Escher: A Web Application for Building, Sharing, and Embedding Data-Rich Visualizations of Biological Pathways

DOE PAGES

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

Sockeye: A 3D Environment for Comparative Genomics

PubMed Central

Montgomery, Stephen B.; Astakhova, Tamara; Bilenky, Mikhail; Birney, Ewan; Fu, Tony; Hassel, Maik; Melsopp, Craig; Rak, Marcin; Robertson, A. Gordon; Sleumer, Monica; Siddiqui, Asim S.; Jones, Steven J.M.

2004-01-01

Comparative genomics techniques are used in bioinformatics analyses to identify the structural and functional properties of DNA sequences. As the amount of available sequence data steadily increases, the ability to perform large-scale comparative analyses has become increasingly relevant. In addition, the growing complexity of genomic feature annotation means that new approaches to genomic visualization need to be explored. We have developed a Java-based application called Sockeye that uses three-dimensional (3D) graphics technology to facilitate the visualization of annotation and conservation across multiple sequences. This software uses the Ensembl database project to import sequence and annotation information from several eukaryotic species. A user can additionally import their own custom sequence and annotation data. Individual annotation objects are displayed in Sockeye by using custom 3D models. Ensembl-derived and imported sequences can be analyzed by using a suite of multiple and pair-wise alignment algorithms. The results of these comparative analyses are also displayed in the 3D environment of Sockeye. By using the Java3D API to visualize genomic data in a 3D environment, we are able to compactly display cross-sequence comparisons. This provides the user with a novel platform for visualizing and comparing genomic feature organization. PMID:15123592

JBrowse: A dynamic web platform for genome visualization and analysis

DOE PAGES

Buels, Robert; Yao, Eric; Diesh, Colin M.; ...

2016-04-12

Background: JBrowse is a fast and full-featured genome browser built with JavaScript and HTML5. It is easily embedded into websites or apps but can also be served as a standalone web page. Results: Overall improvements to speed and scalability are accompanied by specific enhancements that support complex interactive queries on large track sets. Analysis functions can readily be added using the plugin framework; most visual aspects of tracks can also be customized, along with clicks, mouseovers, menus, and popup boxes. JBrowse can also be used to browse local annotation files offline and to generate high-resolution figures for publication. Conclusions: JBrowsemore » is a mature web application suitable for genome visualization and analysis.« less

Next generation tools for genomic data generation, distribution, and visualization

PubMed Central

2010-01-01

Background With the rapidly falling cost and availability of high throughput sequencing and microarray technologies, the bottleneck for effectively using genomic analysis in the laboratory and clinic is shifting to one of effectively managing, analyzing, and sharing genomic data. Results Here we present three open-source, platform independent, software tools for generating, analyzing, distributing, and visualizing genomic data. These include a next generation sequencing/microarray LIMS and analysis project center (GNomEx); an application for annotating and programmatically distributing genomic data using the community vetted DAS/2 data exchange protocol (GenoPub); and a standalone Java Swing application (GWrap) that makes cutting edge command line analysis tools available to those who prefer graphical user interfaces. Both GNomEx and GenoPub use the rich client Flex/Flash web browser interface to interact with Java classes and a relational database on a remote server. Both employ a public-private user-group security model enabling controlled distribution of patient and unpublished data alongside public resources. As such, they function as genomic data repositories that can be accessed manually or programmatically through DAS/2-enabled client applications such as the Integrated Genome Browser. Conclusions These tools have gained wide use in our core facilities, research laboratories and clinics and are freely available for non-profit use. See http://sourceforge.net/projects/gnomex/, http://sourceforge.net/projects/genoviz/, and http://sourceforge.net/projects/useq. PMID:20828407

FISH Oracle: a web server for flexible visualization of DNA copy number data in a genomic context.

PubMed

Mader, Malte; Simon, Ronald; Steinbiss, Sascha; Kurtz, Stefan

2011-07-28

The rapidly growing amount of array CGH data requires improved visualization software supporting the process of identifying candidate cancer genes. Optimally, such software should work across multiple microarray platforms, should be able to cope with data from different sources and should be easy to operate. We have developed a web-based software FISH Oracle to visualize data from multiple array CGH experiments in a genomic context. Its fast visualization engine and advanced web and database technology supports highly interactive use. FISH Oracle comes with a convenient data import mechanism, powerful search options for genomic elements (e.g. gene names or karyobands), quick navigation and zooming into interesting regions, and mechanisms to export the visualization into different high quality formats. These features make the software especially suitable for the needs of life scientists. FISH Oracle offers a fast and easy to use visualization tool for array CGH and SNP array data. It allows for the identification of genomic regions representing minimal common changes based on data from one or more experiments. FISH Oracle will be instrumental to identify candidate onco and tumor suppressor genes based on the frequency and genomic position of DNA copy number changes. The FISH Oracle application and an installed demo web server are available at http://www.zbh.uni-hamburg.de/fishoracle.

FISH Oracle: a web server for flexible visualization of DNA copy number data in a genomic context

PubMed Central

2011-01-01

Background The rapidly growing amount of array CGH data requires improved visualization software supporting the process of identifying candidate cancer genes. Optimally, such software should work across multiple microarray platforms, should be able to cope with data from different sources and should be easy to operate. Results We have developed a web-based software FISH Oracle to visualize data from multiple array CGH experiments in a genomic context. Its fast visualization engine and advanced web and database technology supports highly interactive use. FISH Oracle comes with a convenient data import mechanism, powerful search options for genomic elements (e.g. gene names or karyobands), quick navigation and zooming into interesting regions, and mechanisms to export the visualization into different high quality formats. These features make the software especially suitable for the needs of life scientists. Conclusions FISH Oracle offers a fast and easy to use visualization tool for array CGH and SNP array data. It allows for the identification of genomic regions representing minimal common changes based on data from one or more experiments. FISH Oracle will be instrumental to identify candidate onco and tumor suppressor genes based on the frequency and genomic position of DNA copy number changes. The FISH Oracle application and an installed demo web server are available at http://www.zbh.uni-hamburg.de/fishoracle. PMID:21884636

An Ontology-Based GIS for Genomic Data Management of Rumen Microbes

PubMed Central

Jelokhani-Niaraki, Saber; Minuchehr, Zarrin; Nassiri, Mohammad Reza

2015-01-01

During recent years, there has been exponential growth in biological information. With the emergence of large datasets in biology, life scientists are encountering bottlenecks in handling the biological data. This study presents an integrated geographic information system (GIS)-ontology application for handling microbial genome data. The application uses a linear referencing technique as one of the GIS functionalities to represent genes as linear events on the genome layer, where users can define/change the attributes of genes in an event table and interactively see the gene events on a genome layer. Our application adopted ontology to portray and store genomic data in a semantic framework, which facilitates data-sharing among biology domains, applications, and experts. The application was developed in two steps. In the first step, the genome annotated data were prepared and stored in a MySQL database. The second step involved the connection of the database to both ArcGIS and Protégé as the GIS engine and ontology platform, respectively. We have designed this application specifically to manage the genome-annotated data of rumen microbial populations. Such a GIS-ontology application offers powerful capabilities for visualizing, managing, reusing, sharing, and querying genome-related data. PMID:25873847

An Ontology-Based GIS for Genomic Data Management of Rumen Microbes.

PubMed

Jelokhani-Niaraki, Saber; Tahmoorespur, Mojtaba; Minuchehr, Zarrin; Nassiri, Mohammad Reza

2015-03-01

During recent years, there has been exponential growth in biological information. With the emergence of large datasets in biology, life scientists are encountering bottlenecks in handling the biological data. This study presents an integrated geographic information system (GIS)-ontology application for handling microbial genome data. The application uses a linear referencing technique as one of the GIS functionalities to represent genes as linear events on the genome layer, where users can define/change the attributes of genes in an event table and interactively see the gene events on a genome layer. Our application adopted ontology to portray and store genomic data in a semantic framework, which facilitates data-sharing among biology domains, applications, and experts. The application was developed in two steps. In the first step, the genome annotated data were prepared and stored in a MySQL database. The second step involved the connection of the database to both ArcGIS and Protégé as the GIS engine and ontology platform, respectively. We have designed this application specifically to manage the genome-annotated data of rumen microbial populations. Such a GIS-ontology application offers powerful capabilities for visualizing, managing, reusing, sharing, and querying genome-related data.

Comparative visualization of genetic and physical maps with Strudel.

PubMed

Bayer, Micha; Milne, Iain; Stephen, Gordon; Shaw, Paul; Cardle, Linda; Wright, Frank; Marshall, David

2011-05-01

Data visualization can play a key role in comparative genomics, for example, underpinning the investigation of conserved synteny patterns. Strudel is a desktop application that allows users to easily compare both genetic and physical maps interactively and efficiently. It can handle large datasets from several genomes simultaneously, and allows all-by-all comparisons between these. Installers for Strudel are available for Windows, Linux, Solaris and Mac OS X at http://bioinf.scri.ac.uk/strudel/.

SPOCS: software for predicting and visualizing orthology/paralogy relationships among genomes.

PubMed

Curtis, Darren S; Phillips, Aaron R; Callister, Stephen J; Conlan, Sean; McCue, Lee Ann

2013-10-15

At the rate that prokaryotic genomes can now be generated, comparative genomics studies require a flexible method for quickly and accurately predicting orthologs among the rapidly changing set of genomes available. SPOCS implements a graph-based ortholog prediction method to generate a simple tab-delimited table of orthologs and in addition, html files that provide a visualization of the predicted ortholog/paralog relationships to which gene/protein expression metadata may be overlaid. A SPOCS web application is freely available at http://cbb.pnnl.gov/portal/tools/spocs.html. Source code for Linux systems is also freely available under an open source license at http://cbb.pnnl.gov/portal/software/spocs.html; the Boost C++ libraries and BLAST are required.

GFFview: A Web Server for Parsing and Visualizing Annotation Information of Eukaryotic Genome.

PubMed

Deng, Feilong; Chen, Shi-Yi; Wu, Zhou-Lin; Hu, Yongsong; Jia, Xianbo; Lai, Song-Jia

2017-10-01

Owing to wide application of RNA sequencing (RNA-seq) technology, more and more eukaryotic genomes have been extensively annotated, such as the gene structure, alternative splicing, and noncoding loci. Annotation information of genome is prevalently stored as plain text in General Feature Format (GFF), which could be hundreds or thousands Mb in size. Therefore, it is a challenge for manipulating GFF file for biologists who have no bioinformatic skill. In this study, we provide a web server (GFFview) for parsing the annotation information of eukaryotic genome and then generating statistical description of six indices for visualization. GFFview is very useful for investigating quality and difference of the de novo assembled transcriptome in RNA-seq studies.

Normalization of Complete Genome Characteristics: Application to Evolution from Primitive Organisms to Homo sapiens.

PubMed

Sorimachi, Kenji; Okayasu, Teiji; Ohhira, Shuji

2015-04-01

Normalized nucleotide and amino acid contents of complete genome sequences can be visualized as radar charts. The shapes of these charts depict the characteristics of an organism's genome. The normalized values calculated from the genome sequence theoretically exclude experimental errors. Further, because normalization is independent of both target size and kind, this procedure is applicable not only to single genes but also to whole genomes, which consist of a huge number of different genes. In this review, we discuss the applications of the normalization of the nucleotide and predicted amino acid contents of complete genomes to the investigation of genome structure and to evolutionary research from primitive organisms to Homo sapiens. Some of the results could never have been obtained from the analysis of individual nucleotide or amino acid sequences but were revealed only after the normalization of nucleotide and amino acid contents was applied to genome research. The discovery that genome structure was homogeneous was obtained only after normalization methods were applied to the nucleotide or predicted amino acid contents of genome sequences. Normalization procedures are also applicable to evolutionary research. Thus, normalization of the contents of whole genomes is a useful procedure that can help to characterize organisms.

Gobe: an interactive, web-based tool for comparative genomic visualization.

PubMed

Pedersen, Brent S; Tang, Haibao; Freeling, Michael

2011-04-01

Gobe is a web-based tool for viewing comparative genomic data. It supports viewing multiple genomic regions simultaneously. Its simple text format and flash-based rendering make it an interactive, exploratory research tool. Gobe can be used without installation through our web service, or downloaded and customized with stylesheets and javascript callback functions. Gobe is a flash application that runs in all modern web-browsers. The full source-code, including that for the online web application is available under the MIT license at: http://github.com/brentp/gobe. Sample applications are hosted at http://try-gobe.appspot.com/ and http://synteny.cnr.berkeley.edu/gobe-app/.

GeneWiz browser: An Interactive Tool for Visualizing Sequenced Chromosomes.

PubMed

Hallin, Peter F; Stærfeldt, Hans-Henrik; Rotenberg, Eva; Binnewies, Tim T; Benham, Craig J; Ussery, David W

2009-09-25

We present an interactive web application for visualizing genomic data of prokaryotic chromosomes. The tool (GeneWiz browser) allows users to carry out various analyses such as mapping alignments of homologous genes to other genomes, mapping of short sequencing reads to a reference chromosome, and calculating DNA properties such as curvature or stacking energy along the chromosome. The GeneWiz browser produces an interactive graphic that enables zooming from a global scale down to single nucleotides, without changing the size of the plot. Its ability to disproportionally zoom provides optimal readability and increased functionality compared to other browsers. The tool allows the user to select the display of various genomic features, color setting and data ranges. Custom numerical data can be added to the plot allowing, for example, visualization of gene expression and regulation data. Further, standard atlases are pre-generated for all prokaryotic genomes available in GenBank, providing a fast overview of all available genomes, including recently deposited genome sequences. The tool is available online from http://www.cbs.dtu.dk/services/gwBrowser. Supplemental material including interactive atlases is available online at http://www.cbs.dtu.dk/services/gwBrowser/suppl/.

PathFinder: reconstruction and dynamic visualization of metabolic pathways.

PubMed

Goesmann, Alexander; Haubrock, Martin; Meyer, Folker; Kalinowski, Jörn; Giegerich, Robert

2002-01-01

Beyond methods for a gene-wise annotation and analysis of sequenced genomes new automated methods for functional analysis on a higher level are needed. The identification of realized metabolic pathways provides valuable information on gene expression and regulation. Detection of incomplete pathways helps to improve a constantly evolving genome annotation or discover alternative biochemical pathways. To utilize automated genome analysis on the level of metabolic pathways new methods for the dynamic representation and visualization of pathways are needed. PathFinder is a tool for the dynamic visualization of metabolic pathways based on annotation data. Pathways are represented as directed acyclic graphs, graph layout algorithms accomplish the dynamic drawing and visualization of the metabolic maps. A more detailed analysis of the input data on the level of biochemical pathways helps to identify genes and detect improper parts of annotations. As an Relational Database Management System (RDBMS) based internet application PathFinder reads a list of EC-numbers or a given annotation in EMBL- or Genbank-format and dynamically generates pathway graphs.

A simple and efficient method to visualize and quantify the efficiency of chromosomal mutations from genome editing

PubMed Central

Fu, Liezhen; Wen, Luan; Luu, Nga; Shi, Yun-Bo

2016-01-01

Genome editing with designer nucleases such as TALEN and CRISPR/Cas enzymes has broad applications. Delivery of these designer nucleases into organisms induces various genetic mutations including deletions, insertions and nucleotide substitutions. Characterizing those mutations is critical for evaluating the efficacy and specificity of targeted genome editing. While a number of methods have been developed to identify the mutations, none other than sequencing allows the identification of the most desired mutations, i.e., out-of-frame insertions/deletions that disrupt genes. Here we report a simple and efficient method to visualize and quantify the efficiency of genomic mutations induced by genome-editing. Our approach is based on the expression of a two-color fusion protein in a vector that allows the insertion of the edited region in the genome in between the two color moieties. We show that our approach not only easily identifies developing animals with desired mutations but also efficiently quantifies the mutation rate in vivo. Furthermore, by using LacZα and GFP as the color moieties, our approach can even eliminate the need for a fluorescent microscope, allowing the analysis with simple bright field visualization. Such an approach will greatly simplify the screen for effective genome-editing enzymes and identify the desired mutant cells/animals. PMID:27748423

DCODE.ORG Anthology of Comparative Genomic Tools

DOE Office of Scientific and Technical Information (OSTI.GOV)

Loots, G G; Ovcharenko, I

2005-01-11

Comparative genomics provides the means to demarcate functional regions in anonymous DNA sequences. The successful application of this method to identifying novel genes is currently shifting to deciphering the noncoding encryption of gene regulation across genomes. To facilitate the use of comparative genomics to practical applications in genetics and genomics we have developed several analytical and visualization tools for the analysis of arbitrary sequences and whole genomes. These tools include two alignment tools: zPicture and Mulan; a phylogenetic shadowing tool: eShadow for identifying lineage- and species-specific functional elements; two evolutionary conserved transcription factor analysis tools: rVista and multiTF; a toolmore » for extracting cis-regulatory modules governing the expression of co-regulated genes, CREME; and a dynamic portal to multiple vertebrate and invertebrate genome alignments, the ECR Browser. Here we briefly describe each one of these tools and provide specific examples on their practical applications. All the tools are publicly available at the http://www.dcode.org/ web site.« less

Application of Genomic In Situ Hybridization in Horticultural Science

PubMed Central

Ramzan, Fahad; Lim, Ki-Byung

2017-01-01

Molecular cytogenetic techniques, such as in situ hybridization methods, are admirable tools to analyze the genomic structure and function, chromosome constituents, recombination patterns, alien gene introgression, genome evolution, aneuploidy, and polyploidy and also genome constitution visualization and chromosome discrimination from different genomes in allopolyploids of various horticultural crops. Using GISH advancement as multicolor detection is a significant approach to analyze the small and numerous chromosomes in fruit species, for example, Diospyros hybrids. This analytical technique has proved to be the most exact and effective way for hybrid status confirmation and helps remarkably to distinguish donor parental genomes in hybrids such as Clivia, Rhododendron, and Lycoris ornamental hybrids. The genome characterization facilitates in hybrid selection having potential desirable characteristics during the early hybridization breeding, as this technique expedites to detect introgressed sequence chromosomes. This review study epitomizes applications and advancements of genomic in situ hybridization (GISH) techniques in horticultural plants. PMID:28459054

Comparative visualization of genetic and physical maps with Strudel

PubMed Central

Bayer, Micha; Milne, Iain; Stephen, Gordon; Shaw, Paul; Cardle, Linda; Wright, Frank; Marshall, David

2011-01-01

Summary: Data visualization can play a key role in comparative genomics, for example, underpinning the investigation of conserved synteny patterns. Strudel is a desktop application that allows users to easily compare both genetic and physical maps interactively and efficiently. It can handle large datasets from several genomes simultaneously, and allows all-by-all comparisons between these. Availability and implementation: Installers for Strudel are available for Windows, Linux, Solaris and Mac OS X at http://bioinf.scri.ac.uk/strudel/. Contact: strudel@scri.ac.uk; micha.bayer@scri.ac.uk PMID:21372085

bioWidgets: data interaction components for genomics.

PubMed

Fischer, S; Crabtree, J; Brunk, B; Gibson, M; Overton, G C

1999-10-01

The presentation of genomics data in a perspicuous visual format is critical for its rapid interpretation and validation. Relatively few public database developers have the resources to implement sophisticated front-end user interfaces themselves. Accordingly, these developers would benefit from a reusable toolkit of user interface and data visualization components. We have designed the bioWidget toolkit as a set of JavaBean components. It includes a wide array of user interface components and defines an architecture for assembling applications. The toolkit is founded on established software engineering design patterns and principles, including componentry, Model-View-Controller, factored models and schema neutrality. As a proof of concept, we have used the bioWidget toolkit to create three extendible applications: AnnotView, BlastView and AlignView.

Prokaryotic Contig Annotation Pipeline Server: Web Application for a Prokaryotic Genome Annotation Pipeline Based on the Shiny App Package.

PubMed

Park, Byeonghyeok; Baek, Min-Jeong; Min, Byoungnam; Choi, In-Geol

2017-09-01

Genome annotation is a primary step in genomic research. To establish a light and portable prokaryotic genome annotation pipeline for use in individual laboratories, we developed a Shiny app package designated as "P-CAPS" (Prokaryotic Contig Annotation Pipeline Server). The package is composed of R and Python scripts that integrate publicly available annotation programs into a server application. P-CAPS is not only a browser-based interactive application but also a distributable Shiny app package that can be installed on any personal computer. The final annotation is provided in various standard formats and is summarized in an R markdown document. Annotation can be visualized and examined with a public genome browser. A benchmark test showed that the annotation quality and completeness of P-CAPS were reliable and compatible with those of currently available public pipelines.

Dcode.org anthology of comparative genomic tools.

PubMed

Loots, Gabriela G; Ovcharenko, Ivan

2005-07-01

Comparative genomics provides the means to demarcate functional regions in anonymous DNA sequences. The successful application of this method to identifying novel genes is currently shifting to deciphering the non-coding encryption of gene regulation across genomes. To facilitate the practical application of comparative sequence analysis to genetics and genomics, we have developed several analytical and visualization tools for the analysis of arbitrary sequences and whole genomes. These tools include two alignment tools, zPicture and Mulan; a phylogenetic shadowing tool, eShadow for identifying lineage- and species-specific functional elements; two evolutionary conserved transcription factor analysis tools, rVista and multiTF; a tool for extracting cis-regulatory modules governing the expression of co-regulated genes, Creme 2.0; and a dynamic portal to multiple vertebrate and invertebrate genome alignments, the ECR Browser. Here, we briefly describe each one of these tools and provide specific examples on their practical applications. All the tools are publicly available at the http://www.dcode.org/ website.

GenPlay Multi-Genome, a tool to compare and analyze multiple human genomes in a graphical interface.

PubMed

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.

CMS: A Web-Based System for Visualization and Analysis of Genome-Wide Methylation Data of Human Cancers

PubMed Central

Huang, Yi-Wen; Roa, Juan C.; Goodfellow, Paul J.; Kizer, E. Lynette; Huang, Tim H. M.; Chen, Yidong

2013-01-01

Background DNA methylation of promoter CpG islands is associated with gene suppression, and its unique genome-wide profiles have been linked to tumor progression. Coupled with high-throughput sequencing technologies, it can now efficiently determine genome-wide methylation profiles in cancer cells. Also, experimental and computational technologies make it possible to find the functional relationship between cancer-specific methylation patterns and their clinicopathological parameters. Methodology/Principal Findings Cancer methylome system (CMS) is a web-based database application designed for the visualization, comparison and statistical analysis of human cancer-specific DNA methylation. Methylation intensities were obtained from MBDCap-sequencing, pre-processed and stored in the database. 191 patient samples (169 tumor and 22 normal specimen) and 41 breast cancer cell-lines are deposited in the database, comprising about 6.6 billion uniquely mapped sequence reads. This provides comprehensive and genome-wide epigenetic portraits of human breast cancer and endometrial cancer to date. Two views are proposed for users to better understand methylation structure at the genomic level or systemic methylation alteration at the gene level. In addition, a variety of annotation tracks are provided to cover genomic information. CMS includes important analytic functions for interpretation of methylation data, such as the detection of differentially methylated regions, statistical calculation of global methylation intensities, multiple gene sets of biologically significant categories, interactivity with UCSC via custom-track data. We also present examples of discoveries utilizing the framework. Conclusions/Significance CMS provides visualization and analytic functions for cancer methylome datasets. A comprehensive collection of datasets, a variety of embedded analytic functions and extensive applications with biological and translational significance make this system powerful and unique in cancer methylation research. CMS is freely accessible at: http://cbbiweb.uthscsa.edu/KMethylomes/. PMID:23630576

CMS: a web-based system for visualization and analysis of genome-wide methylation data of human cancers.

PubMed

Gu, Fei; Doderer, Mark S; Huang, Yi-Wen; Roa, Juan C; Goodfellow, Paul J; Kizer, E Lynette; Huang, Tim H M; Chen, Yidong

2013-01-01

DNA methylation of promoter CpG islands is associated with gene suppression, and its unique genome-wide profiles have been linked to tumor progression. Coupled with high-throughput sequencing technologies, it can now efficiently determine genome-wide methylation profiles in cancer cells. Also, experimental and computational technologies make it possible to find the functional relationship between cancer-specific methylation patterns and their clinicopathological parameters. Cancer methylome system (CMS) is a web-based database application designed for the visualization, comparison and statistical analysis of human cancer-specific DNA methylation. Methylation intensities were obtained from MBDCap-sequencing, pre-processed and stored in the database. 191 patient samples (169 tumor and 22 normal specimen) and 41 breast cancer cell-lines are deposited in the database, comprising about 6.6 billion uniquely mapped sequence reads. This provides comprehensive and genome-wide epigenetic portraits of human breast cancer and endometrial cancer to date. Two views are proposed for users to better understand methylation structure at the genomic level or systemic methylation alteration at the gene level. In addition, a variety of annotation tracks are provided to cover genomic information. CMS includes important analytic functions for interpretation of methylation data, such as the detection of differentially methylated regions, statistical calculation of global methylation intensities, multiple gene sets of biologically significant categories, interactivity with UCSC via custom-track data. We also present examples of discoveries utilizing the framework. CMS provides visualization and analytic functions for cancer methylome datasets. A comprehensive collection of datasets, a variety of embedded analytic functions and extensive applications with biological and translational significance make this system powerful and unique in cancer methylation research. CMS is freely accessible at: http://cbbiweb.uthscsa.edu/KMethylomes/.

Microreact: visualizing and sharing data for genomic epidemiology and phylogeography

PubMed Central

Argimón, Silvia; Abudahab, Khalil; Goater, Richard J. E.; Fedosejev, Artemij; Bhai, Jyothish; Glasner, Corinna; Feil, Edward J.; Holden, Matthew T. G.; Yeats, Corin A.; Grundmann, Hajo; Spratt, Brian G.

2016-01-01

Visualization is frequently used to aid our interpretation of complex datasets. Within microbial genomics, visualizing the relationships between multiple genomes as a tree provides a framework onto which associated data (geographical, temporal, phenotypic and epidemiological) are added to generate hypotheses and to explore the dynamics of the system under investigation. Selected static images are then used within publications to highlight the key findings to a wider audience. However, these images are a very inadequate way of exploring and interpreting the richness of the data. There is, therefore, a need for flexible, interactive software that presents the population genomic outputs and associated data in a user-friendly manner for a wide range of end users, from trained bioinformaticians to front-line epidemiologists and health workers. Here, we present Microreact, a web application for the easy visualization of datasets consisting of any combination of trees, geographical, temporal and associated metadata. Data files can be uploaded to Microreact directly via the web browser or by linking to their location (e.g. from Google Drive/Dropbox or via API), and an integrated visualization via trees, maps, timelines and tables provides interactive querying of the data. The visualization can be shared as a permanent web link among collaborators, or embedded within publications to enable readers to explore and download the data. Microreact can act as an end point for any tool or bioinformatic pipeline that ultimately generates a tree, and provides a simple, yet powerful, visualization method that will aid research and discovery and the open sharing of datasets. PMID:28348833

CRISPR/Cas9 for Human Genome Engineering and Disease Research.

