electrode location registration and function mapping based on pre-defined brain models from other software. In addition, the electrode node and mapping properties, such as the node size/color, edge color/thickness, mapping method, can be adjusted easily using the setting panel. Moreover, users may manually import/export location and connectivity data to generate figures for further application. The role of this software is demonstrated by a clinical study of language area localization. Results: The BFM Tool helps clinical doctors and researchers visualize implanted electrodes and brain functions in an easy, quick and flexible manner. Conclusions: Our tool provides convenient electrode registration, easy brain function visualization, and has good performance. It is clinical-oriented and is easy to deploy and use. The BFM tool is suitable for epilepsy and other clinical iEEG applications. PMID:27199729
CLUSTAG: hierarchical clustering and graph methods for selecting tag SNPs.
Ao, S I; Yip, Kevin; Ng, Michael; Cheung, David; Fong, Pui-Yee; Melhado, Ian; Sham, Pak C
2005-04-15
Cluster and set-cover algorithms are developed to obtain a set of tag single nucleotide polymorphisms (SNPs) that can represent all the known SNPs in a chromosomal region, subject to the constraint that all SNPs must have a squared correlation R2>C with at least one tag SNP, where C is specified by the user. http://hkumath.hku.hk/web/link/CLUSTAG/CLUSTAG.html mng@maths.hku.hk.
Rashmi, Venkatasubbaiah; Sanjay, Konasur R
2017-04-01
Consistent search of plants for green synthesis of silver nanoparticles (SNPs) is an important arena in Nanomedicine. This study focuses on synthesis of SNPs using bioreduction of silver nitrate (AgNO 3 ) by aqueous root extract of Decalepis hamiltonii . The biosynthesis of SNPs was monitored by UV-vis analysis at absorbance maxima 432 nm. The fluorescence emission spectra of SNPs illustrated the broad emission peak 450-483 nm at different excitation wavelengths. The surface characteristics were studied by scanning electron microscope and atomic force microscopy, showed spherical shape of SNPs and dynamic light scattering analysis confirmed the average particle size 32.5 nm and the presence of metallic silver was confirmed by energy dispersive X-ray. Face centred cubic structure with crystal size 33.3 nm was revealed by powder X-ray diffraction. Fourier transform infrared spectroscopy indicated the biomolecules involved in the reduction mainly polyols and phenols present in root extracts were found to be responsible for the synthesis of SNPs. The stability and charge on SNPs were revealed by zeta potential analysis. In addition, on therapeutic forum, the synthesised SNPs elicit antioxidant and antimicrobial activity against Bacillus cereus , Bacillus licheniformis , Escherichia coli , Pseudomonas aeruginosa and Staphylococcus aureus .
The versican gene and the risk of intracranial aneurysms.
Ruigrok, Ynte M; Rinkel, Gabriël J E; Wijmenga, Cisca
2006-09-01
The proteoglycan versican is an excellent candidate gene for intracranial aneurysms (IAs) because it plays an important role in extracellular matrix assembly and is localized in a previously implicated locus for IAs on chromosome 5q. We analyzed all the common variations using 16-tag single nucleotide polymorphisms (SNPs) and haplotypes in the versican gene using a 2-stage genotyping approach. For stage 1, 16 SNPs were genotyped in 307 cases and 639 controls. For stage 2, the two SNPs yielding the most significant associations (P<0.01) were genotyped in a second independent cohort of 310 cases for confirmation of the associations. In stage 1, we found several SNPs in strong linkage disequilibrium and haplotypes constituting these SNPs associated with IAs in the Dutch population (strongest SNP association for rs173686 with odds ratio=1.34, 95% CI=1.09 to 1.65, P=0.004). In stage 2, we confirmed association for the 2 SNPs with the most significant associations (strongest SNP association for rs173686 with odds ratio=1.36, 95% CI=1.11 to 1.67, P=0.003). SNPs in strong linkage disequilibrium and haplotypes constituting these SNPs in the versican gene are associated with IAs suggesting that variation in or near the versican gene plays a role in susceptibility to IAs.
Liu, Yanfang; Liao, Huidan; Liu, Ying; Guo, Juanjuan; Sun, Yi; Fu, Xiaoliang; Xiao, Ding; Cai, Jifeng; Lan, Lingmei; Xie, Pingli; Zha, Lagabaiyila
2017-04-01
Nonbinary single-nucleotide polymorphisms (SNPs) are potential forensic genetic markers because their discrimination power is greater than that of normal binary SNPs, and that they can detect highly degraded samples. We previously developed a nonbinary SNP multiplex typing assay. In this study, we selected additional 20 nonbinary SNPs from the NCBI SNP database and verified them through pyrosequencing. These 20 nonbinary SNPs were analyzed using the fluorescent-labeled SNaPshot multiplex SNP typing method. The allele frequencies and genetic parameters of these 20 nonbinary SNPs were determined among 314 unrelated individuals from Han populations from China. The total power of discrimination was 0.9999999999994, and the cumulative probability of exclusion was 0.9986. Moreover, the result of the combination of this 20 nonbinary SNP assay with the 20 nonbinary SNP assay we previously developed demonstrated that the cumulative probability of exclusion of the 40 nonbinary SNPs was 0.999991 and that no significant linkage disequilibrium was observed in all 40 nonbinary SNPs. Thus, we concluded that this new system consisting of new 20 nonbinary SNPs could provide highly informative polymorphic data which would be further used in forensic application and would serve as a potentially valuable supplement to forensic DNA analysis. © 2017 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.
Delgado-Lista, Javier; Perez-Martinez, Pablo; Solivera, Juan; Garcia-Rios, Antonio; Perez-Caballero, A I; Lovegrove, Julie A; Drevon, Christian A; Defoort, Catherine; Blaak, Ellen E; Dembinska-Kieć, Aldona; Risérus, Ulf; Herruzo-Gomez, Ezequiel; Camargo, Antonio; Ordovas, Jose M; Roche, Helen; Lopez-Miranda, José
2014-02-01
Metabolic syndrome (MetS) is a high-prevalence condition characterized by altered energy metabolism, insulin resistance, and elevated cardiovascular risk. Although many individual single nucleotide polymorphisms (SNPs) have been linked to certain MetS features, there are few studies analyzing the influence of SNPs on carbohydrate metabolism in MetS. A total of 904 SNPs (tag SNPs and functional SNPs) were tested for influence on 8 fasting and dynamic markers of carbohydrate metabolism, by performance of an intravenous glucose tolerance test in 450 participants in the LIPGENE study. From 382 initial gene-phenotype associations between SNPs and any phenotypic variables, 61 (16% of the preselected variables) remained significant after bootstrapping. Top SNPs affecting glucose metabolism variables were as follows: fasting glucose, rs26125 (PPARGC1B); fasting insulin, rs4759277 (LRP1); C-peptide, rs4759277 (LRP1); homeostasis assessment of insulin resistance, rs4759277 (LRP1); quantitative insulin sensitivity check index, rs184003 (AGER); sensitivity index, rs7301876 (ABCC9), acute insulin response to glucose, rs290481 (TCF7L2); and disposition index, rs12691 (CEBPA). We describe here the top SNPs linked to phenotypic features in carbohydrate metabolism among approximately 1000 candidate gene variations in fasting and postprandial samples of 450 patients with MetS from the LIPGENE study.