PubMed

Xiong, Xin; Chen, Meng; Lim, Wendell A; Zhao, Dehua; Qi, Lei S

2016-08-31

The clustered regularly interspaced short palindromic repeats (CRISPR)/CRISPR-associated 9 (Cas9) system, a versatile RNA-guided DNA targeting platform, has been revolutionizing our ability to modify, manipulate, and visualize the human genome, which greatly advances both biological research and therapeutics development. Here, we review the current development of CRISPR/Cas9 technologies for gene editing, transcription regulation, genome imaging, and epigenetic modification. We discuss the broad application of this system to the study of functional genomics, especially genome-wide genetic screening, and to therapeutics development, including establishing disease models, correcting defective genetic mutations, and treating diseases.

CuGene as a tool to view and explore genomic data

NASA Astrophysics Data System (ADS)

Haponiuk, Michał; Pawełkowicz, Magdalena; Przybecki, Zbigniew; Nowak, Robert M.

2017-08-01

Integrated CuGene is an easy-to-use, open-source, on-line tool that can be used to browse, analyze, and query genomic data and annotations. It places annotation tracks beneath genome coordinate positions, allowing rapid visual correlation of different types of information. It also allows users to upload and display their own experimental results or annotation sets. An important functionality of the application is a possibility to find similarity between sequences by applying four different algorithms of different accuracy. The presented tool was tested on real genomic data and is extensively used by Polish Consortium of Cucumber Genome Sequencing.

Visualization of aging-associated chromatin alterations with an engineered TALE system

PubMed Central

Ren, Ruotong; Deng, Liping; Xue, Yanhong; Suzuki, Keiichiro; Zhang, Weiqi; Yu, Yang; Wu, Jun; Sun, Liang; Gong, Xiaojun; Luan, Huiqin; Yang, Fan; Ju, Zhenyu; Ren, Xiaoqing; Wang, Si; Tang, Hong; Geng, Lingling; Zhang, Weizhou; Li, Jian; Qiao, Jie; Xu, Tao; Qu, Jing; Liu, Guang-Hui

2017-01-01

Visualization of specific genomic loci in live cells is a prerequisite for the investigation of dynamic changes in chromatin architecture during diverse biological processes, such as cellular aging. However, current precision genomic imaging methods are hampered by the lack of fluorescent probes with high specificity and signal-to-noise contrast. We find that conventional transcription activator-like effectors (TALEs) tend to form protein aggregates, thereby compromising their performance in imaging applications. Through screening, we found that fusing thioredoxin with TALEs prevented aggregate formation, unlocking the full power of TALE-based genomic imaging. Using thioredoxin-fused TALEs (TTALEs), we achieved high-quality imaging at various genomic loci and observed aging-associated (epi) genomic alterations at telomeres and centromeres in human and mouse premature aging models. Importantly, we identified attrition of ribosomal DNA repeats as a molecular marker for human aging. Our study establishes a simple and robust imaging method for precisely monitoring chromatin dynamics in vitro and in vivo. PMID:28139645

Image Analysis of DNA Fiber and Nucleus in Plants.

PubMed

Ohmido, Nobuko; Wako, Toshiyuki; Kato, Seiji; Fukui, Kiichi

2016-01-01

Advances in cytology have led to the application of a wide range of visualization methods in plant genome studies. Image analysis methods are indispensable tools where morphology, density, and color play important roles in the biological systems. Visualization and image analysis methods are useful techniques in the analyses of the detailed structure and function of extended DNA fibers (EDFs) and interphase nuclei. The EDF is the highest in the spatial resolving power to reveal genome structure and it can be used for physical mapping, especially for closely located genes and tandemly repeated sequences. One the other hand, analyzing nuclear DNA and proteins would reveal nuclear structure and functions. In this chapter, we describe the image analysis protocol for quantitatively analyzing different types of plant genome, EDFs and interphase nuclei.

Comparative analysis and visualization of multiple collinear genomes

PubMed Central

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

GenomeCAT: a versatile tool for the analysis and integrative visualization of DNA copy number variants.

PubMed

Tebel, Katrin; Boldt, Vivien; Steininger, Anne; Port, Matthias; Ebert, Grit; Ullmann, Reinhard

2017-01-06

The analysis of DNA copy number variants (CNV) has increasing impact in the field of genetic diagnostics and research. However, the interpretation of CNV data derived from high resolution array CGH or NGS platforms is complicated by the considerable variability of the human genome. Therefore, tools for multidimensional data analysis and comparison of patient cohorts are needed to assist in the discrimination of clinically relevant CNVs from others. We developed GenomeCAT, a standalone Java application for the analysis and integrative visualization of CNVs. GenomeCAT is composed of three modules dedicated to the inspection of single cases, comparative analysis of multidimensional data and group comparisons aiming at the identification of recurrent aberrations in patients sharing the same phenotype, respectively. Its flexible import options ease the comparative analysis of own results derived from microarray or NGS platforms with data from literature or public depositories. Multidimensional data obtained from different experiment types can be merged into a common data matrix to enable common visualization and analysis. All results are stored in the integrated MySQL database, but can also be exported as tab delimited files for further statistical calculations in external programs. GenomeCAT offers a broad spectrum of visualization and analysis tools that assist in the evaluation of CNVs in the context of other experiment data and annotations. The use of GenomeCAT does not require any specialized computer skills. The various R packages implemented for data analysis are fully integrated into GenomeCATs graphical user interface and the installation process is supported by a wizard. The flexibility in terms of data import and export in combination with the ability to create a common data matrix makes the program also well suited as an interface between genomic data from heterogeneous sources and external software tools. Due to the modular architecture the functionality of GenomeCAT can be easily extended by further R packages or customized plug-ins to meet future requirements.

Enhanced annotations and features for comparing thousands of Pseudomonas genomes in the Pseudomonas genome database.

PubMed

Winsor, Geoffrey L; Griffiths, Emma J; Lo, Raymond; Dhillon, Bhavjinder K; Shay, Julie A; Brinkman, Fiona S L

2016-01-04

The Pseudomonas Genome Database (http://www.pseudomonas.com) is well known for the application of community-based annotation approaches for producing a high-quality Pseudomonas aeruginosa PAO1 genome annotation, and facilitating whole-genome comparative analyses with other Pseudomonas strains. To aid analysis of potentially thousands of complete and draft genome assemblies, this database and analysis platform was upgraded to integrate curated genome annotations and isolate metadata with enhanced tools for larger scale comparative analysis and visualization. Manually curated gene annotations are supplemented with improved computational analyses that help identify putative drug targets and vaccine candidates or assist with evolutionary studies by identifying orthologs, pathogen-associated genes and genomic islands. The database schema has been updated to integrate isolate metadata that will facilitate more powerful analysis of genomes across datasets in the future. We continue to place an emphasis on providing high-quality updates to gene annotations through regular review of the scientific literature and using community-based approaches including a major new Pseudomonas community initiative for the assignment of high-quality gene ontology terms to genes. As we further expand from thousands of genomes, we plan to provide enhancements that will aid data visualization and analysis arising from whole-genome comparative studies including more pan-genome and population-based approaches. © The Author(s) 2015. Published by Oxford University Press on behalf of Nucleic Acids Research.

GenomeGraphs: integrated genomic data visualization with R.

PubMed

Durinck, Steffen; Bullard, James; Spellman, Paul T; Dudoit, Sandrine

2009-01-06

Biological studies involve a growing number of distinct high-throughput experiments to characterize samples of interest. There is a lack of methods to visualize these different genomic datasets in a versatile manner. In addition, genomic data analysis requires integrated visualization of experimental data along with constantly changing genomic annotation and statistical analyses. We developed GenomeGraphs, as an add-on software package for the statistical programming environment R, to facilitate integrated visualization of genomic datasets. GenomeGraphs uses the biomaRt package to perform on-line annotation queries to Ensembl and translates these to gene/transcript structures in viewports of the grid graphics package. This allows genomic annotation to be plotted together with experimental data. GenomeGraphs can also be used to plot custom annotation tracks in combination with different experimental data types together in one plot using the same genomic coordinate system. GenomeGraphs is a flexible and extensible software package which can be used to visualize a multitude of genomic datasets within the statistical programming environment R.

BioCircos.js: an interactive Circos JavaScript library for biological data visualization on web applications.

PubMed

Cui, Ya; Chen, Xiaowei; Luo, Huaxia; Fan, Zhen; Luo, Jianjun; He, Shunmin; Yue, Haiyan; Zhang, Peng; Chen, Runsheng

2016-06-01

We here present BioCircos.js, an interactive and lightweight JavaScript library especially for biological data interactive visualization. BioCircos.js facilitates the development of web-based applications for circular visualization of various biological data, such as genomic features, genetic variations, gene expression and biomolecular interactions. BioCircos.js and its manual are freely available online at http://bioinfo.ibp.ac.cn/biocircos/ rschen@ibp.ac.cn 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.

Advances in Engineering the Fly Genome with the CRISPR-Cas System

PubMed Central

Bier, Ethan; Harrison, Melissa M.; O’Connor-Giles, Kate M.; Wildonger, Jill

2018-01-01

Drosophila has long been a premier model for the development and application of cutting-edge genetic approaches. The CRISPR-Cas system now adds the ability to manipulate the genome with ease and precision, providing a rich toolbox to interrogate relationships between genotype and phenotype, to delineate and visualize how the genome is organized, to illuminate and manipulate RNA, and to pioneer new gene drive technologies. Myriad transformative approaches have already originated from the CRISPR-Cas system, which will likely continue to spark the creation of tools with diverse applications. Here, we provide an overview of how CRISPR-Cas gene editing has revolutionized genetic analysis in Drosophila and highlight key areas for future advances. PMID:29301946

Family genome browser: visualizing genomes with pedigree information.

PubMed

Juan, Liran; Liu, Yongzhuang; Wang, Yongtian; Teng, Mingxiang; Zang, Tianyi; Wang, Yadong

2015-07-15

Families with inherited diseases are widely used in Mendelian/complex disease studies. Owing to the advances in high-throughput sequencing technologies, family genome sequencing becomes more and more prevalent. Visualizing family genomes can greatly facilitate human genetics studies and personalized medicine. However, due to the complex genetic relationships and high similarities among genomes of consanguineous family members, family genomes are difficult to be visualized in traditional genome visualization framework. How to visualize the family genome variants and their functions with integrated pedigree information remains a critical challenge. We developed the Family Genome Browser (FGB) to provide comprehensive analysis and visualization for family genomes. The FGB can visualize family genomes in both individual level and variant level effectively, through integrating genome data with pedigree information. Family genome analysis, including determination of parental origin of the variants, detection of de novo mutations, identification of potential recombination events and identical-by-decent segments, etc., can be performed flexibly. Diverse annotations for the family genome variants, such as dbSNP memberships, linkage disequilibriums, genes, variant effects, potential phenotypes, etc., are illustrated as well. Moreover, the FGB can automatically search de novo mutations and compound heterozygous variants for a selected individual, and guide investigators to find high-risk genes with flexible navigation options. These features enable users to investigate and understand family genomes intuitively and systematically. The FGB is available at http://mlg.hit.edu.cn/FGB/. © The Author 2015. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

Gene Graphics: a genomic neighborhood data visualization web application.

PubMed

Harrison, Katherine J; Crécy-Lagard, Valérie de; Zallot, Rémi

2018-04-15

The examination of gene neighborhood is an integral part of comparative genomics but no tools to produce publication quality graphics of gene clusters are available. Gene Graphics is a straightforward web application for creating such visuals. Supported inputs include National Center for Biotechnology Information gene and protein identifiers with automatic fetching of neighboring information, GenBank files and data extracted from the SEED database. Gene representations can be customized for many parameters including gene and genome names, colors and sizes. Gene attributes can be copied and pasted for rapid and user-friendly customization of homologous genes between species. In addition to Portable Network Graphics and Scalable Vector Graphics, produced representations can be exported as Tagged Image File Format or Encapsulated PostScript, formats that are standard for publication. Hands-on tutorials with real life examples inspired from publications are available for training. Gene Graphics is freely available at https://katlabs.cc/genegraphics/ and source code is hosted at https://github.com/katlabs/genegraphics. katherinejh@ufl.edu or remizallot@ufl.edu. Supplementary data are available at Bioinformatics online.

BactoGeNIE: A large-scale comparative genome visualization for big displays

DOE PAGES

Aurisano, Jillian; Reda, Khairi; Johnson, Andrew; ...

2015-08-13

The volume of complete bacterial genome sequence data available to comparative genomics researchers is rapidly increasing. However, visualizations in comparative genomics--which aim to enable analysis tasks across collections of genomes--suffer from visual scalability issues. While large, multi-tiled and high-resolution displays have the potential to address scalability issues, new approaches are needed to take advantage of such environments, in order to enable the effective visual analysis of large genomics datasets. In this paper, we present Bacterial Gene Neighborhood Investigation Environment, or BactoGeNIE, a novel and visually scalable design for comparative gene neighborhood analysis on large display environments. We evaluate BactoGeNIE throughmore » a case study on close to 700 draft Escherichia coli genomes, and present lessons learned from our design process. In conclusion, BactoGeNIE accommodates comparative tasks over substantially larger collections of neighborhoods than existing tools and explicitly addresses visual scalability. Given current trends in data generation, scalable designs of this type may inform visualization design for large-scale comparative research problems in genomics.« less

BactoGeNIE: a large-scale comparative genome visualization for big displays

PubMed Central

2015-01-01

Background The volume of complete bacterial genome sequence data available to comparative genomics researchers is rapidly increasing. However, visualizations in comparative genomics--which aim to enable analysis tasks across collections of genomes--suffer from visual scalability issues. While large, multi-tiled and high-resolution displays have the potential to address scalability issues, new approaches are needed to take advantage of such environments, in order to enable the effective visual analysis of large genomics datasets. Results In this paper, we present Bacterial Gene Neighborhood Investigation Environment, or BactoGeNIE, a novel and visually scalable design for comparative gene neighborhood analysis on large display environments. We evaluate BactoGeNIE through a case study on close to 700 draft Escherichia coli genomes, and present lessons learned from our design process. Conclusions BactoGeNIE accommodates comparative tasks over substantially larger collections of neighborhoods than existing tools and explicitly addresses visual scalability. Given current trends in data generation, scalable designs of this type may inform visualization design for large-scale comparative research problems in genomics. PMID:26329021

BactoGeNIE: A large-scale comparative genome visualization for big displays

DOE Office of Scientific and Technical Information (OSTI.GOV)

Aurisano, Jillian; Reda, Khairi; Johnson, Andrew

The volume of complete bacterial genome sequence data available to comparative genomics researchers is rapidly increasing. However, visualizations in comparative genomics--which aim to enable analysis tasks across collections of genomes--suffer from visual scalability issues. While large, multi-tiled and high-resolution displays have the potential to address scalability issues, new approaches are needed to take advantage of such environments, in order to enable the effective visual analysis of large genomics datasets. In this paper, we present Bacterial Gene Neighborhood Investigation Environment, or BactoGeNIE, a novel and visually scalable design for comparative gene neighborhood analysis on large display environments. We evaluate BactoGeNIE throughmore » a case study on close to 700 draft Escherichia coli genomes, and present lessons learned from our design process. In conclusion, BactoGeNIE accommodates comparative tasks over substantially larger collections of neighborhoods than existing tools and explicitly addresses visual scalability. Given current trends in data generation, scalable designs of this type may inform visualization design for large-scale comparative research problems in genomics.« less

pileup.js: a JavaScript library for interactive and in-browser visualization of genomic data.

PubMed

Vanderkam, Dan; Aksoy, B Arman; Hodes, Isaac; Perrone, Jaclyn; Hammerbacher, Jeff

2016-08-01

P: ileup.js is a new browser-based genome viewer. It is designed to facilitate the investigation of evidence for genomic variants within larger web applications. It takes advantage of recent developments in the JavaScript ecosystem to provide a modular, reliable and easily embedded library. The code and documentation for pileup.js is publicly available at https://github.com/hammerlab/pileup.js under the Apache 2.0 license. correspondence@hammerlab.org. © The Author 2016. Published by Oxford University Press.

The Saccharomyces Genome Database Variant Viewer

PubMed Central

Sheppard, Travis K.; Hitz, Benjamin C.; Engel, Stacia R.; Song, Giltae; Balakrishnan, Rama; Binkley, Gail; Costanzo, Maria C.; Dalusag, Kyla S.; Demeter, Janos; Hellerstedt, Sage T.; Karra, Kalpana; Nash, Robert S.; Paskov, Kelley M.; Skrzypek, Marek S.; Weng, Shuai; Wong, Edith D.; Cherry, J. Michael

2016-01-01

The Saccharomyces Genome Database (SGD; http://www.yeastgenome.org) is the authoritative community resource for the Saccharomyces cerevisiae reference genome sequence and its annotation. In recent years, we have moved toward increased representation of sequence variation and allelic differences within S. cerevisiae. The publication of numerous additional genomes has motivated the creation of new tools for their annotation and analysis. Here we present the Variant Viewer: a dynamic open-source web application for the visualization of genomic and proteomic differences. Multiple sequence alignments have been constructed across high quality genome sequences from 11 different S. cerevisiae strains and stored in the SGD. The alignments and summaries are encoded in JSON and used to create a two-tiered dynamic view of the budding yeast pan-genome, available at http://www.yeastgenome.org/variant-viewer. PMID:26578556

SeeGH--a software tool for visualization of whole genome array comparative genomic hybridization data.

PubMed

Chi, Bryan; DeLeeuw, Ronald J; Coe, Bradley P; MacAulay, Calum; Lam, Wan L

2004-02-09

Array comparative genomic hybridization (CGH) is a technique which detects copy number differences in DNA segments. Complete sequencing of the human genome and the development of an array representing a tiling set of tens of thousands of DNA segments spanning the entire human genome has made high resolution copy number analysis throughout the genome possible. Since array CGH provides signal ratio for each DNA segment, visualization would require the reassembly of individual data points into chromosome profiles. We have developed a visualization tool for displaying whole genome array CGH data in the context of chromosomal location. SeeGH is an application that translates spot signal ratio data from array CGH experiments to displays of high resolution chromosome profiles. Data is imported from a simple tab delimited text file obtained from standard microarray image analysis software. SeeGH processes the signal ratio data and graphically displays it in a conventional CGH karyotype diagram with the added features of magnification and DNA segment annotation. In this process, SeeGH imports the data into a database, calculates the average ratio and standard deviation for each replicate spot, and links them to chromosome regions for graphical display. Once the data is displayed, users have the option of hiding or flagging DNA segments based on user defined criteria, and retrieve annotation information such as clone name, NCBI sequence accession number, ratio, base pair position on the chromosome, and standard deviation. SeeGH represents a novel software tool used to view and analyze array CGH data. The software gives users the ability to view the data in an overall genomic view as well as magnify specific chromosomal regions facilitating the precise localization of genetic alterations. SeeGH is easily installed and runs on Microsoft Windows 2000 or later environments.

Treelink: data integration, clustering and visualization of phylogenetic trees.

PubMed

Allende, Christian; Sohn, Erik; Little, Cedric

2015-12-29

Phylogenetic trees are central to a wide range of biological studies. In many of these studies, tree nodes need to be associated with a variety of attributes. For example, in studies concerned with viral relationships, tree nodes are associated with epidemiological information, such as location, age and subtype. Gene trees used in comparative genomics are usually linked with taxonomic information, such as functional annotations and events. A wide variety of tree visualization and annotation tools have been developed in the past, however none of them are intended for an integrative and comparative analysis. Treelink is a platform-independent software for linking datasets and sequence files to phylogenetic trees. The application allows an automated integration of datasets to trees for operations such as classifying a tree based on a field or showing the distribution of selected data attributes in branches and leafs. Genomic and proteonomic sequences can also be linked to the tree and extracted from internal and external nodes. A novel clustering algorithm to simplify trees and display the most divergent clades was also developed, where validation can be achieved using the data integration and classification function. Integrated geographical information allows ancestral character reconstruction for phylogeographic plotting based on parsimony and likelihood algorithms. Our software can successfully integrate phylogenetic trees with different data sources, and perform operations to differentiate and visualize those differences within a tree. File support includes the most popular formats such as newick and csv. Exporting visualizations as images, cluster outputs and genomic sequences is supported. Treelink is available as a web and desktop application at http://www.treelinkapp.com .

CGI: Java Software for Mapping and Visualizing Data from Array-based Comparative Genomic Hybridization and Expression Profiling

PubMed Central

Gu, Joyce Xiuweu-Xu; Wei, Michael Yang; Rao, Pulivarthi H.; Lau, Ching C.; Behl, Sanjiv; Man, Tsz-Kwong

2007-01-01

With the increasing application of various genomic technologies in biomedical research, there is a need to integrate these data to correlate candidate genes/regions that are identified by different genomic platforms. Although there are tools that can analyze data from individual platforms, essential software for integration of genomic data is still lacking. Here, we present a novel Java-based program called CGI (Cytogenetics-Genomics Integrator) that matches the BAC clones from array-based comparative genomic hybridization (aCGH) to genes from RNA expression profiling datasets. The matching is computed via a fast, backend MySQL database containing UCSC Genome Browser annotations. This program also provides an easy-to-use graphical user interface for visualizing and summarizing the correlation of DNA copy number changes and RNA expression patterns from a set of experiments. In addition, CGI uses a Java applet to display the copy number values of a specific BAC clone in aCGH experiments side by side with the expression levels of genes that are mapped back to that BAC clone from the microarray experiments. The CGI program is built on top of extensible, reusable graphic components specifically designed for biologists. It is cross-platform compatible and the source code is freely available under the General Public License. PMID:19936083

CGI: Java software for mapping and visualizing data from array-based comparative genomic hybridization and expression profiling.

PubMed

Gu, Joyce Xiuweu-Xu; Wei, Michael Yang; Rao, Pulivarthi H; Lau, Ching C; Behl, Sanjiv; Man, Tsz-Kwong

2007-10-06

With the increasing application of various genomic technologies in biomedical research, there is a need to integrate these data to correlate candidate genes/regions that are identified by different genomic platforms. Although there are tools that can analyze data from individual platforms, essential software for integration of genomic data is still lacking. Here, we present a novel Java-based program called CGI (Cytogenetics-Genomics Integrator) that matches the BAC clones from array-based comparative genomic hybridization (aCGH) to genes from RNA expression profiling datasets. The matching is computed via a fast, backend MySQL database containing UCSC Genome Browser annotations. This program also provides an easy-to-use graphical user interface for visualizing and summarizing the correlation of DNA copy number changes and RNA expression patterns from a set of experiments. In addition, CGI uses a Java applet to display the copy number values of a specific BAC clone in aCGH experiments side by side with the expression levels of genes that are mapped back to that BAC clone from the microarray experiments. The CGI program is built on top of extensible, reusable graphic components specifically designed for biologists. It is cross-platform compatible and the source code is freely available under the General Public License.

Efficient CRISPR/Cas9-based genome editing in carrot cells.

PubMed

Klimek-Chodacka, Magdalena; Oleszkiewicz, Tomasz; Lowder, Levi G; Qi, Yiping; Baranski, Rafal

2018-04-01

The first report presenting successful and efficient carrot genome editing using CRISPR/Cas9 system. Clustered Regularly Interspaced Short Palindromic Repeats (CRISPR)/CRISPR-associated (Cas9) is a powerful genome editing tool that has been widely adopted in model organisms recently, but has not been used in carrot-a model species for in vitro culture studies and an important health-promoting crop grown worldwide. In this study, for the first time, we report application of the CRISPR/Cas9 system for efficient targeted mutagenesis of the carrot genome. Multiplexing CRISPR/Cas9 vectors expressing two single-guide RNA (gRNAs) targeting the carrot flavanone-3-hydroxylase (F3H) gene were tested for blockage of the anthocyanin biosynthesis in a model purple-colored callus using Agrobacterium-mediated genetic transformation. This approach allowed fast and visual comparison of three codon-optimized Cas9 genes and revealed that the most efficient one in generating F3H mutants was the Arabidopsis codon-optimized AteCas9 gene with up to 90% efficiency. Knockout of F3H gene resulted in the discoloration of calli, validating the functional role of this gene in the anthocyanin biosynthesis in carrot as well as providing a visual marker for screening successfully edited events. Most resulting mutations were small Indels, but long chromosome fragment deletions of 116-119 nt were also generated with simultaneous cleavage mediated by two gRNAs. The results demonstrate successful site-directed mutagenesis in carrot with CRISPR/Cas9 and the usefulness of a model callus culture to validate genome editing systems. Given that the carrot genome has been sequenced recently, our timely study sheds light on the promising application of genome editing tools for boosting basic and translational research in this important vegetable crop.

Savant Genome Browser 2: visualization and analysis for population-scale genomics.

PubMed

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

PubMed Central

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

Repetitive element signature-based visualization, distance computation, and classification of 1766 microbial genomes.

PubMed

Lee, Kang-Hoon; Shin, Kyung-Seop; Lim, Debora; Kim, Woo-Chan; Chung, Byung Chang; Han, Gyu-Bum; Roh, Jeongkyu; Cho, Dong-Ho; Cho, Kiho

2015-07-01

The genomes of living organisms are populated with pleomorphic repetitive elements (REs) of varying densities. Our hypothesis that genomic RE landscapes are species/strain/individual-specific was implemented into the Genome Signature Imaging system to visualize and compute the RE-based signatures of any genome. Following the occurrence profiling of 5-nucleotide REs/words, the information from top-50 frequency words was transformed into a genome-specific signature and visualized as Genome Signature Images (GSIs), using a CMYK scheme. An algorithm for computing distances among GSIs was formulated using the GSIs' variables (word identity, frequency, and frequency order). The utility of the GSI-distance computation system was demonstrated with control genomes. GSI-based computation of genome-relatedness among 1766 microbes (117 archaea and 1649 bacteria) identified their clustering patterns; although the majority paralleled the established classification, some did not. The Genome Signature Imaging system, with its visualization and distance computation functions, enables genome-scale evolutionary studies involving numerous genomes with varying sizes. Copyright © 2015 Elsevier Inc. All rights reserved.