Elastic-net regularization approaches for genome-wide association studies of rheumatoid arthritis.
Cho, Seoae; Kim, Haseong; Oh, Sohee; Kim, Kyunga; Park, Taesung
2009-12-15
The current trend in genome-wide association studies is to identify regions where the true disease-causing genes may lie by evaluating thousands of single-nucleotide polymorphisms (SNPs) across the whole genome. However, many challenges exist in detecting disease-causing genes among the thousands of SNPs. Examples include multicollinearity and multiple testing issues, especially when a large number of correlated SNPs are simultaneously tested. Multicollinearity can often occur when predictor variables in a multiple regression model are highly correlated, and can cause imprecise estimation of association. In this study, we propose a simple stepwise procedure that identifies disease-causing SNPs simultaneously by employing elastic-net regularization, a variable selection method that allows one to address multicollinearity. At Step 1, the single-marker association analysis was conducted to screen SNPs. At Step 2, the multiple-marker association was scanned based on the elastic-net regularization. The proposed approach was applied to the rheumatoid arthritis (RA) case-control data set of Genetic Analysis Workshop 16. While the selected SNPs at the screening step are located mostly on chromosome 6, the elastic-net approach identified putative RA-related SNPs on other chromosomes in an increased proportion. For some of those putative RA-related SNPs, we identified the interactions with sex, a well known factor affecting RA susceptibility.
Allele-Skewed DNA Modification in the Brain: Relevance to a Schizophrenia GWAS
Gagliano, Sarah A.; Ptak, Carolyn; Mak, Denise Y.F.; Shamsi, Mehrdad; Oh, Gabriel; Knight, Joanne; Boutros, Paul C.; Petronis, Arturas
2016-01-01
Numerous recent studies have suggested that phenotypic effects of DNA sequence variants can be mediated or modulated by their epigenetic marks, such as allele-skewed DNA modification (ASM). Using Affymetrix SNP microarrays, we performed a comprehensive search of ASM effects in human post-mortem brain and sperm samples (total n = 256) from individuals with major psychosis and control individuals. Depending on the phenotypic category of the brain samples, 1.4%–7.5% of interrogated SNPs exhibited ASM effects. Next, we investigated ASM in the context of genetic studies of schizophrenia and detected that brain ASM SNPs were significantly overrepresented among sub-threshold SNPs from a schizophrenia genome-wide association study (GWAS). Brain ASM SNPs showed a much stronger enrichment in a schizophrenia GWAS than in 17 large GWASs of non-psychiatric diseases and traits, arguing that ASM effects are at least partially tissue specific. Studies of germline and control brain ASM SNPs supported a causal association between ASM and schizophrenia. Finally, significantly higher proportions of ASM SNPs than of non-ASM SNPs were detected at loci exhibiting epigenetic signatures of enhancers and promoters, and they were overrepresented within transcription factor binding regions and DNase I hypersensitive sites. All of these findings collectively indicate that ASM SNPs should be prioritized in follow-up GWASs. PMID:27087318
Tool use and the distalization of the end-effector
Bonaiuto, James B.; Jacobs, Stéphane; Frey, Scott H.
2009-01-01
We review recent neurophysiological data from macaques and humans suggesting that the use of tools extends the internal representation of the actor’s hand, and relate it to our modeling of the visual control of grasping. We introduce the idea that, in addition to extending the body schema to incorporate the tool, tool use involves distalization of the end-effector from hand to tool. Different tools extend the body schema in different ways, with a displaced visual target and a novel, task-specific processing of haptic feedback to the hand. This distalization is critical in order to exploit the unique functional capacities engendered by complex tools. PMID:19347356
DOE Office of Scientific and Technical Information (OSTI.GOV)
Springmeyer, R R; Brugger, E; Cook, R
The Data group provides data analysis and visualization support to its customers. This consists primarily of the development and support of VisIt, a data analysis and visualization tool. Support ranges from answering questions about the tool, providing classes on how to use the tool, and performing data analysis and visualization for customers. The Information Management and Graphics Group supports and develops tools that enhance our ability to access, display, and understand large, complex data sets. Activities include applying visualization software for large scale data exploration; running video production labs on two networks; supporting graphics libraries and tools for end users;more » maintaining PowerWalls and assorted other displays; and developing software for searching and managing scientific data. Researchers in the Center for Applied Scientific Computing (CASC) work on various projects including the development of visualization techniques for large scale data exploration that are funded by the ASC program, among others. The researchers also have LDRD projects and collaborations with other lab researchers, academia, and industry. The IMG group is located in the Terascale Simulation Facility, home to Dawn, Atlas, BGL, and others, which includes both classified and unclassified visualization theaters, a visualization computer floor and deployment workshop, and video production labs. We continued to provide the traditional graphics group consulting and video production support. We maintained five PowerWalls and many other displays. We deployed a 576-node Opteron/IB cluster with 72 TB of memory providing a visualization production server on our classified network. We continue to support a 128-node Opteron/IB cluster providing a visualization production server for our unclassified systems and an older 256-node Opteron/IB cluster for the classified systems, as well as several smaller clusters to drive the PowerWalls. The visualization production systems includes NFS servers to provide dedicated storage for data analysis and visualization. The ASC projects have delivered new versions of visualization and scientific data management tools to end users and continue to refine them. VisIt had 4 releases during the past year, ending with VisIt 2.0. We released version 2.4 of Hopper, a Java application for managing and transferring files. This release included a graphical disk usage view which works on all types of connections and an aggregated copy feature for quickly transferring massive datasets quickly and efficiently to HPSS. We continue to use and develop Blockbuster and Telepath. Both the VisIt and IMG teams were engaged in a variety of movie production efforts during the past year in addition to the development tasks.« less
Gerth, Victor E; Vize, Peter D
2005-04-01
The Gene Expression Viewer is a web-launched three-dimensional visualization tool, tailored to compare surface reconstructions of multi-channel image volumes generated by confocal microscopy or micro-CT.
SocialMood: an information visualization tool to measure the mood of the people in social networks
NASA Astrophysics Data System (ADS)
Amorim, Guilherme; Franco, Roberto; Moraes, Rodolfo; Figueiredo, Bruno; Miranda, João.; Dobrões, José; Afonso, Ricardo; Meiguins, Bianchi
2013-12-01
Based on the arena of social networks, the tool developed in this study aims to identify trends mood among undergraduate students. Combining the methodology Self-Assessment Manikin (SAM), which originated in the field of Psychology, the system filters the content provided on the Web and isolates certain words, establishing a range of values as perceived positive, negative or neutral. A Big Data summarizing the results, assisting in the construction and visualization of behavioral profiles generic, so we have a guideline for the development of information visualization tools for social networks.
Three visualization approaches for communicating and exploring PIT tag data
Letcher, Benjamin; Walker, Jeffrey D.; O'Donnell, Matthew; Whiteley, Andrew R.; Nislow, Keith; Coombs, Jason
2018-01-01
As the number, size and complexity of ecological datasets has increased, narrative and interactive raw data visualizations have emerged as important tools for exploring and understanding these large datasets. As a demonstration, we developed three visualizations to communicate and explore passive integrated transponder tag data from two long-term field studies. We created three independent visualizations for the same dataset, allowing separate entry points for users with different goals and experience levels. The first visualization uses a narrative approach to introduce users to the study. The second visualization provides interactive cross-filters that allow users to explore multi-variate relationships in the dataset. The last visualization allows users to visualize the movement histories of individual fish within the stream network. This suite of visualization tools allows a progressive discovery of more detailed information and should make the data accessible to users with a wide variety of backgrounds and interests.
A WebGL Tool for Visualizing the Topology of the Sun's Coronal Magnetic Field
NASA Astrophysics Data System (ADS)
Duffy, A.; Cheung, C.; DeRosa, M. L.
2012-12-01
We present a web-based, topology-viewing tool that allows users to visualize the geometry and topology of the Sun's 3D coronal magnetic field in an interactive manner. The tool is implemented using, open-source, mature, modern web technologies including WebGL, jQuery, HTML 5, and CSS 3, which are compatible with nearly all modern web browsers. As opposed to the traditional method of visualization, which involves the downloading and setup of various software packages-proprietary and otherwise-the tool presents a clean interface that allows the user to easily load and manipulate the model, while also offering great power to choose which topological features are displayed. The tool accepts data encoded in the JSON open format that has libraries available for nearly every major programming language, making it simple to generate the data.
Liu, L B; Wu, C M; Wen, J; Chen, J L; Zheng, M Q; Zhao, G P
2009-03-01
Antibody titers raised for vaccinations against avian influenza (AI) and Newcastle disease (ND) were higher in Chinese Beijing-You (BJY) than in White Leghorn (WL) ( P < 0.001), but there was no breed difference in titers for sheep red blood cells (SRBC). Genotyping by PCR-SSCP identified seven haplotypes in WL and 17 in BJY. After sequencing PCR products (35 and 85, respectively), 43 (WL) and 47 (BJY) single nucleotide polymorphisms (SNPs) were found in the 264 bp of exon 2. In WL chickens, significant associations were found with antibody responses to AI (two SNPs), ND (six SNPs), and SRBC (one SNP), while in BJY there was association with responses to ND (two SNPs) and SRBC (two SNPs), but none with AI. These results indicate that the genomic region bearing exon 2 of the major histocompatibility complex B-F gene has significant effects on antibody responses to SRBC and vaccination against AI and ND. Different SNPs affected antibody titers for each of the antigens and they differed between these very distinct breeds.
Evaluating information content of SNPs for sample-tagging in re-sequencing projects.
Hu, Hao; Liu, Xiang; Jin, Wenfei; Hilger Ropers, H; Wienker, Thomas F
2015-05-15
Sample-tagging is designed for identification of accidental sample mix-up, which is a major issue in re-sequencing studies. In this work, we develop a model to measure the information content of SNPs, so that we can optimize a panel of SNPs that approach the maximal information for discrimination. The analysis shows that as low as 60 optimized SNPs can differentiate the individuals in a population as large as the present world, and only 30 optimized SNPs are in practice sufficient in labeling up to 100 thousand individuals. In the simulated populations of 100 thousand individuals, the average Hamming distances, generated by the optimized set of 30 SNPs are larger than 18, and the duality frequency, is lower than 1 in 10 thousand. This strategy of sample discrimination is proved robust in large sample size and different datasets. The optimized sets of SNPs are designed for Whole Exome Sequencing, and a program is provided for SNP selection, allowing for customized SNP numbers and interested genes. The sample-tagging plan based on this framework will improve re-sequencing projects in terms of reliability and cost-effectiveness.
NASA Astrophysics Data System (ADS)
Chee, T.; Nguyen, L.; Smith, W. L., Jr.; Spangenberg, D.; Palikonda, R.; Bedka, K. M.; Minnis, P.; Thieman, M. M.; Nordeen, M.
2017-12-01
Providing public access to research products including cloud macro and microphysical properties and satellite imagery are a key concern for the NASA Langley Research Center Cloud and Radiation Group. This work describes a web based visualization tool and API that allows end users to easily create customized cloud product and satellite imagery, ground site data and satellite ground track information that is generated dynamically. The tool has two uses, one to visualize the dynamically created imagery and the other to provide access to the dynamically generated imagery directly at a later time. Internally, we leverage our practical experience with large, scalable application practices to develop a system that has the largest potential for scalability as well as the ability to be deployed on the cloud to accommodate scalability issues. We build upon NASA Langley Cloud and Radiation Group's experience with making real-time and historical satellite cloud product information, satellite imagery, ground site data and satellite track information accessible and easily searchable. This tool is the culmination of our prior experience with dynamic imagery generation and provides a way to build a "mash-up" of dynamically generated imagery and related kinds of information that are visualized together to add value to disparate but related information. In support of NASA strategic goals, our group aims to make as much scientific knowledge, observations and products available to the citizen science, research and interested communities as well as for automated systems to acquire the same information for data mining or other analytic purposes. This tool and the underlying API's provide a valuable research tool to a wide audience both as a standalone research tool and also as an easily accessed data source that can easily be mined or used with existing tools.
Maddinedi, Sireesh Babu; Mandal, Badal Kumar; Anna, Kiran Kumar
2017-04-01
A simple, green approach for the size controllable preparation of silver nanoparticles (SNPs) using tyrosine as reducing and capping agent is shown here. The size of SNPs is controlled by varying the pH of tyrosine solution. The as synthesized SNPs are characterized by using XRD, UV-Visible, DLS, TEM and SAED. Zeta potential measurements revealed the stability of tyrosine capped silver nanocolloids. Furthermore, catalytic activity studies concluded that the smaller SNPs acts as good catalyst and the catalytic activity depends on size of the nanoparticles. Further, the in-vitro cytotoxicity experiments concluded that the cytotoxicity of the prepared SNPs towards mouse fibroblast (3T3) cell lines is size and dose dependent. Additionally, the present approach is substitute to the traditional methods that are being used now-a-days for size controlled synthesis of SNPs. Copyright © 2017 Elsevier B.V. All rights reserved.
A training tool for visual aids. Using tracing techniques to create visual aids.
Clark, M; Walters, J E; Wileman, R
1982-01-01
This training tool explains the use of tracing techniques to create visuals requiring few materials and no training of special skills in drawing. Magazines, books, posters, and many other materials contain photographs and drawings which can be used to create visual aids for health training and public health education. The materials required are pencils, an eraser, crayons or colored marking pens, paper clips, tracing and drawing paper, carbon paper, and sources of visual images. The procedure is described. The material was prepared by INTRAH staff members. Other materials include how to evaluate teaching, how to create a family health case study and training in group dynamics.
DspaceOgre 3D Graphics Visualization Tool
NASA Technical Reports Server (NTRS)
Jain, Abhinandan; Myin, Steven; Pomerantz, Marc I.
2011-01-01
This general-purpose 3D graphics visualization C++ tool is designed for visualization of simulation and analysis data for articulated mechanisms. Examples of such systems are vehicles, robotic arms, biomechanics models, and biomolecular structures. DspaceOgre builds upon the open-source Ogre3D graphics visualization library. It provides additional classes to support the management of complex scenes involving multiple viewpoints and different scene groups, and can be used as a remote graphics server. This software provides improved support for adding programs at the graphics processing unit (GPU) level for improved performance. It also improves upon the messaging interface it exposes for use as a visualization server.
deepTools2: a next generation web server for deep-sequencing data analysis.