Applications of the pipeline environment for visual informatics and genomics computations

PubMed Central

2011-01-01

Background Contemporary informatics and genomics research require efficient, flexible and robust management of large heterogeneous data, advanced computational tools, powerful visualization, reliable hardware infrastructure, interoperability of computational resources, and detailed data and analysis-protocol provenance. The Pipeline is a client-server distributed computational environment that facilitates the visual graphical construction, execution, monitoring, validation and dissemination of advanced data analysis protocols. Results This paper reports on the applications of the LONI Pipeline environment to address two informatics challenges - graphical management of diverse genomics tools, and the interoperability of informatics software. Specifically, this manuscript presents the concrete details of deploying general informatics suites and individual software tools to new hardware infrastructures, the design, validation and execution of new visual analysis protocols via the Pipeline graphical interface, and integration of diverse informatics tools via the Pipeline eXtensible Markup Language syntax. We demonstrate each of these processes using several established informatics packages (e.g., miBLAST, EMBOSS, mrFAST, GWASS, MAQ, SAMtools, Bowtie) for basic local sequence alignment and search, molecular biology data analysis, and genome-wide association studies. These examples demonstrate the power of the Pipeline graphical workflow environment to enable integration of bioinformatics resources which provide a well-defined syntax for dynamic specification of the input/output parameters and the run-time execution controls. Conclusions The LONI Pipeline environment http://pipeline.loni.ucla.edu provides a flexible graphical infrastructure for efficient biomedical computing and distributed informatics research. The interactive Pipeline resource manager enables the utilization and interoperability of diverse types of informatics resources. The Pipeline client-server model provides computational power to a broad spectrum of informatics investigators - experienced developers and novice users, user with or without access to advanced computational-resources (e.g., Grid, data), as well as basic and translational scientists. The open development, validation and dissemination of computational networks (pipeline workflows) facilitates the sharing of knowledge, tools, protocols and best practices, and enables the unbiased validation and replication of scientific findings by the entire community. PMID:21791102

Kablammo: an interactive, web-based BLAST results visualizer.

PubMed

Wintersinger, Jeff A; Wasmuth, James D

2015-04-15

Kablammo is a web-based application that produces interactive, vector-based visualizations of sequence alignments generated by BLAST. These visualizations can illustrate many features, including shared protein domains, chromosome structural modifications and genome misassembly. Kablammo can be used at http://kablammo.wasmuthlab.org. For a local installation, the source code and instructions are available under the MIT license at http://github.com/jwintersinger/kablammo. jeff@wintersinger.org. © The Author 2014. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

Genome U-Plot: a whole genome visualization.

PubMed

Gaitatzes, Athanasios; Johnson, Sarah H; Smadbeck, James B; Vasmatzis, George

2018-05-15

The ability to produce and analyze whole genome sequencing (WGS) data from samples with structural variations (SV) generated the need to visualize such abnormalities in simplified plots. Conventional two-dimensional representations of WGS data frequently use either circular or linear layouts. There are several diverse advantages regarding both these representations, but their major disadvantage is that they do not use the two-dimensional space very efficiently. We propose a layout, termed the Genome U-Plot, which spreads the chromosomes on a two-dimensional surface and essentially quadruples the spatial resolution. We present the Genome U-Plot for producing clear and intuitive graphs that allows researchers to generate novel insights and hypotheses by visualizing SVs such as deletions, amplifications, and chromoanagenesis events. The main features of the Genome U-Plot are its layered layout, its high spatial resolution and its improved aesthetic qualities. We compare conventional visualization schemas with the Genome U-Plot using visualization metrics such as number of line crossings and crossing angle resolution measures. Based on our metrics, we improve the readability of the resulting graph by at least 2-fold, making apparent important features and making it easy to identify important genomic changes. A whole genome visualization tool with high spatial resolution and improved aesthetic qualities. An implementation and documentation of the Genome U-Plot is publicly available at https://github.com/gaitat/GenomeUPlot. vasmatzis.george@mayo.edu. Supplementary data are available at Bioinformatics online.

Integrated genome browser: visual analytics platform for genomics.

PubMed

Freese, Nowlan H; Norris, David C; Loraine, Ann E

2016-07-15

Genome browsers that support fast navigation through vast datasets and provide interactive visual analytics functions can help scientists achieve deeper insight into biological systems. Toward this end, we developed Integrated Genome Browser (IGB), a highly configurable, interactive and fast open source desktop genome browser. Here we describe multiple updates to IGB, including all-new capabilities to display and interact with data from high-throughput sequencing experiments. To demonstrate, we describe example visualizations and analyses of datasets from RNA-Seq, ChIP-Seq and bisulfite sequencing experiments. Understanding results from genome-scale experiments requires viewing the data in the context of reference genome annotations and other related datasets. To facilitate this, we enhanced IGB's ability to consume data from diverse sources, including Galaxy, Distributed Annotation and IGB-specific Quickload servers. To support future visualization needs as new genome-scale assays enter wide use, we transformed the IGB codebase into a modular, extensible platform for developers to create and deploy all-new visualizations of genomic data. IGB is open source and is freely available from http://bioviz.org/igb aloraine@uncc.edu. © The Author 2016. Published by Oxford University Press.

User Guidelines for the Brassica Database: BRAD.

PubMed

Wang, Xiaobo; Cheng, Feng; Wang, Xiaowu

2016-01-01

The genome sequence of Brassica rapa was first released in 2011. Since then, further Brassica genomes have been sequenced or are undergoing sequencing. It is therefore necessary to develop tools that help users to mine information from genomic data efficiently. This will greatly aid scientific exploration and breeding application, especially for those with low levels of bioinformatic training. Therefore, the Brassica database (BRAD) was built to collect, integrate, illustrate, and visualize Brassica genomic datasets. BRAD provides useful searching and data mining tools, and facilitates the search of gene annotation datasets, syntenic or non-syntenic orthologs, and flanking regions of functional genomic elements. It also includes genome-analysis tools such as BLAST and GBrowse. One of the important aims of BRAD is to build a bridge between Brassica crop genomes with the genome of the model species Arabidopsis thaliana, thus transferring the bulk of A. thaliana gene study information for use with newly sequenced Brassica crops.

QuIN: A Web Server for Querying and Visualizing Chromatin Interaction Networks.

PubMed

Thibodeau, Asa; Márquez, Eladio J; Luo, Oscar; Ruan, Yijun; Menghi, Francesca; Shin, Dong-Guk; Stitzel, Michael L; Vera-Licona, Paola; Ucar, Duygu

2016-06-01

Recent studies of the human genome have indicated that regulatory elements (e.g. promoters and enhancers) at distal genomic locations can interact with each other via chromatin folding and affect gene expression levels. Genomic technologies for mapping interactions between DNA regions, e.g., ChIA-PET and HiC, can generate genome-wide maps of interactions between regulatory elements. These interaction datasets are important resources to infer distal gene targets of non-coding regulatory elements and to facilitate prioritization of critical loci for important cellular functions. With the increasing diversity and complexity of genomic information and public ontologies, making sense of these datasets demands integrative and easy-to-use software tools. Moreover, network representation of chromatin interaction maps enables effective data visualization, integration, and mining. Currently, there is no software that can take full advantage of network theory approaches for the analysis of chromatin interaction datasets. To fill this gap, we developed a web-based application, QuIN, which enables: 1) building and visualizing chromatin interaction networks, 2) annotating networks with user-provided private and publicly available functional genomics and interaction datasets, 3) querying network components based on gene name or chromosome location, and 4) utilizing network based measures to identify and prioritize critical regulatory targets and their direct and indirect interactions. QuIN's web server is available at http://quin.jax.org QuIN is developed in Java and JavaScript, utilizing an Apache Tomcat web server and MySQL database and the source code is available under the GPLV3 license available on GitHub: https://github.com/UcarLab/QuIN/.

BiGG Models: A platform for integrating, standardizing and sharing genome-scale models

DOE PAGES

King, Zachary A.; Lu, Justin; Drager, Andreas; ...

2015-10-17

In this study, genome-scale metabolic models are mathematically structured knowledge bases that can be used to predict metabolic pathway usage and growth phenotypes. Furthermore, they can generate and test hypotheses when integrated with experimental data. To maximize the value of these models, centralized repositories of high-quality models must be established, models must adhere to established standards and model components must be linked to relevant databases. Tools for model visualization further enhance their utility. To meet these needs, we present BiGG Models (http://bigg.ucsd.edu), a completely redesigned Biochemical, Genetic and Genomic knowledge base. BiGG Models contains more than 75 high-quality, manually-curated genome-scalemore » metabolic models. On the website, users can browse, search and visualize models. BiGG Models connects genome-scale models to genome annotations and external databases. Reaction and metabolite identifiers have been standardized across models to conform to community standards and enable rapid comparison across models. Furthermore, BiGG Models provides a comprehensive application programming interface for accessing BiGG Models with modeling and analysis tools. As a resource for highly curated, standardized and accessible models of metabolism, BiGG Models will facilitate diverse systems biology studies and support knowledge-based analysis of diverse experimental data.« less

BiGG Models: A platform for integrating, standardizing and sharing genome-scale models

PubMed Central

King, Zachary A.; Lu, Justin; Dräger, Andreas; Miller, Philip; Federowicz, Stephen; Lerman, Joshua A.; Ebrahim, Ali; Palsson, Bernhard O.; Lewis, Nathan E.

2016-01-01

Genome-scale metabolic models are mathematically-structured knowledge bases that can be used to predict metabolic pathway usage and growth phenotypes. Furthermore, they can generate and test hypotheses when integrated with experimental data. To maximize the value of these models, centralized repositories of high-quality models must be established, models must adhere to established standards and model components must be linked to relevant databases. Tools for model visualization further enhance their utility. To meet these needs, we present BiGG Models (http://bigg.ucsd.edu), a completely redesigned Biochemical, Genetic and Genomic knowledge base. BiGG Models contains more than 75 high-quality, manually-curated genome-scale metabolic models. On the website, users can browse, search and visualize models. BiGG Models connects genome-scale models to genome annotations and external databases. Reaction and metabolite identifiers have been standardized across models to conform to community standards and enable rapid comparison across models. Furthermore, BiGG Models provides a comprehensive application programming interface for accessing BiGG Models with modeling and analysis tools. As a resource for highly curated, standardized and accessible models of metabolism, BiGG Models will facilitate diverse systems biology studies and support knowledge-based analysis of diverse experimental data. PMID:26476456

Panoptes: web-based exploration of large scale genome variation data.

PubMed

Vauterin, Paul; Jeffery, Ben; Miles, Alistair; Amato, Roberto; Hart, Lee; Wright, Ian; Kwiatkowski, Dominic

2017-10-15

The size and complexity of modern large-scale genome variation studies demand novel approaches for exploring and sharing the data. In order to unlock the potential of these data for a broad audience of scientists with various areas of expertise, a unified exploration framework is required that is accessible, coherent and user-friendly. Panoptes is an open-source software framework for collaborative visual exploration of large-scale genome variation data and associated metadata in a web browser. It relies on technology choices that allow it to operate in near real-time on very large datasets. It can be used to browse rich, hybrid content in a coherent way, and offers interactive visual analytics approaches to assist the exploration. We illustrate its application using genome variation data of Anopheles gambiae, Plasmodium falciparum and Plasmodium vivax. Freely available at https://github.com/cggh/panoptes, under the GNU Affero General Public License. paul.vauterin@gmail.com. © The Author 2017. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com

CartograTree: connecting tree genomes, phenotypes and environment.

PubMed

Vasquez-Gross, Hans A; Yu, John J; Figueroa, Ben; Gessler, Damian D G; Neale, David B; Wegrzyn, Jill L

2013-05-01

Today, researchers spend a tremendous amount of time gathering, formatting, filtering and visualizing data collected from disparate sources. Under the umbrella of forest tree biology, we seek to provide a platform and leverage modern technologies to connect biotic and abiotic data. Our goal is to provide an integrated web-based workspace that connects environmental, genomic and phenotypic data via geo-referenced coordinates. Here, we connect the genomic query web-based workspace, DiversiTree and a novel geographical interface called CartograTree to data housed on the TreeGenes database. To accomplish this goal, we implemented Simple Semantic Web Architecture and Protocol to enable the primary genomics database, TreeGenes, to communicate with semantic web services regardless of platform or back-end technologies. The novelty of CartograTree lies in the interactive workspace that allows for geographical visualization and engagement of high performance computing (HPC) resources. The application provides a unique tool set to facilitate research on the ecology, physiology and evolution of forest tree species. CartograTree can be accessed at: http://dendrome.ucdavis.edu/cartogratree. © 2013 Blackwell Publishing Ltd.

The Saccharomyces Genome Database Variant Viewer.

PubMed

Sheppard, Travis K; Hitz, Benjamin C; Engel, Stacia R; Song, Giltae; Balakrishnan, Rama; Binkley, Gail; Costanzo, Maria C; Dalusag, Kyla S; Demeter, Janos; Hellerstedt, Sage T; Karra, Kalpana; Nash, Robert S; Paskov, Kelley M; Skrzypek, Marek S; Weng, Shuai; Wong, Edith D; Cherry, J Michael

2016-01-04

The Saccharomyces Genome Database (SGD; http://www.yeastgenome.org) is the authoritative community resource for the Saccharomyces cerevisiae reference genome sequence and its annotation. In recent years, we have moved toward increased representation of sequence variation and allelic differences within S. cerevisiae. The publication of numerous additional genomes has motivated the creation of new tools for their annotation and analysis. Here we present the Variant Viewer: a dynamic open-source web application for the visualization of genomic and proteomic differences. Multiple sequence alignments have been constructed across high quality genome sequences from 11 different S. cerevisiae strains and stored in the SGD. The alignments and summaries are encoded in JSON and used to create a two-tiered dynamic view of the budding yeast pan-genome, available at http://www.yeastgenome.org/variant-viewer. © The Author(s) 2015. Published by Oxford University Press on behalf of Nucleic Acids Research.

A New Approach to Dissect Nuclear Organization: TALE-Mediated Genome Visualization (TGV).

PubMed

Miyanari, Yusuke

2016-01-01

Spatiotemporal organization of chromatin within the nucleus has so far remained elusive. Live visualization of nuclear remodeling could be a promising approach to understand its functional relevance in genome functions and mechanisms regulating genome architecture. Recent technological advances in live imaging of chromosomes begun to explore the biological roles of the movement of the chromatin within the nucleus. Here I describe a new technique, called TALE-mediated genome visualization (TGV), which allows us to visualize endogenous repetitive sequence including centromeric, pericentromeric, and telomeric repeats in living cells.

Visualization for genomics: the Microbial Genome Viewer.

PubMed

Kerkhoven, Robert; van Enckevort, Frank H J; Boekhorst, Jos; Molenaar, Douwe; Siezen, Roland J

2004-07-22

A Web-based visualization tool, the Microbial Genome Viewer, is presented that allows the user to combine complex genomic data in a highly interactive way. This Web tool enables the interactive generation of chromosome wheels and linear genome maps from genome annotation data stored in a MySQL database. The generated images are in scalable vector graphics (SVG) format, which is suitable for creating high-quality scalable images and dynamic Web representations. Gene-related data such as transcriptome and time-course microarray experiments can be superimposed on the maps for visual inspection. The Microbial Genome Viewer 1.0 is freely available at http://www.cmbi.kun.nl/MGV

Analysis and Visualization of ChIP-Seq and RNA-Seq Sequence Alignments Using ngs.plot.

PubMed

Loh, Yong-Hwee Eddie; Shen, Li

2016-01-01

The continual maturation and increasing applications of next-generation sequencing technology in scientific research have yielded ever-increasing amounts of data that need to be effectively and efficiently analyzed and innovatively mined for new biological insights. We have developed ngs.plot-a quick and easy-to-use bioinformatics tool that performs visualizations of the spatial relationships between sequencing alignment enrichment and specific genomic features or regions. More importantly, ngs.plot is customizable beyond the use of standard genomic feature databases to allow the analysis and visualization of user-specified regions of interest generated by the user's own hypotheses. In this protocol, we demonstrate and explain the use of ngs.plot using command line executions, as well as a web-based workflow on the Galaxy framework. We replicate the underlying commands used in the analysis of a true biological dataset that we had reported and published earlier and demonstrate how ngs.plot can easily generate publication-ready figures. With ngs.plot, users would be able to efficiently and innovatively mine their own datasets without having to be involved in the technical aspects of sequence coverage calculations and genomic databases.

Integration and visualization of systems biology data in context of the genome

PubMed Central

2010-01-01

Background High-density tiling arrays and new sequencing technologies are generating rapidly increasing volumes of transcriptome and protein-DNA interaction data. Visualization and exploration of this data is critical to understanding the regulatory logic encoded in the genome by which the cell dynamically affects its physiology and interacts with its environment. Results The Gaggle Genome Browser is a cross-platform desktop program for interactively visualizing high-throughput data in the context of the genome. Important features include dynamic panning and zooming, keyword search and open interoperability through the Gaggle framework. Users may bookmark locations on the genome with descriptive annotations and share these bookmarks with other users. The program handles large sets of user-generated data using an in-process database and leverages the facilities of SQL and the R environment for importing and manipulating data. A key aspect of the Gaggle Genome Browser is interoperability. By connecting to the Gaggle framework, the genome browser joins a suite of interconnected bioinformatics tools for analysis and visualization with connectivity to major public repositories of sequences, interactions and pathways. To this flexible environment for exploring and combining data, the Gaggle Genome Browser adds the ability to visualize diverse types of data in relation to its coordinates on the genome. Conclusions Genomic coordinates function as a common key by which disparate biological data types can be related to one another. In the Gaggle Genome Browser, heterogeneous data are joined by their location on the genome to create information-rich visualizations yielding insight into genome organization, transcription and its regulation and, ultimately, a better understanding of the mechanisms that enable the cell to dynamically respond to its environment. PMID:20642854

Theories of Visual Rhetoric: Looking at the Human Genome.

ERIC Educational Resources Information Center

Rosner, Mary

2001-01-01

Considers how visuals are constructions that are products of a writer's interpretation with its own "power-laden agenda." Reviews the current approach taken by composition scholars, surveys richer interdisciplinary work on visuals, and (by using visuals connected with the Human Genome Project) models an analysis of visuals as rhetoric.…

QuIN: A Web Server for Querying and Visualizing Chromatin Interaction Networks

PubMed Central

Thibodeau, Asa; Márquez, Eladio J.; Luo, Oscar; Ruan, Yijun; Shin, Dong-Guk; Stitzel, Michael L.; Ucar, Duygu

2016-01-01

Recent studies of the human genome have indicated that regulatory elements (e.g. promoters and enhancers) at distal genomic locations can interact with each other via chromatin folding and affect gene expression levels. Genomic technologies for mapping interactions between DNA regions, e.g., ChIA-PET and HiC, can generate genome-wide maps of interactions between regulatory elements. These interaction datasets are important resources to infer distal gene targets of non-coding regulatory elements and to facilitate prioritization of critical loci for important cellular functions. With the increasing diversity and complexity of genomic information and public ontologies, making sense of these datasets demands integrative and easy-to-use software tools. Moreover, network representation of chromatin interaction maps enables effective data visualization, integration, and mining. Currently, there is no software that can take full advantage of network theory approaches for the analysis of chromatin interaction datasets. To fill this gap, we developed a web-based application, QuIN, which enables: 1) building and visualizing chromatin interaction networks, 2) annotating networks with user-provided private and publicly available functional genomics and interaction datasets, 3) querying network components based on gene name or chromosome location, and 4) utilizing network based measures to identify and prioritize critical regulatory targets and their direct and indirect interactions. AVAILABILITY: QuIN’s web server is available at http://quin.jax.org QuIN is developed in Java and JavaScript, utilizing an Apache Tomcat web server and MySQL database and the source code is available under the GPLV3 license available on GitHub: https://github.com/UcarLab/QuIN/. PMID:27336171

VESPA: Software to Facilitate Genomic Annotation of Prokaryotic Organisms Through Integration of Proteomic and Transcriptomic Data

DOE Office of Scientific and Technical Information (OSTI.GOV)

Peterson, Elena S.; McCue, Lee Ann; Rutledge, Alexandra C.

2012-04-25

Visual Exploration and Statistics to Promote Annotation (VESPA) is an interactive visual analysis software tool that facilitates the discovery of structural mis-annotations in prokaryotic genomes. VESPA integrates high-throughput peptide-centric proteomics data and oligo-centric or RNA-Seq transcriptomics data into a genomic context. The data may be interrogated via visual analysis across multiple levels of genomic resolution, linked searches, exports and interaction with BLAST to rapidly identify location of interest within the genome and evaluate potential mis-annotations.

The Gene Expression Omnibus Database.

PubMed

Clough, Emily; Barrett, Tanya

2016-01-01

The Gene Expression Omnibus (GEO) database is an international public repository that archives and freely distributes high-throughput gene expression and other functional genomics data sets. Created in 2000 as a worldwide resource for gene expression studies, GEO has evolved with rapidly changing technologies and now accepts high-throughput data for many other data applications, including those that examine genome methylation, chromatin structure, and genome-protein interactions. GEO supports community-derived reporting standards that specify provision of several critical study elements including raw data, processed data, and descriptive metadata. The database not only provides access to data for tens of thousands of studies, but also offers various Web-based tools and strategies that enable users to locate data relevant to their specific interests, as well as to visualize and analyze the data. This chapter includes detailed descriptions of methods to query and download GEO data and use the analysis and visualization tools. The GEO homepage is at http://www.ncbi.nlm.nih.gov/geo/.

Integrative Genomics Viewer (IGV): high-performance genomics data visualization and exploration

PubMed Central

Thorvaldsdóttir, Helga; Mesirov, Jill P.

2013-01-01

Data visualization is an essential component of genomic data analysis. However, the size and diversity of the data sets produced by today’s sequencing and array-based profiling methods present major challenges to visualization tools. The Integrative Genomics Viewer (IGV) is a high-performance viewer that efficiently handles large heterogeneous data sets, while providing a smooth and intuitive user experience at all levels of genome resolution. A key characteristic of IGV is its focus on the integrative nature of genomic studies, with support for both array-based and next-generation sequencing data, and the integration of clinical and phenotypic data. Although IGV is often used to view genomic data from public sources, its primary emphasis is to support researchers who wish to visualize and explore their own data sets or those from colleagues. To that end, IGV supports flexible loading of local and remote data sets, and is optimized to provide high-performance data visualization and exploration on standard desktop systems. IGV is freely available for download from http://www.broadinstitute.org/igv, under a GNU LGPL open-source license. PMID:22517427

Integrative Genomics Viewer (IGV): high-performance genomics data visualization and exploration.

PubMed

Thorvaldsdóttir, Helga; Robinson, James T; Mesirov, Jill P

2013-03-01

Data visualization is an essential component of genomic data analysis. However, the size and diversity of the data sets produced by today's sequencing and array-based profiling methods present major challenges to visualization tools. The Integrative Genomics Viewer (IGV) is a high-performance viewer that efficiently handles large heterogeneous data sets, while providing a smooth and intuitive user experience at all levels of genome resolution. A key characteristic of IGV is its focus on the integrative nature of genomic studies, with support for both array-based and next-generation sequencing data, and the integration of clinical and phenotypic data. Although IGV is often used to view genomic data from public sources, its primary emphasis is to support researchers who wish to visualize and explore their own data sets or those from colleagues. To that end, IGV supports flexible loading of local and remote data sets, and is optimized to provide high-performance data visualization and exploration on standard desktop systems. IGV is freely available for download from http://www.broadinstitute.org/igv, under a GNU LGPL open-source license.

Delta: a new web-based 3D genome visualization and analysis platform.

PubMed

Tang, Bixia; Li, Feifei; Li, Jing; Zhao, Wenming; Zhang, Zhihua

2018-04-15

Delta is an integrative visualization and analysis platform to facilitate visually annotating and exploring the 3D physical architecture of genomes. Delta takes Hi-C or ChIA-PET contact matrix as input and predicts the topologically associating domains and chromatin loops in the genome. It then generates a physical 3D model which represents the plausible consensus 3D structure of the genome. Delta features a highly interactive visualization tool which enhances the integration of genome topology/physical structure with extensive genome annotation by juxtaposing the 3D model with diverse genomic assay outputs. Finally, by visually comparing the 3D model of the β-globin gene locus and its annotation, we speculated a plausible transitory interaction pattern in the locus. Experimental evidence was found to support this speculation by literature survey. This served as an example of intuitive hypothesis testing with the help of Delta. Delta is freely accessible from http://delta.big.ac.cn, and the source code is available at https://github.com/zhangzhwlab/delta. zhangzhihua@big.ac.cn. Supplementary data are available at Bioinformatics online.

3DScapeCS: application of three dimensional, parallel, dynamic network visualization in Cytoscape

PubMed Central

2013-01-01

Background The exponential growth of gigantic biological data from various sources, such as protein-protein interaction (PPI), genome sequences scaffolding, Mass spectrometry (MS) molecular networking and metabolic flux, demands an efficient way for better visualization and interpretation beyond the conventional, two-dimensional visualization tools. Results We developed a 3D Cytoscape Client/Server (3DScapeCS) plugin, which adopted Cytoscape in interpreting different types of data, and UbiGraph for three-dimensional visualization. The extra dimension is useful in accommodating, visualizing, and distinguishing large-scale networks with multiple crossed connections in five case studies. Conclusions Evaluation on several experimental data using 3DScapeCS and its special features, including multilevel graph layout, time-course data animation, and parallel visualization has proven its usefulness in visualizing complex data and help to make insightful conclusions. PMID:24225050

Dynamix: dynamic visualization by automatic selection of informative tracks from hundreds of genomic datasets.

PubMed

Monfort, Matthias; Furlong, Eileen E M; Girardot, Charles

2017-07-15

Visualization of genomic data is fundamental for gaining insights into genome function. Yet, co-visualization of a large number of datasets remains a challenge in all popular genome browsers and the development of new visualization methods is needed to improve the usability and user experience of genome browsers. We present Dynamix, a JBrowse plugin that enables the parallel inspection of hundreds of genomic datasets. Dynamix takes advantage of a priori knowledge to automatically display data tracks with signal within a genomic region of interest. As the user navigates through the genome, Dynamix automatically updates data tracks and limits all manual operations otherwise needed to adjust the data visible on screen. Dynamix also introduces a new carousel view that optimizes screen utilization by enabling users to independently scroll through groups of tracks. Dynamix is hosted at http://furlonglab.embl.de/Dynamix . charles.girardot@embl.de. Supplementary data are available at Bioinformatics online. © The Author(s) 2017. Published by Oxford University Press.

MaGnET: Malaria Genome Exploration Tool.

PubMed

Sharman, Joanna L; Gerloff, Dietlind L

2013-09-15

The Malaria Genome Exploration Tool (MaGnET) is a software tool enabling intuitive 'exploration-style' visualization of functional genomics data relating to the malaria parasite, Plasmodium falciparum. MaGnET provides innovative integrated graphic displays for different datasets, including genomic location of genes, mRNA expression data, protein-protein interactions and more. Any selection of genes to explore made by the user is easily carried over between the different viewers for different datasets, and can be changed interactively at any point (without returning to a search). Free online use (Java Web Start) or download (Java application archive and MySQL database; requires local MySQL installation) at http://malariagenomeexplorer.org joanna.sharman@ed.ac.uk or dgerloff@ffame.org Supplementary data are available at Bioinformatics online.