Ramírez, Fidel; Ryan, Devon P; Grüning, Björn; Bhardwaj, Vivek; Kilpert, Fabian; Richter, Andreas S; Heyne, Steffen; Dündar, Friederike; Manke, Thomas
2016-07-08
We present an update to our Galaxy-based web server for processing and visualizing deeply sequenced data. Its core tool set, deepTools, allows users to perform complete bioinformatic workflows ranging from quality controls and normalizations of aligned reads to integrative analyses, including clustering and visualization approaches. Since we first described our deepTools Galaxy server in 2014, we have implemented new solutions for many requests from the community and our users. Here, we introduce significant enhancements and new tools to further improve data visualization and interpretation. deepTools continue to be open to all users and freely available as a web service at deeptools.ie-freiburg.mpg.de The new deepTools2 suite can be easily deployed within any Galaxy framework via the toolshed repository, and we also provide source code for command line usage under Linux and Mac OS X. A public and documented API for access to deepTools functionality is also available. © The Author(s) 2016. Published by Oxford University Press on behalf of Nucleic Acids Research.
Perceptual issues in scientific visualization
NASA Technical Reports Server (NTRS)
Kaiser, Mary K.; Proffitt, Dennis R.
1989-01-01
In order to develop effective tools for scientific visulaization, consideration must be given to the perceptual competencies, limitations, and biases of the human operator. Perceptual psychology has amassed a rich body of research on these issues and can lend insight to the development of visualization tehcniques. Within a perceptual psychological framework, the computer display screen can best be thought of as a special kind of impoverished visual environemnt. Guidelines can be gleaned from the psychological literature to help visualization tool designers avoid ambiguities and/or illusions in the resulting data displays.
Visualization and Analytics Software Tools for Peregrine System |
R is a language and environment for statistical computing and graphics. Go to the R web site for System Visualization and Analytics Software Tools for Peregrine System Learn about the available visualization for OpenGL-based applications. For more information, please go to the FastX page. ParaView An open
Toward a Scalable Visualization System for Network Traffic Monitoring
NASA Astrophysics Data System (ADS)
Malécot, Erwan Le; Kohara, Masayoshi; Hori, Yoshiaki; Sakurai, Kouichi
With the multiplication of attacks against computer networks, system administrators are required to monitor carefully the traffic exchanged by the networks they manage. However, that monitoring task is increasingly laborious because of the augmentation of the amount of data to analyze. And that trend is going to intensify with the explosion of the number of devices connected to computer networks along with the global rise of the available network bandwidth. So system administrators now heavily rely on automated tools to assist them and simplify the analysis of the data. Yet, these tools provide limited support and, most of the time, require highly skilled operators. Recently, some research teams have started to study the application of visualization techniques to the analysis of network traffic data. We believe that this original approach can also allow system administrators to deal with the large amount of data they have to process. In this paper, we introduce a tool for network traffic monitoring using visualization techniques that we developed in order to assist the system administrators of our corporate network. We explain how we designed the tool and some of the choices we made regarding the visualization techniques to use. The resulting tool proposes two linked representations of the network traffic and activity, one in 2D and the other in 3D. As 2D and 3D visualization techniques have different assets, we resulted in combining them in our tool to take advantage of their complementarity. We finally tested our tool in order to evaluate the accuracy of our approach.
OmicsNet: a web-based tool for creation and visual analysis of biological networks in 3D space.
Zhou, Guangyan; Xia, Jianguo
2018-06-07
Biological networks play increasingly important roles in omics data integration and systems biology. Over the past decade, many excellent tools have been developed to support creation, analysis and visualization of biological networks. However, important limitations remain: most tools are standalone programs, the majority of them focus on protein-protein interaction (PPI) or metabolic networks, and visualizations often suffer from 'hairball' effects when networks become large. To help address these limitations, we developed OmicsNet - a novel web-based tool that allows users to easily create different types of molecular interaction networks and visually explore them in a three-dimensional (3D) space. Users can upload one or multiple lists of molecules of interest (genes/proteins, microRNAs, transcription factors or metabolites) to create and merge different types of biological networks. The 3D network visualization system was implemented using the powerful Web Graphics Library (WebGL) technology that works natively in most major browsers. OmicsNet supports force-directed layout, multi-layered perspective layout, as well as spherical layout to help visualize and navigate complex networks. A rich set of functions have been implemented to allow users to perform coloring, shading, topology analysis, and enrichment analysis. OmicsNet is freely available at http://www.omicsnet.ca.
NASA Astrophysics Data System (ADS)
Wood, Brian M.; Wood, Zoë J.
2006-01-01
We present a visualization and computation tool for modeling the caloric cost of pedestrian travel across three dimensional terrains. This tool is being used in ongoing archaeological research that analyzes how costs of locomotion affect the spatial distribution of trails and artifacts across archaeological landscapes. Throughout human history, traveling by foot has been the most common form of transportation, and therefore analyses of pedestrian travel costs are important for understanding prehistoric patterns of resource acquisition, migration, trade, and political interaction. Traditionally, archaeologists have measured geographic proximity based on "as the crow flies" distance. We propose new methods for terrain visualization and analysis based on measuring paths of least caloric expense, calculated using well established metabolic equations. Our approach provides a human centered metric of geographic closeness, and overcomes significant limitations of available Geographic Information System (GIS) software. We demonstrate such path computations and visualizations applied to archaeological research questions. Our system includes tools to visualize: energetic cost surfaces, comparisons of the elevation profiles of shortest paths versus least cost paths, and the display of paths of least caloric effort on Digital Elevation Models (DEMs). These analysis tools can be applied to calculate and visualize 1) likely locations of prehistoric trails and 2) expected ratios of raw material types to be recovered at archaeological sites.
Sequences associated with human iris pigmentation.
Frudakis, Tony; Thomas, Matthew; Gaskin, Zach; Venkateswarlu, K; Chandra, K Suresh; Ginjupalli, Siva; Gunturi, Sitaram; Natrajan, Sivamani; Ponnuswamy, Viswanathan K; Ponnuswamy, K N
2003-01-01
To determine whether and how common polymorphisms are associated with natural distributions of iris colors, we surveyed 851 individuals of mainly European descent at 335 SNP loci in 13 pigmentation genes and 419 other SNPs distributed throughout the genome and known or thought to be informative for certain elements of population structure. We identified numerous SNPs, haplotypes, and diplotypes (diploid pairs of haplotypes) within the OCA2, MYO5A, TYRP1, AIM, DCT, and TYR genes and the CYP1A2-15q22-ter, CYP1B1-2p21, CYP2C8-10q23, CYP2C9-10q24, and MAOA-Xp11.4 regions as significantly associated with iris colors. Half of the associated SNPs were located on chromosome 15, which corresponds with results that others have previously obtained from linkage analysis. We identified 5 additional genes (ASIP, MC1R, POMC, and SILV) and one additional region (GSTT2-22q11.23) with haplotype and/or diplotypes, but not individual SNP alleles associated with iris colors. For most of the genes, multilocus gene-wise genotype sequences were more strongly associated with iris colors than were haplotypes or SNP alleles. Diplotypes for these genes explain 15% of iris color variation. Apart from representing the first comprehensive candidate gene study for variable iris pigmentation and constituting a first step toward developing a classification model for the inference of iris color from DNA, our results suggest that cryptic population structure might serve as a leverage tool for complex trait gene mapping if genomes are screened with the appropriate ancestry informative markers. PMID:14704187
Pedigree reconstruction from SNP data: parentage assignment, sibship clustering and beyond.