CpGAVAS, an integrated web server for the annotation, visualization, analysis, and GenBank submission of completely sequenced chloroplast genome sequences

PubMed Central

2012-01-01

Background The complete sequences of chloroplast genomes provide wealthy information regarding the evolutionary history of species. With the advance of next-generation sequencing technology, the number of completely sequenced chloroplast genomes is expected to increase exponentially, powerful computational tools annotating the genome sequences are in urgent need. Results We have developed a web server CPGAVAS. The server accepts a complete chloroplast genome sequence as input. First, it predicts protein-coding and rRNA genes based on the identification and mapping of the most similar, full-length protein, cDNA and rRNA sequences by integrating results from Blastx, Blastn, protein2genome and est2genome programs. Second, tRNA genes and inverted repeats (IR) are identified using tRNAscan, ARAGORN and vmatch respectively. Third, it calculates the summary statistics for the annotated genome. Fourth, it generates a circular map ready for publication. Fifth, it can create a Sequin file for GenBank submission. Last, it allows the extractions of protein and mRNA sequences for given list of genes and species. The annotation results in GFF3 format can be edited using any compatible annotation editing tools. The edited annotations can then be uploaded to CPGAVAS for update and re-analyses repeatedly. Using known chloroplast genome sequences as test set, we show that CPGAVAS performs comparably to another application DOGMA, while having several superior functionalities. Conclusions CPGAVAS allows the semi-automatic and complete annotation of a chloroplast genome sequence, and the visualization, editing and analysis of the annotation results. It will become an indispensible tool for researchers studying chloroplast genomes. The software is freely accessible from http://www.herbalgenomics.org/cpgavas. PMID:23256920

Genomic Enzymology: Web Tools for Leveraging Protein Family Sequence-Function Space and Genome Context to Discover Novel Functions.

PubMed

Gerlt, John A

2017-08-22

The exponentially increasing number of protein and nucleic acid sequences provides opportunities to discover novel enzymes, metabolic pathways, and metabolites/natural products, thereby adding to our knowledge of biochemistry and biology. The challenge has evolved from generating sequence information to mining the databases to integrating and leveraging the available information, i.e., the availability of "genomic enzymology" web tools. Web tools that allow identification of biosynthetic gene clusters are widely used by the natural products/synthetic biology community, thereby facilitating the discovery of novel natural products and the enzymes responsible for their biosynthesis. However, many novel enzymes with interesting mechanisms participate in uncharacterized small-molecule metabolic pathways; their discovery and functional characterization also can be accomplished by leveraging information in protein and nucleic acid databases. This Perspective focuses on two genomic enzymology web tools that assist the discovery novel metabolic pathways: (1) Enzyme Function Initiative-Enzyme Similarity Tool (EFI-EST) for generating sequence similarity networks to visualize and analyze sequence-function space in protein families and (2) Enzyme Function Initiative-Genome Neighborhood Tool (EFI-GNT) for generating genome neighborhood networks to visualize and analyze the genome context in microbial and fungal genomes. Both tools have been adapted to other applications to facilitate target selection for enzyme discovery and functional characterization. As the natural products community has demonstrated, the enzymology community needs to embrace the essential role of web tools that allow the protein and genome sequence databases to be leveraged for novel insights into enzymological problems.

Genomic Enzymology: Web Tools for Leveraging Protein Family Sequence–Function Space and Genome Context to Discover Novel Functions

PubMed Central

2017-01-01

The exponentially increasing number of protein and nucleic acid sequences provides opportunities to discover novel enzymes, metabolic pathways, and metabolites/natural products, thereby adding to our knowledge of biochemistry and biology. The challenge has evolved from generating sequence information to mining the databases to integrating and leveraging the available information, i.e., the availability of “genomic enzymology” web tools. Web tools that allow identification of biosynthetic gene clusters are widely used by the natural products/synthetic biology community, thereby facilitating the discovery of novel natural products and the enzymes responsible for their biosynthesis. However, many novel enzymes with interesting mechanisms participate in uncharacterized small-molecule metabolic pathways; their discovery and functional characterization also can be accomplished by leveraging information in protein and nucleic acid databases. This Perspective focuses on two genomic enzymology web tools that assist the discovery novel metabolic pathways: (1) Enzyme Function Initiative-Enzyme Similarity Tool (EFI-EST) for generating sequence similarity networks to visualize and analyze sequence–function space in protein families and (2) Enzyme Function Initiative-Genome Neighborhood Tool (EFI-GNT) for generating genome neighborhood networks to visualize and analyze the genome context in microbial and fungal genomes. Both tools have been adapted to other applications to facilitate target selection for enzyme discovery and functional characterization. As the natural products community has demonstrated, the enzymology community needs to embrace the essential role of web tools that allow the protein and genome sequence databases to be leveraged for novel insights into enzymological problems. PMID:28826221

MIPS Arabidopsis thaliana Database (MAtDB): an integrated biological knowledge resource for plant genomics

PubMed Central

Schoof, Heiko; Ernst, Rebecca; Nazarov, Vladimir; Pfeifer, Lukas; Mewes, Hans-Werner; Mayer, Klaus F. X.

2004-01-01

Arabidopsis thaliana is the most widely studied model plant. Functional genomics is intensively underway in many laboratories worldwide. Beyond the basic annotation of the primary sequence data, the annotated genetic elements of Arabidopsis must be linked to diverse biological data and higher order information such as metabolic or regulatory pathways. The MIPS Arabidopsis thaliana database MAtDB aims to provide a comprehensive resource for Arabidopsis as a genome model that serves as a primary reference for research in plants and is suitable for transfer of knowledge to other plants, especially crops. The genome sequence as a common backbone serves as a scaffold for the integration of data, while, in a complementary effort, these data are enhanced through the application of state-of-the-art bioinformatics tools. This information is visualized on a genome-wide and a gene-by-gene basis with access both for web users and applications. This report updates the information given in a previous report and provides an outlook on further developments. The MAtDB web interface can be accessed at http://mips.gsf.de/proj/thal/db. PMID:14681437

Decoding the Heart through Next Generation Sequencing Approaches.

PubMed

Pawlak, Michal; Niescierowicz, Katarzyna; Winata, Cecilia Lanny

2018-06-07

: Vertebrate organs develop through a complex process which involves interaction between multiple signaling pathways at the molecular, cell, and tissue levels. Heart development is an example of such complex process which, when disrupted, results in congenital heart disease (CHD). This complexity necessitates a holistic approach which allows the visualization of genome-wide interaction networks, as opposed to assessment of limited subsets of factors. Genomics offers a powerful solution to address the problem of biological complexity by enabling the observation of molecular processes at a genome-wide scale. The emergence of next generation sequencing (NGS) technology has facilitated the expansion of genomics, increasing its output capacity and applicability in various biological disciplines. The application of NGS in various aspects of heart biology has resulted in new discoveries, generating novel insights into this field of study. Here we review the contributions of NGS technology into the understanding of heart development and its disruption reflected in CHD and discuss how emerging NGS based methodologies can contribute to the further understanding of heart repair.

Haplotag: Software for Haplotype-Based Genotyping-by-Sequencing Analysis

PubMed Central

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

FISH Oracle 2: a web server for integrative visualization of genomic data in cancer research.

PubMed

Mader, Malte; Simon, Ronald; Kurtz, Stefan

2014-03-31

A comprehensive view on all relevant genomic data is instrumental for understanding the complex patterns of molecular alterations typically found in cancer cells. One of the most effective ways to rapidly obtain an overview of genomic alterations in large amounts of genomic data is the integrative visualization of genomic events. We developed FISH Oracle 2, a web server for the interactive visualization of different kinds of downstream processed genomics data typically available in cancer research. A powerful search interface and a fast visualization engine provide a highly interactive visualization for such data. High quality image export enables the life scientist to easily communicate their results. A comprehensive data administration allows to keep track of the available data sets. We applied FISH Oracle 2 to published data and found evidence that, in colorectal cancer cells, the gene TTC28 may be inactivated in two different ways, a fact that has not been published before. The interactive nature of FISH Oracle 2 and the possibility to store, select and visualize large amounts of downstream processed data support life scientists in generating hypotheses. The export of high quality images supports explanatory data visualization, simplifying the communication of new biological findings. A FISH Oracle 2 demo server and the software is available at http://www.zbh.uni-hamburg.de/fishoracle.

CircosVCF: circos visualization of whole-genome sequence variations stored in VCF files.

PubMed

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

Visualizing conserved gene location across microbe genomes

NASA Astrophysics Data System (ADS)

Shaw, Chris D.

2009-01-01

This paper introduces an analysis-based zoomable visualization technique for displaying the location of genes across many related species of microbes. The purpose of this visualizatiuon is to enable a biologist to examine the layout of genes in the organism of interest with respect to the gene organization of related organisms. During the genomic annotation process, the ability to observe gene organization in common with previously annotated genomes can help a biologist better confirm the structure and function of newly analyzed microbe DNA sequences. We have developed a visualization and analysis tool that enables the biologist to observe and examine gene organization among genomes, in the context of the primary sequence of interest. This paper describes the visualization and analysis steps, and presents a case study using a number of Rickettsia genomes.

A low-latency, big database system and browser for storage, querying and visualization of 3D genomic data.

PubMed

Butyaev, Alexander; Mavlyutov, Ruslan; Blanchette, Mathieu; Cudré-Mauroux, Philippe; Waldispühl, Jérôme

2015-09-18

Recent releases of genome three-dimensional (3D) structures have the potential to transform our understanding of genomes. Nonetheless, the storage technology and visualization tools need to evolve to offer to the scientific community fast and convenient access to these data. We introduce simultaneously a database system to store and query 3D genomic data (3DBG), and a 3D genome browser to visualize and explore 3D genome structures (3DGB). We benchmark 3DBG against state-of-the-art systems and demonstrate that it is faster than previous solutions, and importantly gracefully scales with the size of data. We also illustrate the usefulness of our 3D genome Web browser to explore human genome structures. The 3D genome browser is available at http://3dgb.cs.mcgill.ca/. © The Author(s) 2015. Published by Oxford University Press on behalf of Nucleic Acids Research.

A low-latency, big database system and browser for storage, querying and visualization of 3D genomic data

PubMed Central

Butyaev, Alexander; Mavlyutov, Ruslan; Blanchette, Mathieu; Cudré-Mauroux, Philippe; Waldispühl, Jérôme

2015-01-01

Recent releases of genome three-dimensional (3D) structures have the potential to transform our understanding of genomes. Nonetheless, the storage technology and visualization tools need to evolve to offer to the scientific community fast and convenient access to these data. We introduce simultaneously a database system to store and query 3D genomic data (3DBG), and a 3D genome browser to visualize and explore 3D genome structures (3DGB). We benchmark 3DBG against state-of-the-art systems and demonstrate that it is faster than previous solutions, and importantly gracefully scales with the size of data. We also illustrate the usefulness of our 3D genome Web browser to explore human genome structures. The 3D genome browser is available at http://3dgb.cs.mcgill.ca/. PMID:25990738

CRAVE: a database, middleware and visualization system for phenotype ontologies.

PubMed

Gkoutos, Georgios V; Green, Eain C J; Greenaway, Simon; Blake, Andrew; Mallon, Ann-Marie; Hancock, John M

2005-04-01

A major challenge in modern biology is to link genome sequence information to organismal function. In many organisms this is being done by characterizing phenotypes resulting from mutations. Efficiently expressing phenotypic information requires combinatorial use of ontologies. However tools are not currently available to visualize combinations of ontologies. Here we describe CRAVE (Concept Relation Assay Value Explorer), a package allowing storage, active updating and visualization of multiple ontologies. CRAVE is a web-accessible JAVA application that accesses an underlying MySQL database of ontologies via a JAVA persistent middleware layer (Chameleon). This maps the database tables into discrete JAVA classes and creates memory resident, interlinked objects corresponding to the ontology data. These JAVA objects are accessed via calls through the middleware's application programming interface. CRAVE allows simultaneous display and linking of multiple ontologies and searching using Boolean and advanced searches.

The Harvest suite for rapid core-genome alignment and visualization of thousands of intraspecific microbial genomes.

PubMed

Treangen, Todd J; Ondov, Brian D; Koren, Sergey; Phillippy, Adam M

2014-01-01

Whole-genome sequences are now available for many microbial species and clades, however existing whole-genome alignment methods are limited in their ability to perform sequence comparisons of multiple sequences simultaneously. Here we present the Harvest suite of core-genome alignment and visualization tools for the rapid and simultaneous analysis of thousands of intraspecific microbial strains. Harvest includes Parsnp, a fast core-genome multi-aligner, and Gingr, a dynamic visual platform. Together they provide interactive core-genome alignments, variant calls, recombination detection, and phylogenetic trees. Using simulated and real data we demonstrate that our approach exhibits unrivaled speed while maintaining the accuracy of existing methods. The Harvest suite is open-source and freely available from: http://github.com/marbl/harvest.

Live visualization of genomic loci with BiFC-TALE

PubMed Central

Hu, Huan; Zhang, Hongmin; Wang, Sheng; Ding, Miao; An, Hui; Hou, Yingping; Yang, Xiaojing; Wei, Wensheng; Sun, Yujie; Tang, Chao

2017-01-01

Tracking the dynamics of genomic loci is important for understanding the mechanisms of fundamental intracellular processes. However, fluorescent labeling and imaging of such loci in live cells have been challenging. One of the major reasons is the low signal-to-background ratio (SBR) of images mainly caused by the background fluorescence from diffuse full-length fluorescent proteins (FPs) in the living nucleus, hampering the application of live cell genomic labeling methods. Here, combining bimolecular fluorescence complementation (BiFC) and transcription activator-like effector (TALE) technologies, we developed a novel method for labeling genomic loci (BiFC-TALE), which largely reduces the background fluorescence level. Using BiFC-TALE, we demonstrated a significantly improved SBR by imaging telomeres and centromeres in living cells in comparison with the methods using full-length FP. PMID:28074901

Live visualization of genomic loci with BiFC-TALE.

PubMed

Hu, Huan; Zhang, Hongmin; Wang, Sheng; Ding, Miao; An, Hui; Hou, Yingping; Yang, Xiaojing; Wei, Wensheng; Sun, Yujie; Tang, Chao

2017-01-11

Tracking the dynamics of genomic loci is important for understanding the mechanisms of fundamental intracellular processes. However, fluorescent labeling and imaging of such loci in live cells have been challenging. One of the major reasons is the low signal-to-background ratio (SBR) of images mainly caused by the background fluorescence from diffuse full-length fluorescent proteins (FPs) in the living nucleus, hampering the application of live cell genomic labeling methods. Here, combining bimolecular fluorescence complementation (BiFC) and transcription activator-like effector (TALE) technologies, we developed a novel method for labeling genomic loci (BiFC-TALE), which largely reduces the background fluorescence level. Using BiFC-TALE, we demonstrated a significantly improved SBR by imaging telomeres and centromeres in living cells in comparison with the methods using full-length FP.

FISH Oracle 2: a web server for integrative visualization of genomic data in cancer research

PubMed Central

2014-01-01

Background A comprehensive view on all relevant genomic data is instrumental for understanding the complex patterns of molecular alterations typically found in cancer cells. One of the most effective ways to rapidly obtain an overview of genomic alterations in large amounts of genomic data is the integrative visualization of genomic events. Results We developed FISH Oracle 2, a web server for the interactive visualization of different kinds of downstream processed genomics data typically available in cancer research. A powerful search interface and a fast visualization engine provide a highly interactive visualization for such data. High quality image export enables the life scientist to easily communicate their results. A comprehensive data administration allows to keep track of the available data sets. We applied FISH Oracle 2 to published data and found evidence that, in colorectal cancer cells, the gene TTC28 may be inactivated in two different ways, a fact that has not been published before. Conclusions The interactive nature of FISH Oracle 2 and the possibility to store, select and visualize large amounts of downstream processed data support life scientists in generating hypotheses. The export of high quality images supports explanatory data visualization, simplifying the communication of new biological findings. A FISH Oracle 2 demo server and the software is available at http://www.zbh.uni-hamburg.de/fishoracle. PMID:24684958

ColorTree: a batch customization tool for phylogenic trees

PubMed Central

Chen, Wei-Hua; Lercher, Martin J

2009-01-01

Background Genome sequencing projects and comparative genomics studies typically aim to trace the evolutionary history of large gene sets, often requiring human inspection of hundreds of phylogenetic trees. If trees are checked for compatibility with an explicit null hypothesis (e.g., the monophyly of certain groups), this daunting task is greatly facilitated by an appropriate coloring scheme. Findings In this note, we introduce ColorTree, a simple yet powerful batch customization tool for phylogenic trees. Based on pattern matching rules, ColorTree applies a set of customizations to an input tree file, e.g., coloring labels or branches. The customized trees are saved to an output file, which can then be viewed and further edited by Dendroscope (a freely available tree viewer). ColorTree runs on any Perl installation as a stand-alone command line tool, and its application can thus be easily automated. This way, hundreds of phylogenic trees can be customized for easy visual inspection in a matter of minutes. Conclusion ColorTree allows efficient and flexible visual customization of large tree sets through the application of a user-supplied configuration file to multiple tree files. PMID:19646243

ColorTree: a batch customization tool for phylogenic trees.

PubMed

Chen, Wei-Hua; Lercher, Martin J

2009-07-31

Genome sequencing projects and comparative genomics studies typically aim to trace the evolutionary history of large gene sets, often requiring human inspection of hundreds of phylogenetic trees. If trees are checked for compatibility with an explicit null hypothesis (e.g., the monophyly of certain groups), this daunting task is greatly facilitated by an appropriate coloring scheme. In this note, we introduce ColorTree, a simple yet powerful batch customization tool for phylogenic trees. Based on pattern matching rules, ColorTree applies a set of customizations to an input tree file, e.g., coloring labels or branches. The customized trees are saved to an output file, which can then be viewed and further edited by Dendroscope (a freely available tree viewer). ColorTree runs on any Perl installation as a stand-alone command line tool, and its application can thus be easily automated. This way, hundreds of phylogenic trees can be customized for easy visual inspection in a matter of minutes. ColorTree allows efficient and flexible visual customization of large tree sets through the application of a user-supplied configuration file to multiple tree files.

BioQ: tracing experimental origins in public genomic databases using a novel data provenance model.

PubMed

Saccone, Scott F; Quan, Jiaxi; Jones, Peter L

2012-04-15

Public genomic databases, which are often used to guide genetic studies of human disease, are now being applied to genomic medicine through in silico integrative genomics. These databases, however, often lack tools for systematically determining the experimental origins of the data. We introduce a new data provenance model that we have implemented in a public web application, BioQ, for assessing the reliability of the data by systematically tracing its experimental origins to the original subjects and biologics. BioQ allows investigators to both visualize data provenance as well as explore individual elements of experimental process flow using precise tools for detailed data exploration and documentation. It includes a number of human genetic variation databases such as the HapMap and 1000 Genomes projects. BioQ is freely available to the public at http://bioq.saclab.net.

CAMBerVis: visualization software to support comparative analysis of multiple bacterial strains.

PubMed

Woźniak, Michał; Wong, Limsoon; Tiuryn, Jerzy

2011-12-01

A number of inconsistencies in genome annotations are documented among bacterial strains. Visualization of the differences may help biologists to make correct decisions in spurious cases. We have developed a visualization tool, CAMBerVis, to support comparative analysis of multiple bacterial strains. The software manages simultaneous visualization of multiple bacterial genomes, enabling visual analysis focused on genome structure annotations. The CAMBerVis software is freely available at the project website: http://bioputer.mimuw.edu.pl/camber. Input datasets for Mycobacterium tuberculosis and Staphylocacus aureus are integrated with the software as examples. m.wozniak@mimuw.edu.pl Supplementary data are available at Bioinformatics online.

Natural language processing and visualization in the molecular imaging domain.

PubMed

Tulipano, P Karina; Tao, Ying; Millar, William S; Zanzonico, Pat; Kolbert, Katherine; Xu, Hua; Yu, Hong; Chen, Lifeng; Lussier, Yves A; Friedman, Carol

2007-06-01

Molecular imaging is at the crossroads of genomic sciences and medical imaging. Information within the molecular imaging literature could be used to link to genomic and imaging information resources and to organize and index images in a way that is potentially useful to researchers. A number of natural language processing (NLP) systems are available to automatically extract information from genomic literature. One existing NLP system, known as BioMedLEE, automatically extracts biological information consisting of biomolecular substances and phenotypic data. This paper focuses on the adaptation, evaluation, and application of BioMedLEE to the molecular imaging domain. In order to adapt BioMedLEE for this domain, we extend an existing molecular imaging terminology and incorporate it into BioMedLEE. BioMedLEE's performance is assessed with a formal evaluation study. The system's performance, measured as recall and precision, is 0.74 (95% CI: [.70-.76]) and 0.70 (95% CI [.63-.76]), respectively. We adapt a JAVA viewer known as PGviewer for the simultaneous visualization of images with NLP extracted information.

GenColors-based comparative genome databases for small eukaryotic genomes.

PubMed

Felder, Marius; Romualdi, Alessandro; Petzold, Andreas; Platzer, Matthias; Sühnel, Jürgen; Glöckner, Gernot

2013-01-01

Many sequence data repositories can give a quick and easily accessible overview on genomes and their annotations. Less widespread is the possibility to compare related genomes with each other in a common database environment. We have previously described the GenColors database system (http://gencolors.fli-leibniz.de) and its applications to a number of bacterial genomes such as Borrelia, Legionella, Leptospira and Treponema. This system has an emphasis on genome comparison. It combines data from related genomes and provides the user with an extensive set of visualization and analysis tools. Eukaryote genomes are normally larger than prokaryote genomes and thus pose additional challenges for such a system. We have, therefore, adapted GenColors to also handle larger datasets of small eukaryotic genomes and to display eukaryotic gene structures. Further recent developments include whole genome views, genome list options and, for bacterial genome browsers, the display of horizontal gene transfer predictions. Two new GenColors-based databases for two fungal species (http://fgb.fli-leibniz.de) and for four social amoebas (http://sacgb.fli-leibniz.de) were set up. Both new resources open up a single entry point for related genomes for the amoebozoa and fungal research communities and other interested users. Comparative genomics approaches are greatly facilitated by these resources.

Explorative visual analytics on interval-based genomic data and their metadata.

PubMed

Jalili, Vahid; Matteucci, Matteo; Masseroli, Marco; Ceri, Stefano

2017-12-04

With the wide-spreading of public repositories of NGS processed data, the availability of user-friendly and effective tools for data exploration, analysis and visualization is becoming very relevant. These tools enable interactive analytics, an exploratory approach for the seamless "sense-making" of data through on-the-fly integration of analysis and visualization phases, suggested not only for evaluating processing results, but also for designing and adapting NGS data analysis pipelines. This paper presents abstractions for supporting the early analysis of NGS processed data and their implementation in an associated tool, named GenoMetric Space Explorer (GeMSE). This tool serves the needs of the GenoMetric Query Language, an innovative cloud-based system for computing complex queries over heterogeneous processed data. It can also be used starting from any text files in standard BED, BroadPeak, NarrowPeak, GTF, or general tab-delimited format, containing numerical features of genomic regions; metadata can be provided as text files in tab-delimited attribute-value format. GeMSE allows interactive analytics, consisting of on-the-fly cycling among steps of data exploration, analysis and visualization that help biologists and bioinformaticians in making sense of heterogeneous genomic datasets. By means of an explorative interaction support, users can trace past activities and quickly recover their results, seamlessly going backward and forward in the analysis steps and comparative visualizations of heatmaps. GeMSE effective application and practical usefulness is demonstrated through significant use cases of biological interest. GeMSE is available at http://www.bioinformatics.deib.polimi.it/GeMSE/ , and its source code is available at https://github.com/Genometric/GeMSE under GPLv3 open-source license.

LOLAweb: a containerized web server for interactive genomic locus overlap enrichment analysis.

PubMed

Nagraj, V P; Magee, Neal E; Sheffield, Nathan C

2018-06-06

The past few years have seen an explosion of interest in understanding the role of regulatory DNA. This interest has driven large-scale production of functional genomics data and analytical methods. One popular analysis is to test for enrichment of overlaps between a query set of genomic regions and a database of region sets. In this way, new genomic data can be easily connected to annotations from external data sources. Here, we present an interactive interface for enrichment analysis of genomic locus overlaps using a web server called LOLAweb. LOLAweb accepts a set of genomic ranges from the user and tests it for enrichment against a database of region sets. LOLAweb renders results in an R Shiny application to provide interactive visualization features, enabling users to filter, sort, and explore enrichment results dynamically. LOLAweb is built and deployed in a Linux container, making it scalable to many concurrent users on our servers and also enabling users to download and run LOLAweb locally.

Visual Exploration of Genetic Association with Voxel-based Imaging Phenotypes in an MCI/AD Study

PubMed Central

Kim, Sungeun; Shen, Li; Saykin, Andrew J.; West, John D.

2010-01-01

Neuroimaging genomics is a new transdisciplinary research field, which aims to examine genetic effects on brain via integrated analyses of high throughput neuroimaging and genomic data. We report our recent work on (1) developing an imaging genomic browsing system that allows for whole genome and entire brain analyses based on visual exploration and (2) applying the system to the imaging genomic analysis of an existing MCI/AD cohort. Voxel-based morphometry is used to define imaging phenotypes. ANCOVA is employed to evaluate the effect of the interaction of genotypes and diagnosis in relation to imaging phenotypes while controlling for relevant covariates. Encouraging experimental results suggest that the proposed system has substantial potential for enabling discovery of imaging genomic associations through visual evaluation and for localizing candidate imaging regions and genomic regions for refined statistical modeling. PMID:19963597

MaGnET: Malaria Genome Exploration Tool

PubMed Central

Sharman, Joanna L.; Gerloff, Dietlind L.

2013-01-01

Summary: The Malaria Genome Exploration Tool (MaGnET) is a software tool enabling intuitive ‘exploration-style’ visualization of functional genomics data relating to the malaria parasite, Plasmodium falciparum. MaGnET provides innovative integrated graphic displays for different datasets, including genomic location of genes, mRNA expression data, protein–protein interactions and more. Any selection of genes to explore made by the user is easily carried over between the different viewers for different datasets, and can be changed interactively at any point (without returning to a search). Availability and Implementation: Free online use (Java Web Start) or download (Java application archive and MySQL database; requires local MySQL installation) at http://malariagenomeexplorer.org Contact: joanna.sharman@ed.ac.uk or dgerloff@ffame.org Supplementary information: Supplementary data are available at Bioinformatics online. PMID:23894142

SMART precision cancer medicine: a FHIR-based app to provide genomic information at the point of care.