Huisman, Jisca
2017-09-01
Data on hundreds or thousands of single nucleotide polymorphisms (SNPs) provide detailed information about the relationships between individuals, but currently few tools can turn this information into a multigenerational pedigree. I present the r package sequoia, which assigns parents, clusters half-siblings sharing an unsampled parent and assigns grandparents to half-sibships. Assignments are made after consideration of the likelihoods of all possible first-, second- and third-degree relationships between the focal individuals, as well as the traditional alternative of being unrelated. This careful exploration of the local likelihood surface is implemented in a fast, heuristic hill-climbing algorithm. Distinction between the various categories of second-degree relatives is possible when likelihoods are calculated conditional on at least one parent of each focal individual. Performance was tested on simulated data sets with realistic genotyping error rate and missingness, based on three different large pedigrees (N = 1000-2000). This included a complex pedigree with overlapping generations, occasional close inbreeding and some unknown birth years. Parentage assignment was highly accurate down to about 100 independent SNPs (error rate <0.1%) and fast (<1 min) as most pairs can be excluded from being parent-offspring based on opposite homozygosity. For full pedigree reconstruction, 40% of parents were assumed nongenotyped. Reconstruction resulted in low error rates (<0.3%), high assignment rates (>99%) in limited computation time (typically <1 h) when at least 200 independent SNPs were used. In three empirical data sets, relatedness estimated from the inferred pedigree was strongly correlated to genomic relatedness. © 2017 The Authors. Molecular Ecology Resources Published by John Wiley & Sons Ltd.
Transcriptomic investigation of meat tenderness in two Italian cattle breeds.
Bongiorni, S; Gruber, C E M; Bueno, S; Chillemi, G; Ferrè, F; Failla, S; Moioli, B; Valentini, A
2016-06-01
Our objectives for this study were to understand the biological basis of meat tenderness and to provide an overview of the gene expression profiles related to meat quality as a tool for selection. Through deep mRNA sequencing, we analyzed gene expression in muscle tissues of two Italian cattle breeds: Maremmana and Chianina. We uncovered several differentially expressed genes that encode for proteins belonging to a family of tripartite motif proteins, which are involved in growth, cell differentiation and apoptosis, such as TRIM45, or play an essential role in regulating skeletal muscle differentiation and the regeneration of adult skeletal muscle, such as TRIM32. Other differentially expressed genes (SCN2B, SLC9A7 and KCNK3) emphasize the involvement of potassium-sodium pumps in tender meat. By mapping splice junctions in RNA-Seq reads, we found significant differences in gene isoform expression levels. The PRKAG3 gene, which is involved in the regulation of energy metabolism, showed four isoforms that were differentially expressed. This distinct pattern of PRKAG3 gene expression could indicate impaired glycogen storage in skeletal muscle, and consequently, this gene very likely has a role in the tenderization process. Furthermore, with this deep RNA-sequencing, we captured a high number of expressed SNPs, for example, we found 1462 homozygous SNPs showing the alternative allele with a 100% frequency when comparing tender and tough meat. SNPs were then classified into categories by their position and also by their effect on gene coding (174 non-synonymous polymorphisms) based on the available UMD_3.1 annotations. © 2016 Stichting International Foundation for Animal Genetics.
The Role of Local Ancestry Adjustment in Association Studies Using Admixed Populations
Zhang, Jianqi; Stram, Daniel O.
2016-01-01
Association analysis using admixed populations imposes challenges and opportunities for disease mapping. By developing some explicit results for the variance of an allele of interest conditional on either local or global ancestry and by simulation of recently admixed genomes we evaluate power and false-positive rates under a variety of scenarios concerning linkage disequilibrium (LD) and the presence of unmeasured variants. Pairwise LD patterns were compared between admixed and nonadmixed populations using the HapMap phase 3 data. Based on the above, we showed that as follows: For causal variants with similar effect size in all populations, power is generally higher in a study using admixed population than using nonadmixed population, especially for highly differentiated SNPs. This gain of power is achieved with adjustment of global ancestry, which completely removes any cross-chromosome inflation of type I error rates, and addresses much of the intrachromosome inflation.If reliably estimated, adjusting for local ancestry precisely recovers the localization that could have been achieved in a stratified analysis of source populations. Improved localization is most evident for highly differentiated SNPs; however, the advantage of higher power is lost on exactly the same differentiated SNPs.In the real admixed populations such as African Americans and Latinos, the expansion of LD is not as dramatic as in our simulation.While adjustment for global ancestry is required prior to announcing a novel association seen in an admixed population, local ancestry adjustment may best be regarded as a localization tool not strictly required for discovery purposes. PMID:25043967
Mantello, Camila Campos; Cardoso-Silva, Claudio Benicio; da Silva, Carla Cristina; de Souza, Livia Moura; Scaloppi Junior, Erivaldo José; de Souza Gonçalves, Paulo; Vicentini, Renato; de Souza, Anete Pereira
2014-01-01
Hevea brasiliensis (Willd. Ex Adr. Juss.) Muell.-Arg. is the primary source of natural rubber that is native to the Amazon rainforest. The singular properties of natural rubber make it superior to and competitive with synthetic rubber for use in several applications. Here, we performed RNA sequencing (RNA-seq) of H. brasiliensis bark on the Illumina GAIIx platform, which generated 179,326,804 raw reads on the Illumina GAIIx platform. A total of 50,384 contigs that were over 400 bp in size were obtained and subjected to further analyses. A similarity search against the non-redundant (nr) protein database returned 32,018 (63%) positive BLASTx hits. The transcriptome analysis was annotated using the clusters of orthologous groups (COG), gene ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG), and Pfam databases. A search for putative molecular marker was performed to identify simple sequence repeats (SSRs) and single nucleotide polymorphisms (SNPs). In total, 17,927 SSRs and 404,114 SNPs were detected. Finally, we selected sequences that were identified as belonging to the mevalonate (MVA) and 2-C-methyl-D-erythritol 4-phosphate (MEP) pathways, which are involved in rubber biosynthesis, to validate the SNP markers. A total of 78 SNPs were validated in 36 genotypes of H. brasiliensis. This new dataset represents a powerful information source for rubber tree bark genes and will be an important tool for the development of microsatellites and SNP markers for use in future genetic analyses such as genetic linkage mapping, quantitative trait loci identification, investigations of linkage disequilibrium and marker-assisted selection.