PubMed

Warner, Jeremy L; Rioth, Matthew J; Mandl, Kenneth D; Mandel, Joshua C; Kreda, David A; Kohane, Isaac S; Carbone, Daniel; Oreto, Ross; Wang, Lucy; Zhu, Shilin; Yao, Heming; Alterovitz, Gil

2016-07-01

Precision cancer medicine (PCM) will require ready access to genomic data within the clinical workflow and tools to assist clinical interpretation and enable decisions. Since most electronic health record (EHR) systems do not yet provide such functionality, we developed an EHR-agnostic, clinico-genomic mobile app to demonstrate several features that will be needed for point-of-care conversations. Our prototype, called Substitutable Medical Applications and Reusable Technology (SMART)® PCM, visualizes genomic information in real time, comparing a patient's diagnosis-specific somatic gene mutations detected by PCR-based hotspot testing to a population-level set of comparable data. The initial prototype works for patient specimens with 0 or 1 detected mutation. Genomics extensions were created for the Health Level Seven® Fast Healthcare Interoperability Resources (FHIR)® standard; otherwise, the prototype is a normal SMART on FHIR app. The PCM prototype can rapidly present a visualization that compares a patient's somatic genomic alterations against a distribution built from more than 3000 patients, along with context-specific links to external knowledge bases. Initial evaluation by oncologists provided important feedback about the prototype's strengths and weaknesses. We added several requested enhancements and successfully demonstrated the app at the inaugural American Society of Clinical Oncology Interoperability Demonstration; we have also begun to expand visualization capabilities to include cancer specimens with multiple mutations. PCM is open-source software for clinicians to present the individual patient within the population-level spectrum of cancer somatic mutations. The app can be implemented on any SMART on FHIR-enabled EHRs, and future versions of PCM should be able to evolve in parallel with external knowledge bases. © The Author 2016. Published by Oxford University Press on behalf of the American Medical Informatics Association. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

Cloud Based Resource for Data Hosting, Visualization and Analysis Using UCSC Cancer Genomics Browser | Informatics Technology for Cancer Research (ITCR)

Cancer.gov

The Cancer Analysis Virtual Machine (CAVM) project will leverage cloud technology, the UCSC Cancer Genomics Browser, and the Galaxy analysis workflow system to provide investigators with a flexible, scalable platform for hosting, visualizing and analyzing their own genomic data.

GEnomes Management Application (GEM.app): a new software tool for large-scale collaborative genome analysis.

PubMed

Gonzalez, Michael A; Lebrigio, Rafael F Acosta; Van Booven, Derek; Ulloa, Rick H; Powell, Eric; Speziani, Fiorella; Tekin, Mustafa; Schüle, Rebecca; Züchner, Stephan

2013-06-01

Novel genes are now identified at a rapid pace for many Mendelian disorders, and increasingly, for genetically complex phenotypes. However, new challenges have also become evident: (1) effectively managing larger exome and/or genome datasets, especially for smaller labs; (2) direct hands-on analysis and contextual interpretation of variant data in large genomic datasets; and (3) many small and medium-sized clinical and research-based investigative teams around the world are generating data that, if combined and shared, will significantly increase the opportunities for the entire community to identify new genes. To address these challenges, we have developed GEnomes Management Application (GEM.app), a software tool to annotate, manage, visualize, and analyze large genomic datasets (https://genomics.med.miami.edu/). GEM.app currently contains ∼1,600 whole exomes from 50 different phenotypes studied by 40 principal investigators from 15 different countries. The focus of GEM.app is on user-friendly analysis for nonbioinformaticians to make next-generation sequencing data directly accessible. Yet, GEM.app provides powerful and flexible filter options, including single family filtering, across family/phenotype queries, nested filtering, and evaluation of segregation in families. In addition, the system is fast, obtaining results within 4 sec across ∼1,200 exomes. We believe that this system will further enhance identification of genetic causes of human disease. © 2013 Wiley Periodicals, Inc.

Alview: Portable Software for Viewing Sequence Reads in BAM Formatted Files.

PubMed

Finney, Richard P; Chen, Qing-Rong; Nguyen, Cu V; Hsu, Chih Hao; Yan, Chunhua; Hu, Ying; Abawi, Massih; Bian, Xiaopeng; Meerzaman, Daoud M

2015-01-01

The name Alview is a contraction of the term Alignment Viewer. Alview is a compiled to native architecture software tool for visualizing the alignment of sequencing data. Inputs are files of short-read sequences aligned to a reference genome in the SAM/BAM format and files containing reference genome data. Outputs are visualizations of these aligned short reads. Alview is written in portable C with optional graphical user interface (GUI) code written in C, C++, and Objective-C. The application can run in three different ways: as a web server, as a command line tool, or as a native, GUI program. Alview is compatible with Microsoft Windows, Linux, and Apple OS X. It is available as a web demo at https://cgwb.nci.nih.gov/cgi-bin/alview. The source code and Windows/Mac/Linux executables are available via https://github.com/NCIP/alview.

BGDMdocker: a Docker workflow for data mining and visualization of bacterial pan-genomes and biosynthetic gene clusters.

PubMed

Cheng, Gong; Lu, Quan; Ma, Ling; Zhang, Guocai; Xu, Liang; Zhou, Zongshan

2017-01-01

Recently, Docker technology has received increasing attention throughout the bioinformatics community. However, its implementation has not yet been mastered by most biologists; accordingly, its application in biological research has been limited. In order to popularize this technology in the field of bioinformatics and to promote the use of publicly available bioinformatics tools, such as Dockerfiles and Images from communities, government sources, and private owners in the Docker Hub Registry and other Docker-based resources, we introduce here a complete and accurate bioinformatics workflow based on Docker. The present workflow enables analysis and visualization of pan-genomes and biosynthetic gene clusters of bacteria. This provides a new solution for bioinformatics mining of big data from various publicly available biological databases. The present step-by-step guide creates an integrative workflow through a Dockerfile to allow researchers to build their own Image and run Container easily.

BGDMdocker: a Docker workflow for data mining and visualization of bacterial pan-genomes and biosynthetic gene clusters

PubMed Central

Cheng, Gong; Zhang, Guocai; Xu, Liang

2017-01-01

Recently, Docker technology has received increasing attention throughout the bioinformatics community. However, its implementation has not yet been mastered by most biologists; accordingly, its application in biological research has been limited. In order to popularize this technology in the field of bioinformatics and to promote the use of publicly available bioinformatics tools, such as Dockerfiles and Images from communities, government sources, and private owners in the Docker Hub Registry and other Docker-based resources, we introduce here a complete and accurate bioinformatics workflow based on Docker. The present workflow enables analysis and visualization of pan-genomes and biosynthetic gene clusters of bacteria. This provides a new solution for bioinformatics mining of big data from various publicly available biological databases. The present step-by-step guide creates an integrative workflow through a Dockerfile to allow researchers to build their own Image and run Container easily. PMID:29204317

CGDV: a webtool for circular visualization of genomics and transcriptomics data.

PubMed

Jha, Vineet; Singh, Gulzar; Kumar, Shiva; Sonawane, Amol; Jere, Abhay; Anamika, Krishanpal

2017-10-24

Interpretation of large-scale data is very challenging and currently there is scarcity of web tools which support automated visualization of a variety of high throughput genomics and transcriptomics data and for a wide variety of model organisms along with user defined karyotypes. Circular plot provides holistic visualization of high throughput large scale data but it is very complex and challenging to generate as most of the available tools need informatics expertise to install and run them. We have developed CGDV (Circos for Genomics and Transcriptomics Data Visualization), a webtool based on Circos, for seamless and automated visualization of a variety of large scale genomics and transcriptomics data. CGDV takes output of analyzed genomics or transcriptomics data of different formats, such as vcf, bed, xls, tab limited matrix text file, CNVnator raw output and Gene fusion raw output, to plot circular view of the sample data. CGDV take cares of generating intermediate files required for circos. CGDV is freely available at https://cgdv-upload.persistent.co.in/cgdv/ . The circular plot for each data type is tailored to gain best biological insights into the data. The inter-relationship between data points, homologous sequences, genes involved in fusion events, differential expression pattern, sequencing depth, types and size of variations and enrichment of DNA binding proteins can be seen using CGDV. CGDV thus helps biologists and bioinformaticians to visualize a variety of genomics and transcriptomics data seamlessly.

PanACEA: a bioinformatics tool for the exploration and visualization of bacterial pan-chromosomes.

PubMed

Clarke, Thomas H; Brinkac, Lauren M; Inman, Jason M; Sutton, Granger; Fouts, Derrick E

2018-06-27

Bacterial pan-genomes, comprised of conserved and variable genes across multiple sequenced bacterial genomes, allow for identification of genomic regions that are phylogenetically discriminating or functionally important. Pan-genomes consist of large amounts of data, which can restrict researchers ability to locate and analyze these regions. Multiple software packages are available to visualize pan-genomes, but currently their ability to address these concerns are limited by using only pre-computed data sets, prioritizing core over variable gene clusters, or by not accounting for pan-chromosome positioning in the viewer. We introduce PanACEA (Pan-genome Atlas with Chromosome Explorer and Analyzer), which utilizes locally-computed interactive web-pages to view ordered pan-genome data. It consists of multi-tiered, hierarchical display pages that extend from pan-chromosomes to both core and variable regions to single genes. Regions and genes are functionally annotated to allow for rapid searching and visual identification of regions of interest with the option that user-supplied genomic phylogenies and metadata can be incorporated. PanACEA's memory and time requirements are within the capacities of standard laptops. The capability of PanACEA as a research tool is demonstrated by highlighting a variable region important in differentiating strains of Enterobacter hormaechei. PanACEA can rapidly translate the results of pan-chromosome programs into an intuitive and interactive visual representation. It will empower researchers to visually explore and identify regions of the pan-chromosome that are most biologically interesting, and to obtain publication quality images of these regions.

Strategies to explore functional genomics data sets in NCBI's GEO database.

PubMed

Wilhite, Stephen E; Barrett, Tanya

2012-01-01

The Gene Expression Omnibus (GEO) database is a major repository that stores high-throughput functional genomics data sets that are generated using both microarray-based and sequence-based technologies. Data sets are submitted to GEO primarily by researchers who are publishing their results in journals that require original data to be made freely available for review and analysis. In addition to serving as a public archive for these data, GEO has a suite of tools that allow users to identify, analyze, and visualize data relevant to their specific interests. These tools include sample comparison applications, gene expression profile charts, data set clusters, genome browser tracks, and a powerful search engine that enables users to construct complex queries.

Strategies to Explore Functional Genomics Data Sets in NCBI’s GEO Database

PubMed Central

Wilhite, Stephen E.; Barrett, Tanya

2012-01-01

The Gene Expression Omnibus (GEO) database is a major repository that stores high-throughput functional genomics data sets that are generated using both microarray-based and sequence-based technologies. Data sets are submitted to GEO primarily by researchers who are publishing their results in journals that require original data to be made freely available for review and analysis. In addition to serving as a public archive for these data, GEO has a suite of tools that allow users to identify, analyze and visualize data relevant to their specific interests. These tools include sample comparison applications, gene expression profile charts, data set clusters, genome browser tracks, and a powerful search engine that enables users to construct complex queries. PMID:22130872

Integration of information and volume visualization for analysis of cell lineage and gene expression during embryogenesis

NASA Astrophysics Data System (ADS)

Cedilnik, Andrej; Baumes, Jeffrey; Ibanez, Luis; Megason, Sean; Wylie, Brian

2008-01-01

Dramatic technological advances in the field of genomics have made it possible to sequence the complete genomes of many different organisms. With this overwhelming amount of data at hand, biologists are now confronted with the challenge of understanding the function of the many different elements of the genome. One of the best places to start gaining insight on the mechanisms by which the genome controls an organism is the study of embryogenesis. There are multiple and inter-related layers of information that must be established in order to understand how the genome controls the formation of an organism. One is cell lineage which describes how patterns of cell division give rise to different parts of an organism. Another is gene expression which describes when and where different genes are turned on. Both of these data types can now be acquired using fluorescent laser-scanning (confocal or 2-photon) microscopy of embryos tagged with fluorescent proteins to generate 3D movies of developing embryos. However, analyzing the wealth of resulting images requires tools capable of interactively visualizing several different types of information as well as being scalable to terabytes of data. This paper describes how the combination of existing large data volume visualization and the new Titan information visualization framework of the Visualization Toolkit (VTK) can be applied to the problem of studying the cell lineage of an organism. In particular, by linking the visualization of spatial and temporal gene expression data with novel ways of visualizing cell lineage data, users can study how the genome regulates different aspects of embryonic development.

Pathway Tools version 19.0 update: software for pathway/genome informatics and systems biology

PubMed Central

Latendresse, Mario; Paley, Suzanne M.; Krummenacker, Markus; Ong, Quang D.; Billington, Richard; Kothari, Anamika; Weaver, Daniel; Lee, Thomas; Subhraveti, Pallavi; Spaulding, Aaron; Fulcher, Carol; Keseler, Ingrid M.; Caspi, Ron

2016-01-01

Pathway Tools is a bioinformatics software environment with a broad set of capabilities. The software provides genome-informatics tools such as a genome browser, sequence alignments, a genome-variant analyzer and comparative-genomics operations. It offers metabolic-informatics tools, such as metabolic reconstruction, quantitative metabolic modeling, prediction of reaction atom mappings and metabolic route search. Pathway Tools also provides regulatory-informatics tools, such as the ability to represent and visualize a wide range of regulatory interactions. This article outlines the advances in Pathway Tools in the past 5 years. Major additions include components for metabolic modeling, metabolic route search, computation of atom mappings and estimation of compound Gibbs free energies of formation; addition of editors for signaling pathways, for genome sequences and for cellular architecture; storage of gene essentiality data and phenotype data; display of multiple alignments, and of signaling and electron-transport pathways; and development of Python and web-services application programming interfaces. Scientists around the world have created more than 9800 Pathway/Genome Databases by using Pathway Tools, many of which are curated databases for important model organisms. PMID:26454094

A dictionary based informational genome analysis

PubMed Central

2012-01-01

Background In the post-genomic era several methods of computational genomics are emerging to understand how the whole information is structured within genomes. Literature of last five years accounts for several alignment-free methods, arisen as alternative metrics for dissimilarity of biological sequences. Among the others, recent approaches are based on empirical frequencies of DNA k-mers in whole genomes. Results Any set of words (factors) occurring in a genome provides a genomic dictionary. About sixty genomes were analyzed by means of informational indexes based on genomic dictionaries, where a systemic view replaces a local sequence analysis. A software prototype applying a methodology here outlined carried out some computations on genomic data. We computed informational indexes, built the genomic dictionaries with different sizes, along with frequency distributions. The software performed three main tasks: computation of informational indexes, storage of these in a database, index analysis and visualization. The validation was done by investigating genomes of various organisms. A systematic analysis of genomic repeats of several lengths, which is of vivid interest in biology (for example to compute excessively represented functional sequences, such as promoters), was discussed, and suggested a method to define synthetic genetic networks. Conclusions We introduced a methodology based on dictionaries, and an efficient motif-finding software application for comparative genomics. This approach could be extended along many investigation lines, namely exported in other contexts of computational genomics, as a basis for discrimination of genomic pathologies. PMID:22985068

SVGenes: a library for rendering genomic features in scalable vector graphic format.

PubMed

Etherington, Graham J; MacLean, Daniel

2013-08-01

Drawing genomic features in attractive and informative ways is a key task in visualization of genomics data. Scalable Vector Graphics (SVG) format is a modern and flexible open standard that provides advanced features including modular graphic design, advanced web interactivity and animation within a suitable client. SVGs do not suffer from loss of image quality on re-scaling and provide the ability to edit individual elements of a graphic on the whole object level independent of the whole image. These features make SVG a potentially useful format for the preparation of publication quality figures including genomic objects such as genes or sequencing coverage and for web applications that require rich user-interaction with the graphical elements. SVGenes is a Ruby-language library that uses SVG primitives to render typical genomic glyphs through a simple and flexible Ruby interface. The library implements a simple Page object that spaces and contains horizontal Track objects that in turn style, colour and positions features within them. Tracks are the level at which visual information is supplied providing the full styling capability of the SVG standard. Genomic entities like genes, transcripts and histograms are modelled in Glyph objects that are attached to a track and take advantage of SVG primitives to render the genomic features in a track as any of a selection of defined glyphs. The feature model within SVGenes is simple but flexible and not dependent on particular existing gene feature formats meaning graphics for any existing datasets can easily be created without need for conversion. The library is provided as a Ruby Gem from https://rubygems.org/gems/bio-svgenes under the MIT license, and open source code is available at https://github.com/danmaclean/bioruby-svgenes also under the MIT License. dan.maclean@tsl.ac.uk.

The i5k Workspace@NAL – enabling genomic data access, visualization, and curation for the i5k community

USDA-ARS?s Scientific Manuscript database

The 5,000 arthropod genomes initiative (i5k) has tasked itself with coordinating the sequencing of 5,000 insect or related arthropod genomes. The resulting influx of data, mostly from small research groups or communities with little bioinformatics experience, will require visualization, disseminatio...

CASFISH: CRISPR/Cas9-mediated in situ labeling of genomic loci in fixed cells.

PubMed

Deng, Wulan; Shi, Xinghua; Tjian, Robert; Lionnet, Timothée; Singer, Robert H

2015-09-22

Direct visualization of genomic loci in the 3D nucleus is important for understanding the spatial organization of the genome and its association with gene expression. Various DNA FISH methods have been developed in the past decades, all involving denaturing dsDNA and hybridizing fluorescent nucleic acid probes. Here we report a novel approach that uses in vitro constituted nuclease-deficient clustered regularly interspaced short palindromic repeats (CRISPR)/CRISPR-associated caspase 9 (Cas9) complexes as probes to label sequence-specific genomic loci fluorescently without global DNA denaturation (Cas9-mediated fluorescence in situ hybridization, CASFISH). Using fluorescently labeled nuclease-deficient Cas9 (dCas9) protein assembled with various single-guide RNA (sgRNA), we demonstrated rapid and robust labeling of repetitive DNA elements in pericentromere, centromere, G-rich telomere, and coding gene loci. Assembling dCas9 with an array of sgRNAs tiling arbitrary target loci, we were able to visualize nonrepetitive genomic sequences. The dCas9/sgRNA binary complex is stable and binds its target DNA with high affinity, allowing sequential or simultaneous probing of multiple targets. CASFISH assays using differently colored dCas9/sgRNA complexes allow multicolor labeling of target loci in cells. In addition, the CASFISH assay is remarkably rapid under optimal conditions and is applicable for detection in primary tissue sections. This rapid, robust, less disruptive, and cost-effective technology adds a valuable tool for basic research and genetic diagnosis.

BioQ: tracing experimental origins in public genomic databases using a novel data provenance model

PubMed Central

Saccone, Scott F.; Quan, Jiaxi; Jones, Peter L.

2012-01-01

Motivation: Public genomic databases, which are often used to guide genetic studies of human disease, are now being applied to genomic medicine through in silico integrative genomics. These databases, however, often lack tools for systematically determining the experimental origins of the data. Results: We introduce a new data provenance model that we have implemented in a public web application, BioQ, for assessing the reliability of the data by systematically tracing its experimental origins to the original subjects and biologics. BioQ allows investigators to both visualize data provenance as well as explore individual elements of experimental process flow using precise tools for detailed data exploration and documentation. It includes a number of human genetic variation databases such as the HapMap and 1000 Genomes projects. Availability and implementation: BioQ is freely available to the public at http://bioq.saclab.net Contact: ssaccone@wustl.edu Supplementary information: Supplementary data are available at Bioinformatics online. PMID:22426342

RSAT 2015: Regulatory Sequence Analysis Tools

PubMed Central

Medina-Rivera, Alejandra; Defrance, Matthieu; Sand, Olivier; Herrmann, Carl; Castro-Mondragon, Jaime A.; Delerce, Jeremy; Jaeger, Sébastien; Blanchet, Christophe; Vincens, Pierre; Caron, Christophe; Staines, Daniel M.; Contreras-Moreira, Bruno; Artufel, Marie; Charbonnier-Khamvongsa, Lucie; Hernandez, Céline; Thieffry, Denis; Thomas-Chollier, Morgane; van Helden, Jacques

2015-01-01

RSAT (Regulatory Sequence Analysis Tools) is a modular software suite for the analysis of cis-regulatory elements in genome sequences. Its main applications are (i) motif discovery, appropriate to genome-wide data sets like ChIP-seq, (ii) transcription factor binding motif analysis (quality assessment, comparisons and clustering), (iii) comparative genomics and (iv) analysis of regulatory variations. Nine new programs have been added to the 43 described in the 2011 NAR Web Software Issue, including a tool to extract sequences from a list of coordinates (fetch-sequences from UCSC), novel programs dedicated to the analysis of regulatory variants from GWAS or population genomics (retrieve-variation-seq and variation-scan), a program to cluster motifs and visualize the similarities as trees (matrix-clustering). To deal with the drastic increase of sequenced genomes, RSAT public sites have been reorganized into taxon-specific servers. The suite is well-documented with tutorials and published protocols. The software suite is available through Web sites, SOAP/WSDL Web services, virtual machines and stand-alone programs at http://www.rsat.eu/. PMID:25904632

A direct detection of Escherichia coli genomic DNA using gold nanoprobes

PubMed Central

2012-01-01

Background In situation like diagnosis of clinical and forensic samples there exists a need for highly sensitive, rapid and specific DNA detection methods. Though conventional DNA amplification using PCR can provide fast results, it is not widely practised in diagnostic laboratories partially because it requires skilled personnel and expensive equipment. To overcome these limitations nanoparticles have been explored as signalling probes for ultrasensitive DNA detection that can be used in field applications. Among the nanomaterials, gold nanoparticles (AuNPs) have been extensively used mainly because of its optical property and ability to get functionalized with a variety of biomolecules. Results We report a protocol for the use of gold nanoparticles functionalized with single stranded oligonucleotide (AuNP- oligo probe) as visual detection probes for rapid and specific detection of Escherichia coli. The AuNP- oligo probe on hybridization with target DNA containing complementary sequences remains red whereas test samples without complementary DNA sequences to the probe turns purple due to acid induced aggregation of AuNP- oligo probes. The color change of the solution is observed visually by naked eye demonstrating direct and rapid detection of the pathogenic Escherichia coli from its genomic DNA without the need for PCR amplification. The limit of detection was ~54 ng for unamplified genomic DNA. The method requires less than 30 minutes to complete after genomic DNA extraction. However, by using unamplified enzymatic digested genomic DNA, the detection limit of 11.4 ng was attained. Results of UV-Vis spectroscopic measurement and AFM imaging further support the hypothesis of aggregation based visual discrimination. To elucidate its utility in medical diagnostic, the assay was validated on clinical strains of pathogenic Escherichia coli obtained from local hospitals and spiked urine samples. It was found to be 100% sensitive and proves to be highly specific without any cross reaction with non-Escherichia coli strains. Conclusion This work gives entry into a new class of DNA/gold nanoparticles hybrid materials which might have optical property that can be controlled for application in diagnostics. We note that it should be possible to extend this strategy easily for developing new types of DNA biosensor for point of care detection. The salient feature of this approach includes low-cost, robust reagents and simple colorimetric detection of pathogen. PMID:22309695

GBshape: a genome browser database for DNA shape annotations

PubMed Central

Chiu, Tsu-Pei; Yang, Lin; Zhou, Tianyin; Main, Bradley J.; Parker, Stephen C.J.; Nuzhdin, Sergey V.; Tullius, Thomas D.; Rohs, Remo

2015-01-01

Many regulatory mechanisms require a high degree of specificity in protein-DNA binding. Nucleotide sequence does not provide an answer to the question of why a protein binds only to a small subset of the many putative binding sites in the genome that share the same core motif. Whereas higher-order effects, such as chromatin accessibility, cooperativity and cofactors, have been described, DNA shape recently gained attention as another feature that fine-tunes the DNA binding specificities of some transcription factor families. Our Genome Browser for DNA shape annotations (GBshape; freely available at http://rohslab.cmb.usc.edu/GBshape/) provides minor groove width, propeller twist, roll, helix twist and hydroxyl radical cleavage predictions for the entire genomes of 94 organisms. Additional genomes can easily be added using the GBshape framework. GBshape can be used to visualize DNA shape annotations qualitatively in a genome browser track format, and to download quantitative values of DNA shape features as a function of genomic position at nucleotide resolution. As biological applications, we illustrate the periodicity of DNA shape features that are present in nucleosome-occupied sequences from human, fly and worm, and we demonstrate structural similarities between transcription start sites in the genomes of four Drosophila species. PMID:25326329

DNA Data Visualization (DDV): Software for Generating Web-Based Interfaces Supporting Navigation and Analysis of DNA Sequence Data of Entire Genomes.

PubMed

Neugebauer, Tomasz; Bordeleau, Eric; Burrus, Vincent; Brzezinski, Ryszard

2015-01-01

Data visualization methods are necessary during the exploration and analysis activities of an increasingly data-intensive scientific process. There are few existing visualization methods for raw nucleotide sequences of a whole genome or chromosome. Software for data visualization should allow the researchers to create accessible data visualization interfaces that can be exported and shared with others on the web. Herein, novel software developed for generating DNA data visualization interfaces is described. The software converts DNA data sets into images that are further processed as multi-scale images to be accessed through a web-based interface that supports zooming, panning and sequence fragment selection. Nucleotide composition frequencies and GC skew of a selected sequence segment can be obtained through the interface. The software was used to generate DNA data visualization of human and bacterial chromosomes. Examples of visually detectable features such as short and long direct repeats, long terminal repeats, mobile genetic elements, heterochromatic segments in microbial and human chromosomes, are presented. The software and its source code are available for download and further development. The visualization interfaces generated with the software allow for the immediate identification and observation of several types of sequence patterns in genomes of various sizes and origins. The visualization interfaces generated with the software are readily accessible through a web browser. This software is a useful research and teaching tool for genetics and structural genomics.

Fluorescence In situ Hybridization: Cell-Based Genetic Diagnostic and Research Applications.

PubMed

Cui, Chenghua; Shu, Wei; Li, Peining

2016-01-01

Fluorescence in situ hybridization (FISH) is a macromolecule recognition technology based on the complementary nature of DNA or DNA/RNA double strands. Selected DNA strands incorporated with fluorophore-coupled nucleotides can be used as probes to hybridize onto the complementary sequences in tested cells and tissues and then visualized through a fluorescence microscope or an imaging system. This technology was initially developed as a physical mapping tool to delineate genes within chromosomes. Its high analytical resolution to a single gene level and high sensitivity and specificity enabled an immediate application for genetic diagnosis of constitutional common aneuploidies, microdeletion/microduplication syndromes, and subtelomeric rearrangements. FISH tests using panels of gene-specific probes for somatic recurrent losses, gains, and translocations have been routinely applied for hematologic and solid tumors and are one of the fastest-growing areas in cancer diagnosis. FISH has also been used to detect infectious microbias and parasites like malaria in human blood cells. Recent advances in FISH technology involve various methods for improving probe labeling efficiency and the use of super resolution imaging systems for direct visualization of intra-nuclear chromosomal organization and profiling of RNA transcription in single cells. Cas9-mediated FISH (CASFISH) allowed in situ labeling of repetitive sequences and single-copy sequences without the disruption of nuclear genomic organization in fixed or living cells. Using oligopaint-FISH and super-resolution imaging enabled in situ visualization of chromosome haplotypes from differentially specified single-nucleotide polymorphism loci. Single molecule RNA FISH (smRNA-FISH) using combinatorial labeling or sequential barcoding by multiple round of hybridization were applied to measure mRNA expression of multiple genes within single cells. Research applications of these single molecule single cells DNA and RNA FISH techniques have visualized intra-nuclear genomic structure and sub-cellular transcriptional dynamics of many genes and revealed their functions in various biological processes.

Genomes as geography: using GIS technology to build interactive genome feature maps

PubMed Central

Dolan, Mary E; Holden, Constance C; Beard, M Kate; Bult, Carol J

2006-01-01

Background Many commonly used genome browsers display sequence annotations and related attributes as horizontal data tracks that can be toggled on and off according to user preferences. Most genome browsers use only simple keyword searches and limit the display of detailed annotations to one chromosomal region of the genome at a time. We have employed concepts, methodologies, and tools that were developed for the display of geographic data to develop a Genome Spatial Information System (GenoSIS) for displaying genomes spatially, and interacting with genome annotations and related attribute data. In contrast to the paradigm of horizontally stacked data tracks used by most genome browsers, GenoSIS uses the concept of registered spatial layers composed of spatial objects for integrated display of diverse data. In addition to basic keyword searches, GenoSIS supports complex queries, including spatial queries, and dynamically generates genome maps. Our adaptation of the geographic information system (GIS) model in a genome context supports spatial representation of genome features at multiple scales with a versatile and expressive query capability beyond that supported by existing genome browsers. Results We implemented an interactive genome sequence feature map for the mouse genome in GenoSIS, an application that uses ArcGIS, a commercially available GIS software system. The genome features and their attributes are represented as spatial objects and data layers that can be toggled on and off according to user preferences or displayed selectively in response to user queries. GenoSIS supports the generation of custom genome maps in response to complex queries about genome features based on both their attributes and locations. Our example application of GenoSIS to the mouse genome demonstrates the powerful visualization and query capability of mature GIS technology applied in a novel domain. Conclusion Mapping tools developed specifically for geographic data can be exploited to display, explore and interact with genome data. The approach we describe here is organism independent and is equally useful for linear and circular chromosomes. One of the unique capabilities of GenoSIS compared to existing genome browsers is the capacity to generate genome feature maps dynamically in response to complex attribute and spatial queries. PMID:16984652

ShinyGPAS: interactive genomic prediction accuracy simulator based on deterministic formulas.

PubMed

Morota, Gota

2017-12-20

Deterministic formulas for the accuracy of genomic predictions highlight the relationships among prediction accuracy and potential factors influencing prediction accuracy prior to performing computationally intensive cross-validation. Visualizing such deterministic formulas in an interactive manner may lead to a better understanding of how genetic factors control prediction accuracy. The software to simulate deterministic formulas for genomic prediction accuracy was implemented in R and encapsulated as a web-based Shiny application. Shiny genomic prediction accuracy simulator (ShinyGPAS) simulates various deterministic formulas and delivers dynamic scatter plots of prediction accuracy versus genetic factors impacting prediction accuracy, while requiring only mouse navigation in a web browser. ShinyGPAS is available at: https://chikudaisei.shinyapps.io/shinygpas/ . ShinyGPAS is a shiny-based interactive genomic prediction accuracy simulator using deterministic formulas. It can be used for interactively exploring potential factors that influence prediction accuracy in genome-enabled prediction, simulating achievable prediction accuracy prior to genotyping individuals, or supporting in-class teaching. ShinyGPAS is open source software and it is hosted online as a freely available web-based resource with an intuitive graphical user interface.

NCBI GEO: archive for functional genomics data sets--update.

PubMed

Barrett, Tanya; Wilhite, Stephen E; Ledoux, Pierre; Evangelista, Carlos; Kim, Irene F; Tomashevsky, Maxim; Marshall, Kimberly A; Phillippy, Katherine H; Sherman, Patti M; Holko, Michelle; Yefanov, Andrey; Lee, Hyeseung; Zhang, Naigong; Robertson, Cynthia L; Serova, Nadezhda; Davis, Sean; Soboleva, Alexandra

2013-01-01

The Gene Expression Omnibus (GEO, http://www.ncbi.nlm.nih.gov/geo/) is an international public repository for high-throughput microarray and next-generation sequence functional genomic data sets submitted by the research community. The resource supports archiving of raw data, processed data and metadata which are indexed, cross-linked and searchable. All data are freely available for download in a variety of formats. GEO also provides several web-based tools and strategies to assist users to query, analyse and visualize data. This article reports current status and recent database developments, including the release of GEO2R, an R-based web application that helps users analyse GEO data.

Laser Capture Microdissection in the Genomic and Proteomic Era: Targeting the Genetic Basis of Cancer

PubMed Central

Domazet, Barbara; MacLennan, Gregory T.; Lopez-Beltran, Antonio; Montironi, Rodolfo; Cheng, Liang

2008-01-01

The advent of new technologies has enabled deeper insight into processes atsubcellular levels, which will ultimately improve diagnostic procedures and patient outcome. Thanks to cell enrichment methods, it is now possible to study cells in their native environment. This has greatly contributed to a rapid growth in several areas, such as gene expression analysis, proteomics, and metabolonomics. Laser capture microdissection (LCM) as a method of procuring subpopulations of cells under direct visual inspection is playing an important role in these areas. This review provides an overview of existing LCM technology and its downstream applications in genomics, proteomics, diagnostics and therapy. PMID:18787684

Laser capture microdissection in the genomic and proteomic era: targeting the genetic basis of cancer.

PubMed

Domazet, Barbara; Maclennan, Gregory T; Lopez-Beltran, Antonio; Montironi, Rodolfo; Cheng, Liang

2008-03-15

The advent of new technologies has enabled deeper insight into processes at subcellular levels, which will ultimately improve diagnostic procedures and patient outcome. Thanks to cell enrichment methods, it is now possible to study cells in their native environment. This has greatly contributed to a rapid growth in several areas, such as gene expression analysis, proteomics, and metabolonomics. Laser capture microdissection (LCM) as a method of procuring subpopulations of cells under direct visual inspection is playing an important role in these areas. This review provides an overview of existing LCM technology and its downstream applications in genomics, proteomics, diagnostics and therapy.

Association of common genetic variants in GPCPD1 with scaling of visual cortical surface area in humans.

PubMed

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.

dictyExpress: a web-based platform for sequence data management and analytics in Dictyostelium and beyond.

PubMed

Stajdohar, Miha; Rosengarten, Rafael D; Kokosar, Janez; Jeran, Luka; Blenkus, Domen; Shaulsky, Gad; Zupan, Blaz

2017-06-02

Dictyostelium discoideum, a soil-dwelling social amoeba, is a model for the study of numerous biological processes. Research in the field has benefited mightily from the adoption of next-generation sequencing for genomics and transcriptomics. Dictyostelium biologists now face the widespread challenges of analyzing and exploring high dimensional data sets to generate hypotheses and discovering novel insights. We present dictyExpress (2.0), a web application designed for exploratory analysis of gene expression data, as well as data from related experiments such as Chromatin Immunoprecipitation sequencing (ChIP-Seq). The application features visualization modules that include time course expression profiles, clustering, gene ontology enrichment analysis, differential expression analysis and comparison of experiments. All visualizations are interactive and interconnected, such that the selection of genes in one module propagates instantly to visualizations in other modules. dictyExpress currently stores the data from over 800 Dictyostelium experiments and is embedded within a general-purpose software framework for management of next-generation sequencing data. dictyExpress allows users to explore their data in a broader context by reciprocal linking with dictyBase-a repository of Dictyostelium genomic data. In addition, we introduce a companion application called GenBoard, an intuitive graphic user interface for data management and bioinformatics analysis. dictyExpress and GenBoard enable broad adoption of next generation sequencing based inquiries by the Dictyostelium research community. Labs without the means to undertake deep sequencing projects can mine the data available to the public. The entire information flow, from raw sequence data to hypothesis testing, can be accomplished in an efficient workspace. The software framework is generalizable and represents a useful approach for any research community. To encourage more wide usage, the backend is open-source, available for extension and further development by bioinformaticians and data scientists.

MOSAIC: an online database dedicated to the comparative genomics of bacterial strains at the intra-species level.

PubMed

Chiapello, Hélène; Gendrault, Annie; Caron, Christophe; Blum, Jérome; Petit, Marie-Agnès; El Karoui, Meriem

2008-11-27

The recent availability of complete sequences for numerous closely related bacterial genomes opens up new challenges in comparative genomics. Several methods have been developed to align complete genomes at the nucleotide level but their use and the biological interpretation of results are not straightforward. It is therefore necessary to develop new resources to access, analyze, and visualize genome comparisons. Here we present recent developments on MOSAIC, a generalist comparative bacterial genome database. This database provides the bacteriologist community with easy access to comparisons of complete bacterial genomes at the intra-species level. The strategy we developed for comparison allows us to define two types of regions in bacterial genomes: backbone segments (i.e., regions conserved in all compared strains) and variable segments (i.e., regions that are either specific to or variable in one of the aligned genomes). Definition of these segments at the nucleotide level allows precise comparative and evolutionary analyses of both coding and non-coding regions of bacterial genomes. Such work is easily performed using the MOSAIC Web interface, which allows browsing and graphical visualization of genome comparisons. The MOSAIC database now includes 493 pairwise comparisons and 35 multiple maximal comparisons representing 78 bacterial species. Genome conserved regions (backbones) and variable segments are presented in various formats for further analysis. A graphical interface allows visualization of aligned genomes and functional annotations. The MOSAIC database is available online at http://genome.jouy.inra.fr/mosaic.

PGSB PlantsDB: updates to the database framework for comparative plant genome research.

PubMed

Spannagl, Manuel; Nussbaumer, Thomas; Bader, Kai C; Martis, Mihaela M; Seidel, Michael; Kugler, Karl G; Gundlach, Heidrun; Mayer, Klaus F X

2016-01-04

PGSB (Plant Genome and Systems Biology: formerly MIPS) PlantsDB (http://pgsb.helmholtz-muenchen.de/plant/index.jsp) is a database framework for the comparative analysis and visualization of plant genome data. The resource has been updated with new data sets and types as well as specialized tools and interfaces to address user demands for intuitive access to complex plant genome data. In its latest incarnation, we have re-worked both the layout and navigation structure and implemented new keyword search options and a new BLAST sequence search functionality. Actively involved in corresponding sequencing consortia, PlantsDB has dedicated special efforts to the integration and visualization of complex triticeae genome data, especially for barley, wheat and rye. We enhanced CrowsNest, a tool to visualize syntenic relationships between genomes, with data from the wheat sub-genome progenitor Aegilops tauschii and added functionality to the PGSB RNASeqExpressionBrowser. GenomeZipper results were integrated for the genomes of barley, rye, wheat and perennial ryegrass and interactive access is granted through PlantsDB interfaces. Data exchange and cross-linking between PlantsDB and other plant genome databases is stimulated by the transPLANT project (http://transplantdb.eu/). © The Author(s) 2015. Published by Oxford University Press on behalf of Nucleic Acids Research.

DNAism: exploring genomic datasets on the web with Horizon Charts.

PubMed

Rio Deiros, David; Gibbs, Richard A; Rogers, Jeffrey

2016-01-27

Computational biologists daily face the need to explore massive amounts of genomic data. New visualization techniques can help researchers navigate and understand these big data. Horizon Charts are a relatively new visualization method that, under the right circumstances, maximizes data density without losing graphical perception. Horizon Charts have been successfully applied to understand multi-metric time series data. We have adapted an existing JavaScript library (Cubism) that implements Horizon Charts for the time series domain so that it works effectively with genomic datasets. We call this new library DNAism. Horizon Charts can be an effective visual tool to explore complex and large genomic datasets. Researchers can use our library to leverage these techniques to extract additional insights from their own datasets.

Genomics Analogy Model for Educators (GAME): Fuzzy DNA Model to Enable the Learning of Gene Sequencing by Visually-Impaired and Blind Students

ERIC Educational Resources Information Center

Butler, Charles; Bello, Julia; York, Alan; Orvis, Kathryn; Pittendrigh, Barry R.

2008-01-01

Much of the general population is aware of terms such as biotechnology, genetic engineering, and genomics. However, there is a lack of understanding concerning these fields among many secondary school students. Few teaching models exist to explain concepts behind genomics and even less are available for teaching the visually impaired and blind.…

Recent updates and developments to plant genome size databases

PubMed Central

Garcia, Sònia; Leitch, Ilia J.; Anadon-Rosell, Alba; Canela, Miguel Á.; Gálvez, Francisco; Garnatje, Teresa; Gras, Airy; Hidalgo, Oriane; Johnston, Emmeline; Mas de Xaxars, Gemma; Pellicer, Jaume; Siljak-Yakovlev, Sonja; Vallès, Joan; Vitales, Daniel; Bennett, Michael D.

2014-01-01

Two plant genome size databases have been recently updated and/or extended: the Plant DNA C-values database (http://data.kew.org/cvalues), and GSAD, the Genome Size in Asteraceae database (http://www.asteraceaegenomesize.com). While the first provides information on nuclear DNA contents across land plants and some algal groups, the second is focused on one of the largest and most economically important angiosperm families, Asteraceae. Genome size data have numerous applications: they can be used in comparative studies on genome evolution, or as a tool to appraise the cost of whole-genome sequencing programs. The growing interest in genome size and increasing rate of data accumulation has necessitated the continued update of these databases. Currently, the Plant DNA C-values database (Release 6.0, Dec. 2012) contains data for 8510 species, while GSAD has 1219 species (Release 2.0, June 2013), representing increases of 17 and 51%, respectively, in the number of species with genome size data, compared with previous releases. Here we provide overviews of the most recent releases of each database, and outline new features of GSAD. The latter include (i) a tool to visually compare genome size data between species, (ii) the option to export data and (iii) a webpage containing information about flow cytometry protocols. PMID:24288377

Integrative Analysis of Complex Cancer Genomics and Clinical Profiles Using the cBioPortal

PubMed Central

Gao, Jianjiong; Aksoy, Bülent Arman; Dogrusoz, Ugur; Dresdner, Gideon; Gross, Benjamin; Sumer, S. Onur; Sun, Yichao; Jacobsen, Anders; Sinha, Rileen; Larsson, Erik; Cerami, Ethan; Sander, Chris; Schultz, Nikolaus

2014-01-01

The cBioPortal for Cancer Genomics (http://cbioportal.org) provides a Web resource for exploring, visualizing, and analyzing multidimensional cancer genomics data. The portal reduces molecular profiling data from cancer tissues and cell lines into readily understandable genetic, epigenetic, gene expression, and proteomic events. The query interface combined with customized data storage enables researchers to interactively explore genetic alterations across samples, genes, and pathways and, when available in the underlying data, to link these to clinical outcomes. The portal provides graphical summaries of gene-level data from multiple platforms, network visualization and analysis, survival analysis, patient-centric queries, and software programmatic access. The intuitive Web interface of the portal makes complex cancer genomics profiles accessible to researchers and clinicians without requiring bioinformatics expertise, thus facilitating biological discoveries. Here, we provide a practical guide to the analysis and visualization features of the cBioPortal for Cancer Genomics. PMID:23550210

Genome Maps, a new generation genome browser.

PubMed

Medina, Ignacio; Salavert, Francisco; Sanchez, Rubén; de Maria, Alejandro; Alonso, Roberto; Escobar, Pablo; Bleda, Marta; Dopazo, Joaquín

2013-07-01

Genome browsers have gained importance as more genomes and related genomic information become available. However, the increase of information brought about by new generation sequencing technologies is, at the same time, causing a subtle but continuous decrease in the efficiency of conventional genome browsers. Here, we present Genome Maps, a genome browser that implements an innovative model of data transfer and management. The program uses highly efficient technologies from the new HTML5 standard, such as scalable vector graphics, that optimize workloads at both server and client sides and ensure future scalability. Thus, data management and representation are entirely carried out by the browser, without the need of any Java Applet, Flash or other plug-in technology installation. Relevant biological data on genes, transcripts, exons, regulatory features, single-nucleotide polymorphisms, karyotype and so forth, are imported from web services and are available as tracks. In addition, several DAS servers are already included in Genome Maps. As a novelty, this web-based genome browser allows the local upload of huge genomic data files (e.g. VCF or BAM) that can be dynamically visualized in real time at the client side, thus facilitating the management of medical data affected by privacy restrictions. Finally, Genome Maps can easily be integrated in any web application by including only a few lines of code. Genome Maps is an open source collaborative initiative available in the GitHub repository (https://github.com/compbio-bigdata-viz/genome-maps). Genome Maps is available at: http://www.genomemaps.org.

Genome Maps, a new generation genome browser

PubMed Central

Medina, Ignacio; Salavert, Francisco; Sanchez, Rubén; de Maria, Alejandro; Alonso, Roberto; Escobar, Pablo; Bleda, Marta; Dopazo, Joaquín

2013-01-01

Genome browsers have gained importance as more genomes and related genomic information become available. However, the increase of information brought about by new generation sequencing technologies is, at the same time, causing a subtle but continuous decrease in the efficiency of conventional genome browsers. Here, we present Genome Maps, a genome browser that implements an innovative model of data transfer and management. The program uses highly efficient technologies from the new HTML5 standard, such as scalable vector graphics, that optimize workloads at both server and client sides and ensure future scalability. Thus, data management and representation are entirely carried out by the browser, without the need of any Java Applet, Flash or other plug-in technology installation. Relevant biological data on genes, transcripts, exons, regulatory features, single-nucleotide polymorphisms, karyotype and so forth, are imported from web services and are available as tracks. In addition, several DAS servers are already included in Genome Maps. As a novelty, this web-based genome browser allows the local upload of huge genomic data files (e.g. VCF or BAM) that can be dynamically visualized in real time at the client side, thus facilitating the management of medical data affected by privacy restrictions. Finally, Genome Maps can easily be integrated in any web application by including only a few lines of code. Genome Maps is an open source collaborative initiative available in the GitHub repository (https://github.com/compbio-bigdata-viz/genome-maps). Genome Maps is available at: http://www.genomemaps.org. PMID:23748955

The Gene Expression Omnibus database

PubMed Central

Clough, Emily; Barrett, Tanya

2016-01-01

The Gene Expression Omnibus (GEO) database is an international public repository that archives and freely distributes high-throughput gene expression and other functional genomics data sets. Created in 2000 as a worldwide resource for gene expression studies, GEO has evolved with rapidly changing technologies and now accepts high-throughput data for many other data applications, including those that examine genome methylation, chromatin structure, and genome–protein interactions. GEO supports community-derived reporting standards that specify provision of several critical study elements including raw data, processed data, and descriptive metadata. The database not only provides access to data for tens of thousands of studies, but also offers various Web-based tools and strategies that enable users to locate data relevant to their specific interests, as well as to visualize and analyze the data. This chapter includes detailed descriptions of methods to query and download GEO data and use the analysis and visualization tools. The GEO homepage is at http://www.ncbi.nlm.nih.gov/geo/. PMID:27008011

Software for the Integration of Multiomics Experiments in Bioconductor.

PubMed

Ramos, Marcel; Schiffer, Lucas; Re, Angela; Azhar, Rimsha; Basunia, Azfar; Rodriguez, Carmen; Chan, Tiffany; Chapman, Phil; Davis, Sean R; Gomez-Cabrero, David; Culhane, Aedin C; Haibe-Kains, Benjamin; Hansen, Kasper D; Kodali, Hanish; Louis, Marie S; Mer, Arvind S; Riester, Markus; Morgan, Martin; Carey, Vince; Waldron, Levi

2017-11-01

Multiomics experiments are increasingly commonplace in biomedical research and add layers of complexity to experimental design, data integration, and analysis. R and Bioconductor provide a generic framework for statistical analysis and visualization, as well as specialized data classes for a variety of high-throughput data types, but methods are lacking for integrative analysis of multiomics experiments. The MultiAssayExperiment software package, implemented in R and leveraging Bioconductor software and design principles, provides for the coordinated representation of, storage of, and operation on multiple diverse genomics data. We provide the unrestricted multiple 'omics data for each cancer tissue in The Cancer Genome Atlas as ready-to-analyze MultiAssayExperiment objects and demonstrate in these and other datasets how the software simplifies data representation, statistical analysis, and visualization. The MultiAssayExperiment Bioconductor package reduces major obstacles to efficient, scalable, and reproducible statistical analysis of multiomics data and enhances data science applications of multiple omics datasets. Cancer Res; 77(21); e39-42. ©2017 AACR . ©2017 American Association for Cancer Research.

Pathway Tools version 19.0 update: software for pathway/genome informatics and systems biology.

PubMed

Karp, Peter D; Latendresse, Mario; Paley, Suzanne M; Krummenacker, Markus; Ong, Quang D; Billington, Richard; Kothari, Anamika; Weaver, Daniel; Lee, Thomas; Subhraveti, Pallavi; Spaulding, Aaron; Fulcher, Carol; Keseler, Ingrid M; Caspi, Ron

2016-09-01

Pathway Tools is a bioinformatics software environment with a broad set of capabilities. The software provides genome-informatics tools such as a genome browser, sequence alignments, a genome-variant analyzer and comparative-genomics operations. It offers metabolic-informatics tools, such as metabolic reconstruction, quantitative metabolic modeling, prediction of reaction atom mappings and metabolic route search. Pathway Tools also provides regulatory-informatics tools, such as the ability to represent and visualize a wide range of regulatory interactions. This article outlines the advances in Pathway Tools in the past 5 years. Major additions include components for metabolic modeling, metabolic route search, computation of atom mappings and estimation of compound Gibbs free energies of formation; addition of editors for signaling pathways, for genome sequences and for cellular architecture; storage of gene essentiality data and phenotype data; display of multiple alignments, and of signaling and electron-transport pathways; and development of Python and web-services application programming interfaces. Scientists around the world have created more than 9800 Pathway/Genome Databases by using Pathway Tools, many of which are curated databases for important model organisms. © The Author 2015. Published by Oxford University Press. For Permissions, please email: journals.permissions@oup.com.

GenomeDiagram: a python package for the visualization of large-scale genomic data.

PubMed

Pritchard, Leighton; White, Jennifer A; Birch, Paul R J; Toth, Ian K

2006-03-01

We present GenomeDiagram, a flexible, open-source Python module for the visualization of large-scale genomic, comparative genomic and other data with reference to a single chromosome or other biological sequence. GenomeDiagram may be used to generate publication-quality vector graphics, rastered images and in-line streamed graphics for webpages. The package integrates with datatypes from the BioPython project, and is available for Windows, Linux and Mac OS X systems. GenomeDiagram is freely available as source code (under GNU Public License) at http://bioinf.scri.ac.uk/lp/programs.html, and requires Python 2.3 or higher, and recent versions of the ReportLab and BioPython packages. A user manual, example code and images are available at http://bioinf.scri.ac.uk/lp/programs.html.

GBshape: a genome browser database for DNA shape annotations.

PubMed

Chiu, Tsu-Pei; Yang, Lin; Zhou, Tianyin; Main, Bradley J; Parker, Stephen C J; Nuzhdin, Sergey V; Tullius, Thomas D; Rohs, Remo

2015-01-01

Many regulatory mechanisms require a high degree of specificity in protein-DNA binding. Nucleotide sequence does not provide an answer to the question of why a protein binds only to a small subset of the many putative binding sites in the genome that share the same core motif. Whereas higher-order effects, such as chromatin accessibility, cooperativity and cofactors, have been described, DNA shape recently gained attention as another feature that fine-tunes the DNA binding specificities of some transcription factor families. Our Genome Browser for DNA shape annotations (GBshape; freely available at http://rohslab.cmb.usc.edu/GBshape/) provides minor groove width, propeller twist, roll, helix twist and hydroxyl radical cleavage predictions for the entire genomes of 94 organisms. Additional genomes can easily be added using the GBshape framework. GBshape can be used to visualize DNA shape annotations qualitatively in a genome browser track format, and to download quantitative values of DNA shape features as a function of genomic position at nucleotide resolution. As biological applications, we illustrate the periodicity of DNA shape features that are present in nucleosome-occupied sequences from human, fly and worm, and we demonstrate structural similarities between transcription start sites in the genomes of four Drosophila species. © The Author(s) 2014. Published by Oxford University Press on behalf of Nucleic Acids Research.

chromoWIZ: a web tool to query and visualize chromosome-anchored genes from cereal and model genomes.

PubMed

Nussbaumer, Thomas; Kugler, Karl G; Schweiger, Wolfgang; Bader, Kai C; Gundlach, Heidrun; Spannagl, Manuel; Poursarebani, Naser; Pfeifer, Matthias; Mayer, Klaus F X

2014-12-10

Over the last years reference genome sequences of several economically and scientifically important cereals and model plants became available. Despite the agricultural significance of these crops only a small number of tools exist that allow users to inspect and visualize the genomic position of genes of interest in an interactive manner. We present chromoWIZ, a web tool that allows visualizing the genomic positions of relevant genes and comparing these data between different plant genomes. Genes can be queried using gene identifiers, functional annotations, or sequence homology in four grass species (Triticum aestivum, Hordeum vulgare, Brachypodium distachyon, Oryza sativa). The distribution of the anchored genes is visualized along the chromosomes by using heat maps. Custom gene expression measurements, differential expression information, and gene-to-group mappings can be uploaded and can be used for further filtering. This tool is mainly designed for breeders and plant researchers, who are interested in the location and the distribution of candidate genes as well as in the syntenic relationships between different grass species. chromoWIZ is freely available and online accessible at http://mips.helmholtz-muenchen.de/plant/chromoWIZ/index.jsp.

Visualization of RNA structure models within the Integrative Genomics Viewer.

PubMed

Busan, Steven; Weeks, Kevin M

2017-07-01

Analyses of the interrelationships between RNA structure and function are increasingly important components of genomic studies. The SHAPE-MaP strategy enables accurate RNA structure probing and realistic structure modeling of kilobase-length noncoding RNAs and mRNAs. Existing tools for visualizing RNA structure models are not suitable for efficient analysis of long, structurally heterogeneous RNAs. In addition, structure models are often advantageously interpreted in the context of other experimental data and gene annotation information, for which few tools currently exist. We have developed a module within the widely used and well supported open-source Integrative Genomics Viewer (IGV) that allows visualization of SHAPE and other chemical probing data, including raw reactivities, data-driven structural entropies, and data-constrained base-pair secondary structure models, in context with linear genomic data tracks. We illustrate the usefulness of visualizing RNA structure in the IGV by exploring structure models for a large viral RNA genome, comparing bacterial mRNA structure in cells with its structure under cell- and protein-free conditions, and comparing a noncoding RNA structure modeled using SHAPE data with a base-pairing model inferred through sequence covariation analysis. © 2017 Busan and Weeks; Published by Cold Spring Harbor Laboratory Press for the RNA Society.