Jordan, Rebecca; Hoffmann, Ary A; Dillon, Shannon K; Prober, Suzanne M
2017-11-01
Understanding whether populations can adapt in situ or whether interventions are required is of key importance for biodiversity management under climate change. Landscape genomics is becoming an increasingly important and powerful tool for rapid assessments of climate adaptation, especially in long-lived species such as trees. We investigated climate adaptation in Eucalyptus microcarpa using the DArTseq genomic approach. A combination of F ST outlier and environmental association analyses were performed using >4200 genomewide single nucleotide polymorphisms (SNPs) from 26 populations spanning climate gradients in southeastern Australia. Eighty-one SNPs were identified as putatively adaptive, based on significance in F ST outlier tests and significant associations with one or more climate variables related to temperature (70/81), aridity (37/81) or precipitation (35/81). Adaptive SNPs were located on all 11 chromosomes, with no particular region associated with individual climate variables. Climate adaptation appeared to be characterized by subtle shifts in allele frequencies, with no consistent fixed differences identified. Based on these associations, we predict adaptation under projected changes in climate will include a suite of shifts in allele frequencies. Whether this can occur sufficiently rapidly through natural selection within populations, or would benefit from assisted gene migration, requires further evaluation. In some populations, the absence or predicted increases to near fixation of particular adaptive alleles hint at potential limits to adaptive capacity. Together, these results reinforce the importance of standing genetic variation at the geographic level for maintaining species' evolutionary potential. © 2017 John Wiley & Sons Ltd.
New genetic variants of LATS1 detected in urinary bladder and colon cancer.
Saadeldin, Mona K; Shawer, Heba; Mostafa, Ahmed; Kassem, Neemat M; Amleh, Asma; Siam, Rania
2014-01-01
LATS1, the large tumor suppressor 1 gene, encodes for a serine/threonine kinase protein and is implicated in cell cycle progression. LATS1 is down-regulated in various human cancers, such as breast cancer, and astrocytoma. Point mutations in LATS1 were reported in human sarcomas. Additionally, loss of heterozygosity of LATS1 chromosomal region predisposes to breast, ovarian, and cervical tumors. In the current study, we investigated LATS1 genetic variations including single nucleotide polymorphisms (SNPs), in 28 Egyptian patients with either urinary bladder or colon cancers. The LATS1 gene was amplified and sequenced and the expression of LATS1 at the RNA level was assessed in 12 urinary bladder cancer samples. We report, the identification of a total of 29 variants including previously identified SNPs within LATS1 coding and non-coding sequences. A total of 18 variants were novel. Majority of the novel variants, 13, were mapped to intronic sequences and un-translated regions of the gene. Four of the five novel variants located in the coding region of the gene, represented missense mutations within the serine/threonine kinase catalytic domain. Interestingly, LATS1 RNA steady state levels was lost in urinary bladder cancerous tissue harboring four specific SNPs (16045 + 41736 + 34614 + 56177) positioned in the 5'UTR, intron 6, and two silent mutations within exon 4 and exon 8, respectively. This study identifies novel single-base-sequence alterations in the LATS1 gene. These newly identified variants could potentially be used as novel diagnostic or prognostic tools in cancer.
Tsai, Hsin Y; Robledo, Diego; Lowe, Natalie R; Bekaert, Michael; Taggart, John B; Bron, James E; Houston, Ross D
2016-07-07
High density linkage maps are useful tools for fine-scale mapping of quantitative trait loci, and characterization of the recombination landscape of a species' genome. Genomic resources for Atlantic salmon (Salmo salar) include a well-assembled reference genome, and high density single nucleotide polymorphism (SNP) arrays. Our aim was to create a high density linkage map, and to align it with the reference genome assembly. Over 96,000 SNPs were mapped and ordered on the 29 salmon linkage groups using a pedigreed population comprising 622 fish from 60 nuclear families, all genotyped with the 'ssalar01' high density SNP array. The number of SNPs per group showed a high positive correlation with physical chromosome length (r = 0.95). While the order of markers on the genetic and physical maps was generally consistent, areas of discrepancy were identified. Approximately 6.5% of the previously unmapped reference genome sequence was assigned to chromosomes using the linkage map. Male recombination rate was lower than females across the vast majority of the genome, but with a notable peak in subtelomeric regions. Finally, using RNA-Seq data to annotate the reference genome, the mapped SNPs were categorized according to their predicted function, including annotation of ∼2500 putative nonsynonymous variants. The highest density SNP linkage map for any salmonid species has been created, annotated, and integrated with the Atlantic salmon reference genome assembly. This map highlights the marked heterochiasmy of salmon, and provides a useful resource for salmonid genetics and genomics research. Copyright © 2016 Tsai et al.
Gu, Wanjun; Gurguis, Christopher I.; Zhou, Jin J.; Zhu, Yihua; Ko, Eun-A.; Ko, Jae-Hong; Wang, Ting; Zhou, Tong
2015-01-01
Genetic variation arising from single nucleotide polymorphisms (SNPs) is ubiquitously found among human populations. While disease-causing variants are known in some cases, identifying functional or causative variants for most human diseases remains a challenging task. Rare SNPs, rather than common ones, are thought to be more important in the pathology of most human diseases. We propose that rare SNPs should be divided into two categories dependent on whether the minor alleles are derived or ancestral. Derived alleles are less likely to have been purified by evolutionary processes and may be more likely to induce deleterious effects. We therefore hypothesized that the rare SNPs with derived minor alleles would be more important for human diseases and predicted that these variants would have larger functional or structural consequences relative to the rare variants for which the minor alleles are ancestral. We systematically investigated the consequences of the exonic SNPs on protein function, mRNA structure, and translation. We found that the functional and structural consequences are more significant for the rare exonic variants for which the minor alleles are derived. However, this pattern is reversed when the minor alleles are ancestral. Thus, the rare exonic SNPs with derived minor alleles are more likely to be deleterious. Age estimation of rare SNPs confirms that these potentially deleterious SNPs are recently evolved in the human population. These results have important implications for understanding the function of genetic variations in human exonic regions and for prioritizing functional SNPs in genome-wide association studies of human diseases. PMID:26454016
Singh, Vikas K; Khan, Aamir W; Saxena, Rachit K; Kumar, Vinay; Kale, Sandip M; Sinha, Pallavi; Chitikineni, Annapurna; Pazhamala, Lekha T; Garg, Vanika; Sharma, Mamta; Sameer Kumar, Chanda Venkata; Parupalli, Swathi; Vechalapu, Suryanarayana; Patil, Suyash; Muniswamy, Sonnappa; Ghanta, Anuradha; Yamini, Kalinati Narasimhan; Dharmaraj, Pallavi Subbanna; Varshney, Rajeev K
2016-05-01
To map resistance genes for Fusarium wilt (FW) and sterility mosaic disease (SMD) in pigeonpea, sequencing-based bulked segregant analysis (Seq-BSA) was used. Resistant (R) and susceptible (S) bulks from the extreme recombinant inbred lines of ICPL 20096 × ICPL 332 were sequenced. Subsequently, SNP index was calculated between R- and S-bulks with the help of draft genome sequence and reference-guided assembly of ICPL 20096 (resistant parent). Seq-BSA has provided seven candidate SNPs for FW and SMD resistance in pigeonpea. In parallel, four additional genotypes were re-sequenced and their combined analysis with R- and S-bulks has provided a total of 8362 nonsynonymous (ns) SNPs. Of 8362 nsSNPs, 60 were found within the 2-Mb flanking regions of seven candidate SNPs identified through Seq-BSA. Haplotype analysis narrowed down to eight nsSNPs in seven genes. These eight nsSNPs were further validated by re-sequencing 11 genotypes that are resistant and susceptible to FW and SMD. This analysis revealed association of four candidate nsSNPs in four genes with FW resistance and four candidate nsSNPs in three genes with SMD resistance. Further, In silico protein analysis and expression profiling identified two most promising candidate genes namely C.cajan_01839 for SMD resistance and C.cajan_03203 for FW resistance. Identified candidate genomic regions/SNPs will be useful for genomics-assisted breeding in pigeonpea. © 2015 The Authors. Plant Biotechnology Journal published by Society for Experimental Biology and The Association of Applied Biologists and John Wiley & Sons Ltd.