Current status of potential applications of repurposed Cas9 for structural and functional genomics of plants.

PubMed

Seth, Kunal; Harish

2016-11-25

Redesigned Cas9 has emerged as a tool with various applications like gene editing, gene regulation, epigenetic modification and chromosomal imaging. Target specific single guide RNA (sgRNA) can be used with Cas9 for precise gene editing with high efficiency than previously known methods. Further, nuclease-deactivated Cas9 (dCas9) can be fused with activator or repressor for activation (CRISPRa) and repression (CRISPRi) of gene expression, respectively. dCas9 fused with epigenetic modifier like methylase or acetylase further expand the scope of this technique. Fluorescent probes can be tagged to dCas9 to visualize the chromosome. Due to its wide-spread application, simplicity, accessibility, efficacy and universality, this technique is expanding the structural and functional genomic studies of plant and developing CRISPR crops. The present review focuses on current status of using repurposed Cas9 system in these various areas, with major focus on application in plants. Major challenges, concerns and future directions of using this technique are discussed in brief. Copyright © 2016 Elsevier Inc. All rights reserved.

ATGC transcriptomics: a web-based application to integrate, explore and analyze de novo transcriptomic data.

PubMed

Gonzalez, Sergio; Clavijo, Bernardo; Rivarola, Máximo; Moreno, Patricio; Fernandez, Paula; Dopazo, Joaquín; Paniego, Norma

2017-02-22

In the last years, applications based on massively parallelized RNA sequencing (RNA-seq) have become valuable approaches for studying non-model species, e.g., without a fully sequenced genome. RNA-seq is a useful tool for detecting novel transcripts and genetic variations and for evaluating differential gene expression by digital measurements. The large and complex datasets resulting from functional genomic experiments represent a challenge in data processing, management, and analysis. This problem is especially significant for small research groups working with non-model species. We developed a web-based application, called ATGC transcriptomics, with a flexible and adaptable interface that allows users to work with new generation sequencing (NGS) transcriptomic analysis results using an ontology-driven database. This new application simplifies data exploration, visualization, and integration for a better comprehension of the results. ATGC transcriptomics provides access to non-expert computer users and small research groups to a scalable storage option and simple data integration, including database administration and management. The software is freely available under the terms of GNU public license at http://atgcinta.sourceforge.net .

RSAT 2015: Regulatory Sequence Analysis Tools.

PubMed

Medina-Rivera, Alejandra; Defrance, Matthieu; Sand, Olivier; Herrmann, Carl; Castro-Mondragon, Jaime A; Delerce, Jeremy; Jaeger, Sébastien; Blanchet, Christophe; Vincens, Pierre; Caron, Christophe; Staines, Daniel M; Contreras-Moreira, Bruno; Artufel, Marie; Charbonnier-Khamvongsa, Lucie; Hernandez, Céline; Thieffry, Denis; Thomas-Chollier, Morgane; van Helden, Jacques

2015-07-01

RSAT (Regulatory Sequence Analysis Tools) is a modular software suite for the analysis of cis-regulatory elements in genome sequences. Its main applications are (i) motif discovery, appropriate to genome-wide data sets like ChIP-seq, (ii) transcription factor binding motif analysis (quality assessment, comparisons and clustering), (iii) comparative genomics and (iv) analysis of regulatory variations. Nine new programs have been added to the 43 described in the 2011 NAR Web Software Issue, including a tool to extract sequences from a list of coordinates (fetch-sequences from UCSC), novel programs dedicated to the analysis of regulatory variants from GWAS or population genomics (retrieve-variation-seq and variation-scan), a program to cluster motifs and visualize the similarities as trees (matrix-clustering). To deal with the drastic increase of sequenced genomes, RSAT public sites have been reorganized into taxon-specific servers. The suite is well-documented with tutorials and published protocols. The software suite is available through Web sites, SOAP/WSDL Web services, virtual machines and stand-alone programs at http://www.rsat.eu/. © The Author(s) 2015. Published by Oxford University Press on behalf of Nucleic Acids Research.

Live neighbor-joining.

PubMed

Telles, Guilherme P; Araújo, Graziela S; Walter, Maria E M T; Brigido, Marcelo M; Almeida, Nalvo F

2018-05-16

In phylogenetic reconstruction the result is a tree where all taxa are leaves and internal nodes are hypothetical ancestors. In a live phylogeny, both ancestral and living taxa may coexist, leading to a tree where internal nodes may be living taxa. The well-known Neighbor-Joining heuristic is largely used for phylogenetic reconstruction. We present Live Neighbor-Joining, a heuristic for building a live phylogeny. We have investigated Live Neighbor-Joining on datasets of viral genomes, a plausible scenario for its application, which allowed the construction of alternative hypothesis for the relationships among virus that embrace both ancestral and descending taxa. We also applied Live Neighbor-Joining on a set of bacterial genomes and to sets of images and texts. Non-biological data may be better explored visually when their relationship in terms of content similarity is represented by means of a phylogeny. Our experiments have shown interesting alternative phylogenetic hypothesis for RNA virus genomes, bacterial genomes and alternative relationships among images and texts, illustrating a wide range of scenarios where Live Neighbor-Joining may be used.

NCBI GEO: archive for functional genomics data sets—update

PubMed Central

Barrett, Tanya; Wilhite, Stephen E.; Ledoux, Pierre; Evangelista, Carlos; Kim, Irene F.; Tomashevsky, Maxim; Marshall, Kimberly A.; Phillippy, Katherine H.; Sherman, Patti M.; Holko, Michelle; Yefanov, Andrey; Lee, Hyeseung; Zhang, Naigong; Robertson, Cynthia L.; Serova, Nadezhda; Davis, Sean; Soboleva, Alexandra

2013-01-01

The Gene Expression Omnibus (GEO, http://www.ncbi.nlm.nih.gov/geo/) is an international public repository for high-throughput microarray and next-generation sequence functional genomic data sets submitted by the research community. The resource supports archiving of raw data, processed data and metadata which are indexed, cross-linked and searchable. All data are freely available for download in a variety of formats. GEO also provides several web-based tools and strategies to assist users to query, analyse and visualize data. This article reports current status and recent database developments, including the release of GEO2R, an R-based web application that helps users analyse GEO data. PMID:23193258

Trafficking of bluetongue virus visualized by recovery of tetracysteine-tagged virion particles.

PubMed

Du, Junzheng; Bhattacharya, Bishnupriya; Ward, Theresa H; Roy, Polly

2014-11-01

Bluetongue virus (BTV), a member of the Orbivirus genus in the Reoviridae family, is a double-capsid insect-borne virus enclosing a genome of 10 double-stranded RNA segments. Like those of other members of the family, BTV virions are nonenveloped particles containing two architecturally complex capsids. The two proteins of the outer capsid, VP2 and VP5, are involved in BTV entry and in the delivery of the transcriptionally active core to the cell cytoplasm. Although the importance of the endocytic pathway in BTV entry has been reported, detailed analyses of entry and the role of each protein in virus trafficking have not been possible due to the lack of availability of a tagged virus. Here, for the first time, we report on the successful manipulation of a segmented genome of a nonenveloped capsid virus by the introduction of tags that were subsequently fluorescently visualized in infected cells. The genetically engineered fluorescent BTV particles were observed to enter live cells immediately after virus adsorption. Further, we showed the separation of VP2 from VP5 during virus entry and confirmed that while VP2 is shed from virions in early endosomes, virus particles still consisting of VP5 were trafficked sequentially from early to late endosomes. Since BTV infects both mammalian and insect cells, the generation of tagged viruses will allow visualization of the trafficking of BTV farther downstream in different host cells. In addition, the tagging technology has potential for transferable application to other nonenveloped complex viruses. Live-virus trafficking in host cells has been highly informative on the interactions between virus and host cells. Although the insertion of fluorescent markers into viral genomes has made it possible to study the trafficking of enveloped viruses, the physical constraints of architecturally complex capsid viruses have imposed practical limitations. In this study, we have successfully genetically engineered the segmented RNA genome of bluetongue virus (BTV), a complex nonenveloped virus belonging to the Reoviridae family. The resulting fluorescent virus particles could be visualized in virus entry studies of both live and fixed cells. This is the first time a structurally complex capsid virus has been successfully genetically manipulated to generate virus particles that could be visualized in infected cells. Copyright © 2014, American Society for Microbiology. All Rights Reserved.

Reefgenomics.Org - a repository for marine genomics data.

PubMed

Liew, Yi Jin; Aranda, Manuel; Voolstra, Christian R

2016-01-01

Over the last decade, technological advancements have substantially decreased the cost and time of obtaining large amounts of sequencing data. Paired with the exponentially increased computing power, individual labs are now able to sequence genomes or transcriptomes to investigate biological questions of interest. This has led to a significant increase in available sequence data. Although the bulk of data published in articles are stored in public sequence databases, very often, only raw sequencing data are available; miscellaneous data such as assembled transcriptomes, genome annotations etc. are not easily obtainable through the same means. Here, we introduce our website (http://reefgenomics.org) that aims to centralize genomic and transcriptomic data from marine organisms. Besides providing convenient means to download sequences, we provide (where applicable) a genome browser to explore available genomic features, and a BLAST interface to search through the hosted sequences. Through the interface, multiple datasets can be queried simultaneously, allowing for the retrieval of matching sequences from organisms of interest. The minimalistic, no-frills interface reduces visual clutter, making it convenient for end-users to search and explore processed sequence data. DATABASE URL: http://reefgenomics.org. © The Author(s) 2016. Published by Oxford University Press.

Genome contact map explorer: a platform for the comparison, interactive visualization and analysis of genome contact maps

PubMed Central

Kumar, Rajendra; Sobhy, Haitham

2017-01-01

Abstract Hi-C experiments generate data in form of large genome contact maps (Hi-C maps). These show that chromosomes are arranged in a hierarchy of three-dimensional compartments. But to understand how these compartments form and by how much they affect genetic processes such as gene regulation, biologists and bioinformaticians need efficient tools to visualize and analyze Hi-C data. However, this is technically challenging because these maps are big. In this paper, we remedied this problem, partly by implementing an efficient file format and developed the genome contact map explorer platform. Apart from tools to process Hi-C data, such as normalization methods and a programmable interface, we made a graphical interface that let users browse, scroll and zoom Hi-C maps to visually search for patterns in the Hi-C data. In the software, it is also possible to browse several maps simultaneously and plot related genomic data. The software is openly accessible to the scientific community. PMID:28973466

VirtualPlant: A Software Platform to Support Systems Biology Research1[W][OA

PubMed Central

Katari, Manpreet S.; Nowicki, Steve D.; Aceituno, Felipe F.; Nero, Damion; Kelfer, Jonathan; Thompson, Lee Parnell; Cabello, Juan M.; Davidson, Rebecca S.; Goldberg, Arthur P.; Shasha, Dennis E.; Coruzzi, Gloria M.; Gutiérrez, Rodrigo A.

2010-01-01

Data generation is no longer the limiting factor in advancing biological research. In addition, data integration, analysis, and interpretation have become key bottlenecks and challenges that biologists conducting genomic research face daily. To enable biologists to derive testable hypotheses from the increasing amount of genomic data, we have developed the VirtualPlant software platform. VirtualPlant enables scientists to visualize, integrate, and analyze genomic data from a systems biology perspective. VirtualPlant integrates genome-wide data concerning the known and predicted relationships among genes, proteins, and molecules, as well as genome-scale experimental measurements. VirtualPlant also provides visualization techniques that render multivariate information in visual formats that facilitate the extraction of biological concepts. Importantly, VirtualPlant helps biologists who are not trained in computer science to mine lists of genes, microarray experiments, and gene networks to address questions in plant biology, such as: What are the molecular mechanisms by which internal or external perturbations affect processes controlling growth and development? We illustrate the use of VirtualPlant with three case studies, ranging from querying a gene of interest to the identification of gene networks and regulatory hubs that control seed development. Whereas the VirtualPlant software was developed to mine Arabidopsis (Arabidopsis thaliana) genomic data, its data structures, algorithms, and visualization tools are designed in a species-independent way. VirtualPlant is freely available at www.virtualplant.org. PMID:20007449

D-peaks: a visual tool to display ChIP-seq peaks along the genome.

PubMed

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.

Methods, Tools and Current Perspectives in Proteogenomics *

PubMed Central

Ruggles, Kelly V.; Krug, Karsten; Wang, Xiaojing; Clauser, Karl R.; Wang, Jing; Payne, Samuel H.; Fenyö, David; Zhang, Bing; Mani, D. R.

2017-01-01

With combined technological advancements in high-throughput next-generation sequencing and deep mass spectrometry-based proteomics, proteogenomics, i.e. the integrative analysis of proteomic and genomic data, has emerged as a new research field. Early efforts in the field were focused on improving protein identification using sample-specific genomic and transcriptomic sequencing data. More recently, integrative analysis of quantitative measurements from genomic and proteomic studies have identified novel insights into gene expression regulation, cell signaling, and disease. Many methods and tools have been developed or adapted to enable an array of integrative proteogenomic approaches and in this article, we systematically classify published methods and tools into four major categories, (1) Sequence-centric proteogenomics; (2) Analysis of proteogenomic relationships; (3) Integrative modeling of proteogenomic data; and (4) Data sharing and visualization. We provide a comprehensive review of methods and available tools in each category and highlight their typical applications. PMID:28456751

CRISPR-Cas Genome Surgery in Ophthalmology

PubMed Central

DiCarlo, James E.; Sengillo, Jesse D.; Justus, Sally; Cabral, Thiago; Tsang, Stephen H.; Mahajan, Vinit B.

2017-01-01

Genetic disease affecting vision can significantly impact patient quality of life. Gene therapy seeks to slow the progression of these diseases by treating the underlying etiology at the level of the genome. Clustered regularly interspaced short palindromic repeats (CRISPR) and CRISPR-associated systems (Cas) represent powerful tools for studying diseases through the creation of model organisms generated by targeted modification and by the correction of disease mutations for therapeutic purposes. CRISPR-Cas systems have been applied successfully to the visual sciences and study of ophthalmic disease – from the modification of zebrafish and mammalian models of eye development and disease, to the correction of pathogenic mutations in patient-derived stem cells. Recent advances in CRISPR-Cas delivery and optimization boast improved functionality that continues to enhance genome-engineering applications in the eye. This review provides a synopsis of the recent implementations of CRISPR-Cas tools in the field of ophthalmology. PMID:28573077

Explore, Visualize, and Analyze Functional Cancer Proteomic Data Using the Cancer Proteome Atlas. | Office of Cancer Genomics

Cancer.gov

Reverse-phase protein arrays (RPPA) represent a powerful functional proteomic approach to elucidate cancer-related molecular mechanisms and to develop novel cancer therapies. To facilitate community-based investigation of the large-scale protein expression data generated by this platform, we have developed a user-friendly, open-access bioinformatic resource, The Cancer Proteome Atlas (TCPA, http://tcpaportal.org), which contains two separate web applications.

AGORA : Organellar genome annotation from the amino acid and nucleotide references.

PubMed

Jung, Jaehee; Kim, Jong Im; Jeong, Young-Sik; Yi, Gangman

2018-03-29

Next-generation sequencing (NGS) technologies have led to the accumulation of highthroughput sequence data from various organisms in biology. To apply gene annotation of organellar genomes for various organisms, more optimized tools for functional gene annotation are required. Almost all gene annotation tools are mainly focused on the chloroplast genome of land plants or the mitochondrial genome of animals.We have developed a web application AGORA for the fast, user-friendly, and improved annotations of organellar genomes. AGORA annotates genes based on a BLAST-based homology search and clustering with selected reference sequences from the NCBI database or user-defined uploaded data. AGORA can annotate the functional genes in almost all mitochondrion and plastid genomes of eukaryotes. The gene annotation of a genome with an exon-intron structure within a gene or inverted repeat region is also available. It provides information of start and end positions of each gene, BLAST results compared with the reference sequence, and visualization of gene map by OGDRAW. Users can freely use the software, and the accessible URL is https://bigdata.dongguk.edu/gene_project/AGORA/.The main module of the tool is implemented by the python and php, and the web page is built by the HTML and CSS to support all browsers. gangman@dongguk.edu.

DEApp: an interactive web interface for differential expression analysis of next generation sequence data.

PubMed

Li, Yan; Andrade, Jorge

2017-01-01

A growing trend in the biomedical community is the use of Next Generation Sequencing (NGS) technologies in genomics research. The complexity of downstream differential expression (DE) analysis is however still challenging, as it requires sufficient computer programing and command-line knowledge. Furthermore, researchers often need to evaluate and visualize interactively the effect of using differential statistical and error models, assess the impact of selecting different parameters and cutoffs, and finally explore the overlapping consensus of cross-validated results obtained with different methods. This represents a bottleneck that slows down or impedes the adoption of NGS technologies in many labs. We developed DEApp, an interactive and dynamic web application for differential expression analysis of count based NGS data. This application enables models selection, parameter tuning, cross validation and visualization of results in a user-friendly interface. DEApp enables labs with no access to full time bioinformaticians to exploit the advantages of NGS applications in biomedical research. This application is freely available at https://yanli.shinyapps.io/DEAppand https://gallery.shinyapps.io/DEApp.

Open source bioimage informatics for cell biology.

PubMed

Swedlow, Jason R; Eliceiri, Kevin W

2009-11-01

Significant technical advances in imaging, molecular biology and genomics have fueled a revolution in cell biology, in that the molecular and structural processes of the cell are now visualized and measured routinely. Driving much of this recent development has been the advent of computational tools for the acquisition, visualization, analysis and dissemination of these datasets. These tools collectively make up a new subfield of computational biology called bioimage informatics, which is facilitated by open source approaches. We discuss why open source tools for image informatics in cell biology are needed, some of the key general attributes of what make an open source imaging application successful, and point to opportunities for further operability that should greatly accelerate future cell biology discovery.

Integrative Genomics Viewer (IGV) | Informatics Technology for Cancer Research (ITCR)

Cancer.gov

The Integrative Genomics Viewer (IGV) is a high-performance visualization tool for interactive exploration of large, integrated genomic datasets. It supports a wide variety of data types, including array-based and next-generation sequence data, and genomic annotations.

Using Galaxy to Perform Large-Scale Interactive Data Analyses

PubMed Central

Hillman-Jackson, Jennifer; Clements, Dave; Blankenberg, Daniel; Taylor, James; Nekrutenko, Anton

2012-01-01

Innovations in biomedical research technologies continue to provide experimental biologists with novel and increasingly large genomic and high-throughput data resources to be analyzed. As creating and obtaining data has become easier, the key decision faced by many researchers is a practical one: where and how should an analysis be performed? Datasets are large and analysis tool set-up and use is riddled with complexities outside of the scope of core research activities. The authors believe that Galaxy (galaxyproject.org) provides a powerful solution that simplifies data acquisition and analysis in an intuitive web-application, granting all researchers access to key informatics tools previously only available to computational specialists working in Unix-based environments. We will demonstrate through a series of biomedically relevant protocols how Galaxy specifically brings together 1) data retrieval from public and private sources, for example, UCSC’s Eukaryote and Microbial Genome Browsers (genome.ucsc.edu), 2) custom tools (wrapped Unix functions, format standardization/conversions, interval operations) and 3rd party analysis tools, for example, Bowtie/Tuxedo Suite (bowtie-bio.sourceforge.net), Lastz (www.bx.psu.edu/~rsharris/lastz/), SAMTools (samtools.sourceforge.net), FASTX-toolkit (hannonlab.cshl.edu/fastx_toolkit), and MACS (liulab.dfci.harvard.edu/MACS), and creates results formatted for visualization in tools such as the Galaxy Track Browser (GTB, galaxyproject.org/wiki/Learn/Visualization), UCSC Genome Browser (genome.ucsc.edu), Ensembl (www.ensembl.org), and GeneTrack (genetrack.bx.psu.edu). Galaxy rapidly has become the most popular choice for integrated next generation sequencing (NGS) analytics and collaboration, where users can perform, document, and share complex analysis within a single interface in an unprecedented number of ways. PMID:18428782

Informing the Design of Direct-to-Consumer Interactive Personal Genomics Reports

PubMed Central

Shaer, Orit; Okerlund, Johanna; Balestra, Martina; Stowell, Elizabeth; Ascher, Laura; Bi, Joanna; Schlenker, Claire; Ball, Madeleine

2015-01-01

Background In recent years, people who sought direct-to-consumer genetic testing services have been increasingly confronted with an unprecedented amount of personal genomic information, which influences their decisions, emotional state, and well-being. However, these users of direct-to-consumer genetic services, who vary in their education and interests, frequently have little relevant experience or tools for understanding, reasoning about, and interacting with their personal genomic data. Online interactive techniques can play a central role in making personal genomic data useful for these users. Objective We sought to (1) identify the needs of diverse users as they make sense of their personal genomic data, (2) consequently develop effective interactive visualizations of genomic trait data to address these users’ needs, and (3) evaluate the effectiveness of the developed visualizations in facilitating comprehension. Methods The first two user studies, conducted with 63 volunteers in the Personal Genome Project and with 36 personal genomic users who participated in a design workshop, respectively, employed surveys and interviews to identify the needs and expectations of diverse users. Building on the two initial studies, the third study was conducted with 730 Amazon Mechanical Turk users and employed a controlled experimental design to examine the effectiveness of different design interventions on user comprehension. Results The first two studies identified searching, comparing, sharing, and organizing data as fundamental to users’ understanding of personal genomic data. The third study demonstrated that interactive and visual design interventions could improve the understandability of personal genomic reports for consumers. In particular, results showed that a new interactive bubble chart visualization designed for the study resulted in the highest comprehension scores, as well as the highest perceived comprehension scores. These scores were significantly higher than scores received using the industry standard tabular reports currently used for communicating personal genomic information. Conclusions Drawing on multiple research methods and populations, the findings of the studies reported in this paper offer deep understanding of users’ needs and practices, and demonstrate that interactive online design interventions can improve the understandability of personal genomic reports for consumers. We discuss implications for designers and researchers. PMID:26070951

Informing the Design of Direct-to-Consumer Interactive Personal Genomics Reports.

PubMed

Shaer, Orit; Nov, Oded; Okerlund, Johanna; Balestra, Martina; Stowell, Elizabeth; Ascher, Laura; Bi, Joanna; Schlenker, Claire; Ball, Madeleine

2015-06-12

In recent years, people who sought direct-to-consumer genetic testing services have been increasingly confronted with an unprecedented amount of personal genomic information, which influences their decisions, emotional state, and well-being. However, these users of direct-to-consumer genetic services, who vary in their education and interests, frequently have little relevant experience or tools for understanding, reasoning about, and interacting with their personal genomic data. Online interactive techniques can play a central role in making personal genomic data useful for these users. We sought to (1) identify the needs of diverse users as they make sense of their personal genomic data, (2) consequently develop effective interactive visualizations of genomic trait data to address these users' needs, and (3) evaluate the effectiveness of the developed visualizations in facilitating comprehension. The first two user studies, conducted with 63 volunteers in the Personal Genome Project and with 36 personal genomic users who participated in a design workshop, respectively, employed surveys and interviews to identify the needs and expectations of diverse users. Building on the two initial studies, the third study was conducted with 730 Amazon Mechanical Turk users and employed a controlled experimental design to examine the effectiveness of different design interventions on user comprehension. The first two studies identified searching, comparing, sharing, and organizing data as fundamental to users' understanding of personal genomic data. The third study demonstrated that interactive and visual design interventions could improve the understandability of personal genomic reports for consumers. In particular, results showed that a new interactive bubble chart visualization designed for the study resulted in the highest comprehension scores, as well as the highest perceived comprehension scores. These scores were significantly higher than scores received using the industry standard tabular reports currently used for communicating personal genomic information. Drawing on multiple research methods and populations, the findings of the studies reported in this paper offer deep understanding of users' needs and practices, and demonstrate that interactive online design interventions can improve the understandability of personal genomic reports for consumers. We discuss implications for designers and researchers.

CoryneRegNet: an ontology-based data warehouse of corynebacterial transcription factors and regulatory networks.

PubMed

Baumbach, Jan; Brinkrolf, Karina; Czaja, Lisa F; Rahmann, Sven; Tauch, Andreas

2006-02-14

The application of DNA microarray technology in post-genomic analysis of bacterial genome sequences has allowed the generation of huge amounts of data related to regulatory networks. This data along with literature-derived knowledge on regulation of gene expression has opened the way for genome-wide reconstruction of transcriptional regulatory networks. These large-scale reconstructions can be converted into in silico models of bacterial cells that allow a systematic analysis of network behavior in response to changing environmental conditions. CoryneRegNet was designed to facilitate the genome-wide reconstruction of transcriptional regulatory networks of corynebacteria relevant in biotechnology and human medicine. During the import and integration process of data derived from experimental studies or literature knowledge CoryneRegNet generates links to genome annotations, to identified transcription factors and to the corresponding cis-regulatory elements. CoryneRegNet is based on a multi-layered, hierarchical and modular concept of transcriptional regulation and was implemented by using the relational database management system MySQL and an ontology-based data structure. Reconstructed regulatory networks can be visualized by using the yFiles JAVA graph library. As an application example of CoryneRegNet, we have reconstructed the global transcriptional regulation of a cellular module involved in SOS and stress response of corynebacteria. CoryneRegNet is an ontology-based data warehouse that allows a pertinent data management of regulatory interactions along with the genome-scale reconstruction of transcriptional regulatory networks. These models can further be combined with metabolic networks to build integrated models of cellular function including both metabolism and its transcriptional regulation.