Genome-wide association study of coronary and aortic calcification in lung cancer screening CT
NASA Astrophysics Data System (ADS)
de Vos, Bob D.; van Setten, Jessica; de Jong, Pim A.; Mali, Willem P.; Oudkerk, Matthijs; Viergever, Max A.; Išgum, Ivana
2016-03-01
Arterial calcification has been related to cardiovascular disease (CVD) and osteoporosis. However, little is known about the role of genetics and exact pathways leading to arterial calcification and its relation to bone density changes indicating osteoporosis. In this study, we conducted a genome-wide association study of arterial calcification burden, followed by a look-up of known single nucleotide polymorphisms (SNPs) for coronary artery disease (CAD) and myocardial infarction (MI), and bone mineral density (BMD) to test for a shared genetic basis between the traits. The study included a subcohort of the Dutch-Belgian lung cancer screening trial comprised of 2,561 participants. Participants underwent baseline CT screening in one of two hospitals participating in the trial. Low-dose chest CT images were acquired without contrast enhancement and without ECG-synchronization. In these images coronary and aortic calcifications were identified automatically. Subsequently, the detected calcifications were quantified using coronary artery calcium Agatston and volume scores. Genotype data was available for these participants. A genome-wide association study was conducted on 10,220,814 SNPs using a linear regression model. To reduce multiple testing burden, known CAD/MI and BMD SNPs were specifically tested (45 SNPs from the CARDIoGRAMplusC4D consortium and 60 SNPS from the GEFOS consortium). No novel significant SNPs were found. Significant enrichment for CAD/MI SNPs was observed in testing Agatston and coronary artery calcium volume scores. Moreover, a significant enrichment of BMD SNPs was shown in aortic calcium volume scores. This may indicate genetic relation of BMD SNPs and arterial calcification burden.
Visualizing vascular structures in virtual environments
NASA Astrophysics Data System (ADS)
Wischgoll, Thomas
2013-01-01
In order to learn more about the cause of coronary heart diseases and develop diagnostic tools, the extraction and visualization of vascular structures from volumetric scans for further analysis is an important step. By determining a geometric representation of the vasculature, the geometry can be inspected and additional quantitative data calculated and incorporated into the visualization of the vasculature. To provide a more user-friendly visualization tool, virtual environment paradigms can be utilized. This paper describes techniques for interactive rendering of large-scale vascular structures within virtual environments. This can be applied to almost any virtual environment configuration, such as CAVE-type displays. Specifically, the tools presented in this paper were tested on a Barco I-Space and a large 62x108 inch passive projection screen with a Kinect sensor for user tracking.
2011-01-01
Background Single nucleotide polymorphisms (SNPs) are the most abundant source of genetic variation among individuals of a species. New genotyping technologies allow examining hundreds to thousands of SNPs in a single reaction for a wide range of applications such as genetic diversity analysis, linkage mapping, fine QTL mapping, association studies, marker-assisted or genome-wide selection. In this paper, we evaluated the potential of highly-multiplexed SNP genotyping for genetic mapping in maritime pine (Pinus pinaster Ait.), the main conifer used for commercial plantation in southwestern Europe. Results We designed a custom GoldenGate assay for 1,536 SNPs detected through the resequencing of gene fragments (707 in vitro SNPs/Indels) and from Sanger-derived Expressed Sequenced Tags assembled into a unigene set (829 in silico SNPs/Indels). Offspring from three-generation outbred (G2) and inbred (F2) pedigrees were genotyped. The success rate of the assay was 63.6% and 74.8% for in silico and in vitro SNPs, respectively. A genotyping error rate of 0.4% was further estimated from segregating data of SNPs belonging to the same gene. Overall, 394 SNPs were available for mapping. A total of 287 SNPs were integrated with previously mapped markers in the G2 parental maps, while 179 SNPs were localized on the map generated from the analysis of the F2 progeny. Based on 98 markers segregating in both pedigrees, we were able to generate a consensus map comprising 357 SNPs from 292 different loci. Finally, the analysis of sequence homology between mapped markers and their orthologs in a Pinus taeda linkage map, made it possible to align the 12 linkage groups of both species. Conclusions Our results show that the GoldenGate assay can be used successfully for high-throughput SNP genotyping in maritime pine, a conifer species that has a genome seven times the size of the human genome. This SNP-array will be extended thanks to recent sequencing effort using new generation sequencing technologies and will include SNPs from comparative orthologous sequences that were identified in the present study, providing a wider collection of anchor points for comparative genomics among the conifers. PMID:21767361
Visualization of the NASA ICON mission in 3d
NASA Astrophysics Data System (ADS)
Mendez, R. A., Jr.; Immel, T. J.; Miller, N.
2016-12-01
The ICON Explorer mission (http://icon.ssl.berkeley.edu) will provide several data products for the atmosphere and ionosphere after its launch in 2017. This project will support the mission by investigating the capability of these tools for visualization of current and predicted observatory characteristics and data acquisition. Visualization of this mission can be accomplished using tools like Google Earth or CesiumJS, as well assistance from Java or Python. Ideally we will bring this visualization into the homes of people without the need of additional software. The path of launching a standalone website, building this environment, and a full toolkit will be discussed. Eventually, the initial work could lead to the addition of a downloadable visualization packages for mission demonstration or science visualization.
Chamala, Srikar; Beckstead, Wesley A; Rowe, Mark J; McClellan, David A
2007-01-01
We investigated whether the effect of evolutionary selection on three recent Single Nucleotide Polymorphisms (SNPs) in the mitochondrial sub-haplogroups of Pima Indians is consistent with their effects on metabolic efficiency. The mitochondrial SNPs impact metabolic rate and respiratory quotient, and may be adaptations to caloric restriction in a desert habitat. Using TreeSAAP software, we examined evolutionary selection in 107 mammalian species at these SNPs, characterising the biochemical shifts produced by the amino acid substitutions. Our results suggest that two SNPs were affected by selection during mammalian evolution in a manner consistent with their effects on metabolic efficiency in Pima Indians.
Kharrat, Najla; Abdelmouleh, Wafa; Abdelhedi, Rania; Alfadhli, Suad; Rebai, Ahmed
2012-01-01
DNA variations within the Angiotensin-Converting Enzyme (ACE) gene have been shown to be involved in the aetiology of several common diseases and the therapeutic response. This study reports a comparison of haplotype analysis of five SNPs in the ACE gene region using a sample of 100 healthy subjects derived from five different populations (Tunisian, Iranian, Kuwaiti, Bahraini and Indian). Strong linkage disequilibrium was found among all SNPs studied for all populations. Two SNPs (rs1800764 and rs4340) were identified as key SNPs for all populations. These SNPs will be valuable for future effective association studies of the ACE gene polymorphisms in Arab and Asian populations.
Green synthesis of silver nanoparticles: characterization and determination of antibacterial potency
NASA Astrophysics Data System (ADS)
Annamalai, Jayshree; Nallamuthu, Thangaraju
2016-02-01
Silver ions (Ag+) and its compounds are highly toxic to microorganisms, exhibiting strong biocidal effects on many species of bacteria but have a low toxicity toward animal cells. In the present study, silver nanoparticles (SNPs) were biosynthesized using aqueous extract of Chlorella vulgaris as reducing agent and size of SNPs synthesized ranged between 15 and 47 nm. SNPs were characterized by UV-visible spectroscopy, scanning electron microscopy, transmission electron microscopy, X-ray diffraction and Fourier infrared spectroscopy, and analyzed for its antibacterial property against human pathogens. This approach of SNPs synthesis involving green chemistry process can be considered for the large-scale production of SNPs and in the development of biomedicines.
Klaver, Peter; Latal, Beatrice; Martin, Ernst
2015-01-01
Very low birth weight (VLBW) premature born infants have a high risk to develop visual perceptual and learning deficits as well as widespread functional and structural brain abnormalities during infancy and childhood. Whether and how prematurity alters neural specialization within visual neural networks is still unknown. We used functional and structural brain imaging to examine the visual semantic system of VLBW born (<1250 g, gestational age 25-32 weeks) adolescents (13-15 years, n = 11, 3 males) and matched term born control participants (13-15 years, n = 11, 3 males). Neurocognitive assessment revealed no group differences except for lower scores on an adaptive visuomotor integration test. All adolescents were scanned while viewing pictures of animals and tools and scrambled versions of these pictures. Both groups demonstrated animal and tool category related neural networks. Term born adolescents showed tool category related neural activity, i.e. tool pictures elicited more activity than animal pictures, in temporal and parietal brain areas. Animal category related activity was found in the occipital, temporal and frontal cortex. VLBW born adolescents showed reduced tool category related activity in the dorsal visual stream compared with controls, specifically the left anterior intraparietal sulcus, and enhanced animal category related activity in the left middle occipital gyrus and right lingual gyrus. Lower birth weight of VLBW adolescents correlated with larger thickness of the pericalcarine gyrus in the occipital cortex and smaller surface area of the superior temporal gyrus in the lateral temporal cortex. Moreover, larger thickness of the pericalcarine gyrus and smaller surface area of the superior temporal gyrus correlated with reduced tool category related activity in the parietal cortex. Together, our data suggest that very low birth weight predicts alterations of higher order visual semantic networks, particularly in the dorsal stream. The differences in neural specialization may be associated with aberrant cortical development of areas in the visual system that develop early in childhood. Copyright © 2014 Elsevier Ltd. All rights reserved.
Exploiting Genome Structure in Association Analysis
Kim, Seyoung
2014-01-01
Abstract A genome-wide association study involves examining a large number of single-nucleotide polymorphisms (SNPs) to identify SNPs that are significantly associated with the given phenotype, while trying to reduce the false positive rate. Although haplotype-based association methods have been proposed to accommodate correlation information across nearby SNPs that are in linkage disequilibrium, none of these methods directly incorporated the structural information such as recombination events along chromosome. In this paper, we propose a new approach called stochastic block lasso for association mapping that exploits prior knowledge on linkage disequilibrium structure in the genome such as recombination rates and distances between adjacent SNPs in order to increase the power of detecting true associations while reducing false positives. Following a typical linear regression framework with the genotypes as inputs and the phenotype as output, our proposed method employs a sparsity-enforcing Laplacian prior for the regression coefficients, augmented by a first-order Markov process along the sequence of SNPs that incorporates the prior information on the linkage disequilibrium structure. The Markov-chain prior models the structural dependencies between a pair of adjacent SNPs, and allows us to look for association SNPs in a coupled manner, combining strength from multiple nearby SNPs. Our results on HapMap-simulated datasets and mouse datasets show that there is a significant advantage in incorporating the prior knowledge on linkage disequilibrium structure for marker identification under whole-genome association. PMID:21548809
Langlois, Christine; Abadi, Arkan; Peralta-Romero, Jesus; Alyass, Akram; Suarez, Fernando; Gomez-Zamudio, Jaime; Burguete-Garcia, Ana I.; Yazdi, Fereshteh T.; Cruz, Miguel; Meyre, David
2016-01-01
Genome wide association studies (GWAS) have identified single-nucleotide polymorphisms (SNPs) that are associated with fasting plasma glucose (FPG) in adult European populations. The contribution of these SNPs to FPG in non-Europeans and children is unclear. We studied the association of 15 GWAS SNPs and a genotype score (GS) with FPG and 7 metabolic traits in 1,421 Mexican children and adolescents from Mexico City. Genotyping of the 15 SNPs was performed using TaqMan Open Array. We used multivariate linear regression models adjusted for age, sex, body mass index standard deviation score, and recruitment center. We identified significant associations between 3 SNPs (G6PC2 (rs560887), GCKR (rs1260326), MTNR1B (rs10830963)), the GS and FPG level. The FPG risk alleles of 11 out of the 15 SNPs (73.3%) displayed significant or non-significant beta values for FPG directionally consistent with those reported in adult European GWAS. The risk allele frequencies for 11 of 15 (73.3%) SNPs differed significantly in Mexican children and adolescents compared to European adults from the 1000G Project, but no significant enrichment in FPG risk alleles was observed in the Mexican population. Our data support a partial transferability of European GWAS FPG association signals in children and adolescents from the admixed Mexican population. PMID:27782183
Munretnam, Khamsigan; Alex, Livy; Ramzi, Nurul Hanis; Chahil, Jagdish Kaur; Kavitha, I S; Hashim, Nikman Adli Nor; Lye, Say Hean; Velapasamy, Sharmila; Ler, Lian Wee
2014-01-01
There is growing global interest to stratify men into different levels of risk to developing prostate cancer, thus it is important to identify common genetic variants that confer the risk. Although many studies have identified more than a dozen common genetic variants which are highly associated with prostate cancer, none have been done in Malaysian population. To determine the association of such variants in Malaysian men with prostate cancer, we evaluated a panel of 768 SNPs found previously associated with various cancers which also included the prostate specific SNPs in a population based case control study (51 case subjects with prostate cancer and 51 control subjects) in Malaysian men of Malay, Chinese and Indian ethnicity. We identified 21 SNPs significantly associated with prostate cancer. Among these, 12 SNPs were strongly associated with increased risk of prostate cancer while remaining nine SNPs were associated with reduced risk. However, data analysis based on ethnic stratification led to only five SNPs in Malays and 3 SNPs in Chinese which remained significant. This could be due to small sample size in each ethnic group. Significant non-genetic risk factors were also identified for their association with prostate cancer. Our study is the first to investigate the involvement of multiple variants towards susceptibility for PC in Malaysian men using genotyping approach. Identified SNPs and non-genetic risk factors have a significant association with prostate cancer.