An automated graphics tool for comparative genomics: the Coulson plot generator

PubMed Central

2013-01-01

Background Comparative analysis is an essential component to biology. When applied to genomics for example, analysis may require comparisons between the predicted presence and absence of genes in a group of genomes under consideration. Frequently, genes can be grouped into small categories based on functional criteria, for example membership of a multimeric complex, participation in a metabolic or signaling pathway or shared sequence features and/or paralogy. These patterns of retention and loss are highly informative for the prediction of function, and hence possible biological context, and can provide great insights into the evolutionary history of cellular functions. However, representation of such information in a standard spreadsheet is a poor visual means from which to extract patterns within a dataset. Results We devised the Coulson Plot, a new graphical representation that exploits a matrix of pie charts to display comparative genomics data. Each pie is used to describe a complex or process from a separate taxon, and is divided into sectors corresponding to the number of proteins (subunits) in a complex/process. The predicted presence or absence of proteins in each complex are delineated by occupancy of a given sector; this format is visually highly accessible and makes pattern recognition rapid and reliable. A key to the identity of each subunit, plus hierarchical naming of taxa and coloring are included. A java-based application, the Coulson plot generator (CPG) automates graphic production, with a tab or comma-delineated text file as input and generating an editable portable document format or svg file. Conclusions CPG software may be used to rapidly convert spreadsheet data to a graphical matrix pie chart format. The representation essentially retains all of the information from the spreadsheet but presents a graphically rich format making comparisons and identification of patterns significantly clearer. While the Coulson plot format is highly useful in comparative genomics, its original purpose, the software can be used to visualize any dataset where entity occupancy is compared between different classes. Availability CPG software is available at sourceforge http://sourceforge.net/projects/coulson and http://dl.dropbox.com/u/6701906/Web/Sites/Labsite/CPG.html PMID:23621955

fluff: exploratory analysis and visualization of high-throughput sequencing data

PubMed Central

Georgiou, Georgios

2016-01-01

Summary. In this article we describe fluff, a software package that allows for simple exploration, clustering and visualization of high-throughput sequencing data mapped to a reference genome. The package contains three command-line tools to generate publication-quality figures in an uncomplicated manner using sensible defaults. Genome-wide data can be aggregated, clustered and visualized in a heatmap, according to different clustering methods. This includes a predefined setting to identify dynamic clusters between different conditions or developmental stages. Alternatively, clustered data can be visualized in a bandplot. Finally, fluff includes a tool to generate genomic profiles. As command-line tools, the fluff programs can easily be integrated into standard analysis pipelines. The installation is straightforward and documentation is available at http://fluff.readthedocs.org. Availability. fluff is implemented in Python and runs on Linux. The source code is freely available for download at https://github.com/simonvh/fluff. PMID:27547532

MSeqDR: A Centralized Knowledge Repository and Bioinformatics Web Resource to Facilitate Genomic Investigations in Mitochondrial Disease.

PubMed

Shen, Lishuang; Diroma, Maria Angela; Gonzalez, Michael; Navarro-Gomez, Daniel; Leipzig, Jeremy; Lott, Marie T; van Oven, Mannis; Wallace, Douglas C; Muraresku, Colleen Clarke; Zolkipli-Cunningham, Zarazuela; Chinnery, Patrick F; Attimonelli, Marcella; Zuchner, Stephan; Falk, Marni J; Gai, Xiaowu

2016-06-01

MSeqDR is the Mitochondrial Disease Sequence Data Resource, a centralized and comprehensive genome and phenome bioinformatics resource built by the mitochondrial disease community to facilitate clinical diagnosis and research investigations of individual patient phenotypes, genomes, genes, and variants. A central Web portal (https://mseqdr.org) integrates community knowledge from expert-curated databases with genomic and phenotype data shared by clinicians and researchers. MSeqDR also functions as a centralized application server for Web-based tools to analyze data across both mitochondrial and nuclear DNA, including investigator-driven whole exome or genome dataset analyses through MSeqDR-Genesis. MSeqDR-GBrowse genome browser supports interactive genomic data exploration and visualization with custom tracks relevant to mtDNA variation and mitochondrial disease. MSeqDR-LSDB is a locus-specific database that currently manages 178 mitochondrial diseases, 1,363 genes associated with mitochondrial biology or disease, and 3,711 pathogenic variants in those genes. MSeqDR Disease Portal allows hierarchical tree-style disease exploration to evaluate their unique descriptions, phenotypes, and causative variants. Automated genomic data submission tools are provided that capture ClinVar compliant variant annotations. PhenoTips will be used for phenotypic data submission on deidentified patients using human phenotype ontology terminology. The development of a dynamic informed patient consent process to guide data access is underway to realize the full potential of these resources. © 2016 WILEY PERIODICALS, INC.

Visualization of genome signatures of eukaryote genomes by batch-learning self-organizing map with a special emphasis on Drosophila genomes.

PubMed

Abe, Takashi; Hamano, Yuta; Ikemura, Toshimichi

2014-01-01

A strategy of evolutionary studies that can compare vast numbers of genome sequences is becoming increasingly important with the remarkable progress of high-throughput DNA sequencing methods. We previously established a sequence alignment-free clustering method "BLSOM" for di-, tri-, and tetranucleotide compositions in genome sequences, which can characterize sequence characteristics (genome signatures) of a wide range of species. In the present study, we generated BLSOMs for tetra- and pentanucleotide compositions in approximately one million sequence fragments derived from 101 eukaryotes, for which almost complete genome sequences were available. BLSOM recognized phylotype-specific characteristics (e.g., key combinations of oligonucleotide frequencies) in the genome sequences, permitting phylotype-specific clustering of the sequences without any information regarding the species. In our detailed examination of 12 Drosophila species, the correlation between their phylogenetic classification and the classification on the BLSOMs was observed to visualize oligonucleotides diagnostic for species-specific clustering.

EDGAR: A software framework for the comparative analysis of prokaryotic genomes

PubMed Central

Blom, Jochen; Albaum, Stefan P; Doppmeier, Daniel; Pühler, Alfred; Vorhölter, Frank-Jörg; Zakrzewski, Martha; Goesmann, Alexander

2009-01-01

Background The introduction of next generation sequencing approaches has caused a rapid increase in the number of completely sequenced genomes. As one result of this development, it is now feasible to analyze large groups of related genomes in a comparative approach. A main task in comparative genomics is the identification of orthologous genes in different genomes and the classification of genes as core genes or singletons. Results To support these studies EDGAR – "Efficient Database framework for comparative Genome Analyses using BLAST score Ratios" – was developed. EDGAR is designed to automatically perform genome comparisons in a high throughput approach. Comparative analyses for 582 genomes across 75 genus groups taken from the NCBI genomes database were conducted with the software and the results were integrated into an underlying database. To demonstrate a specific application case, we analyzed ten genomes of the bacterial genus Xanthomonas, for which phylogenetic studies were awkward due to divergent taxonomic systems. The resultant phylogeny EDGAR provided was consistent with outcomes from traditional approaches performed recently and moreover, it was possible to root each strain with unprecedented accuracy. Conclusion EDGAR provides novel analysis features and significantly simplifies the comparative analysis of related genomes. The software supports a quick survey of evolutionary relationships and simplifies the process of obtaining new biological insights into the differential gene content of kindred genomes. Visualization features, like synteny plots or Venn diagrams, are offered to the scientific community through a web-based and therefore platform independent user interface , where the precomputed data sets can be browsed. PMID:19457249

GenomeFingerprinter: the genome fingerprint and the universal genome fingerprint analysis for systematic comparative genomics.

PubMed

Ai, Yuncan; Ai, Hannan; Meng, Fanmei; Zhao, Lei

2013-01-01

No attention has been paid on comparing a set of genome sequences crossing genetic components and biological categories with far divergence over large size range. We define it as the systematic comparative genomics and aim to develop the methodology. First, we create a method, GenomeFingerprinter, to unambiguously produce a set of three-dimensional coordinates from a sequence, followed by one three-dimensional plot and six two-dimensional trajectory projections, to illustrate the genome fingerprint of a given genome sequence. Second, we develop a set of concepts and tools, and thereby establish a method called the universal genome fingerprint analysis (UGFA). Particularly, we define the total genetic component configuration (TGCC) (including chromosome, plasmid, and phage) for describing a strain as a systematic unit, the universal genome fingerprint map (UGFM) of TGCC for differentiating strains as a universal system, and the systematic comparative genomics (SCG) for comparing a set of genomes crossing genetic components and biological categories. Third, we construct a method of quantitative analysis to compare two genomes by using the outcome dataset of genome fingerprint analysis. Specifically, we define the geometric center and its geometric mean for a given genome fingerprint map, followed by the Euclidean distance, the differentiate rate, and the weighted differentiate rate to quantitatively describe the difference between two genomes of comparison. Moreover, we demonstrate the applications through case studies on various genome sequences, giving tremendous insights into the critical issues in microbial genomics and taxonomy. We have created a method, GenomeFingerprinter, for rapidly computing, geometrically visualizing, intuitively comparing a set of genomes at genome fingerprint level, and hence established a method called the universal genome fingerprint analysis, as well as developed a method of quantitative analysis of the outcome dataset. These have set up the methodology of systematic comparative genomics based on the genome fingerprint analysis.

Metabolome searcher: a high throughput tool for metabolite identification and metabolic pathway mapping directly from mass spectrometry and using genome restriction.

PubMed

Dhanasekaran, A Ranjitha; Pearson, Jon L; Ganesan, Balasubramanian; Weimer, Bart C

2015-02-25

Mass spectrometric analysis of microbial metabolism provides a long list of possible compounds. Restricting the identification of the possible compounds to those produced by the specific organism would benefit the identification process. Currently, identification of mass spectrometry (MS) data is commonly done using empirically derived compound databases. Unfortunately, most databases contain relatively few compounds, leaving long lists of unidentified molecules. Incorporating genome-encoded metabolism enables MS output identification that may not be included in databases. Using an organism's genome as a database restricts metabolite identification to only those compounds that the organism can produce. To address the challenge of metabolomic analysis from MS data, a web-based application to directly search genome-constructed metabolic databases was developed. The user query returns a genome-restricted list of possible compound identifications along with the putative metabolic pathways based on the name, formula, SMILES structure, and the compound mass as defined by the user. Multiple queries can be done simultaneously by submitting a text file created by the user or obtained from the MS analysis software. The user can also provide parameters specific to the experiment's MS analysis conditions, such as mass deviation, adducts, and detection mode during the query so as to provide additional levels of evidence to produce the tentative identification. The query results are provided as an HTML page and downloadable text file of possible compounds that are restricted to a specific genome. Hyperlinks provided in the HTML file connect the user to the curated metabolic databases housed in ProCyc, a Pathway Tools platform, as well as the KEGG Pathway database for visualization and metabolic pathway analysis. Metabolome Searcher, a web-based tool, facilitates putative compound identification of MS output based on genome-restricted metabolic capability. This enables researchers to rapidly extend the possible identifications of large data sets for metabolites that are not in compound databases. Putative compound names with their associated metabolic pathways from metabolomics data sets are returned to the user for additional biological interpretation and visualization. This novel approach enables compound identification by restricting the possible masses to those encoded in the genome.

STAR: an integrated solution to management and visualization of sequencing data.

PubMed

Wang, Tao; Liu, Jie; Shen, Li; Tonti-Filippini, Julian; Zhu, Yun; Jia, Haiyang; Lister, Ryan; Whitaker, John W; Ecker, Joseph R; Millar, A Harvey; Ren, Bing; Wang, Wei

2013-12-15

Easily visualization of complex data features is a necessary step to conduct studies on next-generation sequencing (NGS) data. We developed STAR, an integrated web application that enables online management, visualization and track-based analysis of NGS data. STAR is a multilayer web service system. On the client side, STAR leverages JavaScript, HTML5 Canvas and asynchronous communications to deliver a smoothly scrolling desktop-like graphical user interface with a suite of in-browser analysis tools that range from providing simple track configuration controls to sophisticated feature detection within datasets. On the server side, STAR supports private session state retention via an account management system and provides data management modules that enable collection, visualization and analysis of third-party sequencing data from the public domain with over thousands of tracks hosted to date. Overall, STAR represents a next-generation data exploration solution to match the requirements of NGS data, enabling both intuitive visualization and dynamic analysis of data. STAR browser system is freely available on the web at http://wanglab.ucsd.edu/star/browser and https://github.com/angell1117/STAR-genome-browser.

Genovar: a detection and visualization tool for genomic variants.

PubMed

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/.

Tomato functional genomics database (TFGD): a comprehensive collection and analysis package for tomato functional genomics

USDA-ARS?s Scientific Manuscript database

Tomato Functional Genomics Database (TFGD; http://ted.bti.cornell.edu) provides a comprehensive systems biology resource to store, mine, analyze, visualize and integrate large-scale tomato functional genomics datasets. The database is expanded from the previously described Tomato Expression Database...

GenomicusPlants: a web resource to study genome evolution in flowering plants.

PubMed

Louis, Alexandra; Murat, Florent; Salse, Jérôme; Crollius, Hugues Roest

2015-01-01

Comparative genomics combined with phylogenetic reconstructions are powerful approaches to study the evolution of genes and genomes. However, the current rapid expansion of the volume of genomic information makes it increasingly difficult to interrogate, integrate and synthesize comparative genome data while taking into account the maximum breadth of information available. GenomicusPlants (http://www.genomicus.biologie.ens.fr/genomicus-plants) is an extension of the Genomicus webserver that addresses this issue by allowing users to explore flowering plant genomes in an intuitive way, across the broadest evolutionary scales. Extant genomes of 26 flowering plants can be analyzed, as well as 23 ancestral reconstructed genomes. Ancestral gene order provides a long-term chronological view of gene order evolution, greatly facilitating comparative genomics and evolutionary studies. Four main interfaces ('views') are available where: (i) PhyloView combines phylogenetic trees with comparisons of genomic loci across any number of genomes; (ii) AlignView projects loci of interest against all other genomes to visualize its topological conservation; (iii) MatrixView compares two genomes in a classical dotplot representation; and (iv) Karyoview visualizes chromosome karyotypes 'painted' with colours of another genome of interest. All four views are interconnected and benefit from many customizable features. © The Author 2014. Published by Oxford University Press on behalf of Japanese Society of Plant Physiologists.

Epiviz: a view inside the design of an integrated visual analysis software for genomics

PubMed Central

2015-01-01

Background Computational and visual data analysis for genomics has traditionally involved a combination of tools and resources, of which the most ubiquitous consist of genome browsers, focused mainly on integrative visualization of large numbers of big datasets, and computational environments, focused on data modeling of a small number of moderately sized datasets. Workflows that involve the integration and exploration of multiple heterogeneous data sources, small and large, public and user specific have been poorly addressed by these tools. In our previous work, we introduced Epiviz, which bridges the gap between the two types of tools, simplifying these workflows. Results In this paper we expand on the design decisions behind Epiviz, and introduce a series of new advanced features that further support the type of interactive exploratory workflow we have targeted. We discuss three ways in which Epiviz advances the field of genomic data analysis: 1) it brings code to interactive visualizations at various different levels; 2) takes the first steps in the direction of collaborative data analysis by incorporating user plugins from source control providers, as well as by allowing analysis states to be shared among the scientific community; 3) combines established analysis features that have never before been available simultaneously in a genome browser. In our discussion section, we present security implications of the current design, as well as a series of limitations and future research steps. Conclusions Since many of the design choices of Epiviz are novel in genomics data analysis, this paper serves both as a document of our own approaches with lessons learned, as well as a start point for future efforts in the same direction for the genomics community. PMID:26328750

The Genome Portal of the Department of Energy Joint Genome Institute

DOE Office of Scientific and Technical Information (OSTI.GOV)

Nordberg, Henrik; Cantor, Michael; Dushekyo, Serge

2014-03-14

The JGI Genome Portal (http://genome.jgi.doe.gov) provides unified access to all JGI genomic databases and analytical tools. A user can search, download and explore multiple data sets available for all DOE JGI sequencing projects including their status, assemblies and annotations of sequenced genomes. Genome Portal in the past 2 years was significantly updated, with a specific emphasis on efficient handling of the rapidly growing amount of diverse genomic data accumulated in JGI. A critical aspect of handling big data in genomics is the development of visualization and analysis tools that allow scientists to derive meaning from what are otherwise terrabases ofmore » inert sequence. An interactive visualization tool developed in the group allows us to explore contigs resulting from a single metagenome assembly. Implemented with modern web technologies that take advantage of the power of the computer's graphical processing unit (gpu), the tool allows the user to easily navigate over a 100,000 data points in multiple dimensions, among many biologically meaningful parameters of a dataset such as relative abundance, contig length, and G+C content.« less

GPU Accelerated Browser for Neuroimaging Genomics.

PubMed

Zigon, Bob; Li, Huang; Yao, Xiaohui; Fang, Shiaofen; Hasan, Mohammad Al; Yan, Jingwen; Moore, Jason H; Saykin, Andrew J; Shen, Li

2018-04-25

Neuroimaging genomics is an emerging field that provides exciting opportunities to understand the genetic basis of brain structure and function. The unprecedented scale and complexity of the imaging and genomics data, however, have presented critical computational bottlenecks. In this work we present our initial efforts towards building an interactive visual exploratory system for mining big data in neuroimaging genomics. A GPU accelerated browsing tool for neuroimaging genomics is created that implements the ANOVA algorithm for single nucleotide polymorphism (SNP) based analysis and the VEGAS algorithm for gene-based analysis, and executes them at interactive rates. The ANOVA algorithm is 110 times faster than the 4-core OpenMP version, while the VEGAS algorithm is 375 times faster than its 4-core OpenMP counter part. This approach lays a solid foundation for researchers to address the challenges of mining large-scale imaging genomics datasets via interactive visual exploration.

Gigwa-Genotype investigator for genome-wide analyses.

PubMed

Sempéré, Guilhem; Philippe, Florian; Dereeper, Alexis; Ruiz, Manuel; Sarah, Gautier; Larmande, Pierre

2016-06-06

Exploring the structure of genomes and analyzing their evolution is essential to understanding the ecological adaptation of organisms. However, with the large amounts of data being produced by next-generation sequencing, computational challenges arise in terms of storage, search, sharing, analysis and visualization. This is particularly true with regards to studies of genomic variation, which are currently lacking scalable and user-friendly data exploration solutions. Here we present Gigwa, a web-based tool that provides an easy and intuitive way to explore large amounts of genotyping data by filtering it not only on the basis of variant features, including functional annotations, but also on genotype patterns. The data storage relies on MongoDB, which offers good scalability properties. Gigwa can handle multiple databases and may be deployed in either single- or multi-user mode. In addition, it provides a wide range of popular export formats. The Gigwa application is suitable for managing large amounts of genomic variation data. Its user-friendly web interface makes such processing widely accessible. It can either be simply deployed on a workstation or be used to provide a shared data portal for a given community of researchers.

Genomicus 2018: karyotype evolutionary trees and on-the-fly synteny computing

PubMed Central

Nguyen, Nga Thi Thuy; Vincens, Pierre

2018-01-01

Abstract Since 2010, the Genomicus web server is available online at http://genomicus.biologie.ens.fr/genomicus. This graphical browser provides access to comparative genomic analyses in four different phyla (Vertebrate, Plants, Fungi, and non vertebrate Metazoans). Users can analyse genomic information from extant species, as well as ancestral gene content and gene order for vertebrates and flowering plants, in an integrated evolutionary context. New analyses and visualization tools have recently been implemented in Genomicus Vertebrate. Karyotype structures from several genomes can now be compared along an evolutionary pathway (Multi-KaryotypeView), and synteny blocks can be computed and visualized between any two genomes (PhylDiagView). PMID:29087490

Open source bioimage informatics for cell biology

PubMed Central

Swedlow, Jason R.; Eliceiri, Kevin W.

2009-01-01

Significant technical advances in imaging, molecular biology and genomics have fueled a revolution in cell biology, in that the molecular and structural processes of the cell are now visualized and measured routinely. Driving much of this recent development has been the advent of computational tools for the acquisition, visualization, analysis and dissemination of these datasets. These tools collectively make up a new subfield of computational biology called bioimage informatics, which is facilitated by open source approaches. We discuss why open source tools for image informatics in cell biology are needed, some of the key general attributes of what make an open source imaging application successful, and point to opportunities for further operability that should greatly accelerate future cell biology discovery. PMID:19833518

GoIFISH: a system for the quantification of single cell heterogeneity from IFISH images.

PubMed

Trinh, Anne; Rye, Inga H; Almendro, Vanessa; Helland, Aslaug; Russnes, Hege G; Markowetz, Florian

2014-08-26

Molecular analysis has revealed extensive intra-tumor heterogeneity in human cancer samples, but cannot identify cell-to-cell variations within the tissue microenvironment. In contrast, in situ analysis can identify genetic aberrations in phenotypically defined cell subpopulations while preserving tissue-context specificity. GoIFISHGoIFISH is a widely applicable, user-friendly system tailored for the objective and semi-automated visualization, detection and quantification of genomic alterations and protein expression obtained from fluorescence in situ analysis. In a sample set of HER2-positive breast cancers GoIFISHGoIFISH is highly robust in visual analysis and its accuracy compares favorably to other leading image analysis methods. GoIFISHGoIFISH is freely available at www.sourceforge.net/projects/goifish/.

MSeqDR: A Centralized Knowledge Repository and Bioinformatics Web Resource to Facilitate Genomic Investigations in Mitochondrial Disease

PubMed Central

Shen, Lishuang; Diroma, Maria Angela; Gonzalez, Michael; Navarro-Gomez, Daniel; Leipzig, Jeremy; Lott, Marie T.; van Oven, Mannis; Wallace, Douglas C.; Muraresku, Colleen Clarke; Zolkipli-Cunningham, Zarazuela; Chinnery, Patrick F.; Attimonelli, Marcella; Zuchner, Stephan

2016-01-01

MSeqDR is the Mitochondrial Disease Sequence Data Resource, a centralized and comprehensive genome and phenome bioinformatics resource built by the mitochondrial disease community to facilitate clinical diagnosis and research investigations of individual patient phenotypes, genomes, genes, and variants. A central Web portal (https://mseqdr.org) integrates community knowledge from expert-curated databases with genomic and phenotype data shared by clinicians and researchers. MSeqDR also functions as a centralized application server for Web-based tools to analyze data across both mitochondrial and nuclear DNA, including investigator-driven whole exome or genome dataset analyses through MSeqDR-Genesis. MSeqDR-GBrowse supports interactive genomic data exploration and visualization with custom tracks relevant to mtDNA variation and disease. MSeqDR-LSDB is a locus specific database that currently manages 178 mitochondrial diseases, 1,363 genes associated with mitochondrial biology or disease, and 3,711 pathogenic variants in those genes. MSeqDR Disease Portal allows hierarchical tree-style disease exploration to evaluate their unique descriptions, phenotypes, and causative variants. Automated genomic data submission tools are provided that capture ClinVar-compliant variant annotations. PhenoTips is used for phenotypic data submission on de-identified patients using human phenotype ontology terminology. Development of a dynamic informed patient consent process to guide data access is underway to realize the full potential of these resources. PMID:26919060

The UCSC genome browser and associated tools

PubMed Central

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.

PubMed

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.

GenExp: an interactive web-based genomic DAS client with client-side data rendering.

PubMed

Gel Moreno, Bernat; Messeguer Peypoch, Xavier

2011-01-01

The Distributed Annotation System (DAS) offers a standard protocol for sharing and integrating annotations on biological sequences. There are more than 1000 DAS sources available and the number is steadily increasing. Clients are an essential part of the DAS system and integrate data from several independent sources in order to create a useful representation to the user. While web-based DAS clients exist, most of them do not have direct interaction capabilities such as dragging and zooming with the mouse. Here we present GenExp, a web based and fully interactive visual DAS client. GenExp is a genome oriented DAS client capable of creating informative representations of genomic data zooming out from base level to complete chromosomes. It proposes a novel approach to genomic data rendering and uses the latest HTML5 web technologies to create the data representation inside the client browser. Thanks to client-side rendering most position changes do not need a network request to the server and so responses to zooming and panning are almost immediate. In GenExp it is possible to explore the genome intuitively moving it with the mouse just like geographical map applications. Additionally, in GenExp it is possible to have more than one data viewer at the same time and to save the current state of the application to revisit it later on. GenExp is a new interactive web-based client for DAS and addresses some of the short-comings of the existing clients. It uses client-side data rendering techniques resulting in easier genome browsing and exploration. GenExp is open source under the GPL license and it is freely available at http://gralggen.lsi.upc.edu/recerca/genexp.

CoryneRegNet: An ontology-based data warehouse of corynebacterial transcription factors and regulatory networks

PubMed Central

Baumbach, Jan; Brinkrolf, Karina; Czaja, Lisa F; Rahmann, Sven; Tauch, Andreas

2006-01-01

Background The application of DNA microarray technology in post-genomic analysis of bacterial genome sequences has allowed the generation of huge amounts of data related to regulatory networks. This data along with literature-derived knowledge on regulation of gene expression has opened the way for genome-wide reconstruction of transcriptional regulatory networks. These large-scale reconstructions can be converted into in silico models of bacterial cells that allow a systematic analysis of network behavior in response to changing environmental conditions. Description CoryneRegNet was designed to facilitate the genome-wide reconstruction of transcriptional regulatory networks of corynebacteria relevant in biotechnology and human medicine. During the import and integration process of data derived from experimental studies or literature knowledge CoryneRegNet generates links to genome annotations, to identified transcription factors and to the corresponding cis-regulatory elements. CoryneRegNet is based on a multi-layered, hierarchical and modular concept of transcriptional regulation and was implemented by using the relational database management system MySQL and an ontology-based data structure. Reconstructed regulatory networks can be visualized by using the yFiles JAVA graph library. As an application example of CoryneRegNet, we have reconstructed the global transcriptional regulation of a cellular module involved in SOS and stress response of corynebacteria. Conclusion CoryneRegNet is an ontology-based data warehouse that allows a pertinent data management of regulatory interactions along with the genome-scale reconstruction of transcriptional regulatory networks. These models can further be combined with metabolic networks to build integrated models of cellular function including both metabolism and its transcriptional regulation. PMID:16478536

GenExp: An Interactive Web-Based Genomic DAS Client with Client-Side Data Rendering

PubMed Central

Gel Moreno, Bernat; Messeguer Peypoch, Xavier

2011-01-01

Background The Distributed Annotation System (DAS) offers a standard protocol for sharing and integrating annotations on biological sequences. There are more than 1000 DAS sources available and the number is steadily increasing. Clients are an essential part of the DAS system and integrate data from several independent sources in order to create a useful representation to the user. While web-based DAS clients exist, most of them do not have direct interaction capabilities such as dragging and zooming with the mouse. Results Here we present GenExp, a web based and fully interactive visual DAS client. GenExp is a genome oriented DAS client capable of creating informative representations of genomic data zooming out from base level to complete chromosomes. It proposes a novel approach to genomic data rendering and uses the latest HTML5 web technologies to create the data representation inside the client browser. Thanks to client-side rendering most position changes do not need a network request to the server and so responses to zooming and panning are almost immediate. In GenExp it is possible to explore the genome intuitively moving it with the mouse just like geographical map applications. Additionally, in GenExp it is possible to have more than one data viewer at the same time and to save the current state of the application to revisit it later on. Conclusions GenExp is a new interactive web-based client for DAS and addresses some of the short-comings of the existing clients. It uses client-side data rendering techniques resulting in easier genome browsing and exploration. GenExp is open source under the GPL license and it is freely available at http://gralggen.lsi.upc.edu/recerca/genexp. PMID:21750706

NABIC: A New Access Portal to Search, Visualize, and Share Agricultural Genomics Data.

PubMed

Seol, Young-Joo; Lee, Tae-Ho; Park, Dong-Suk; Kim, Chang-Kug

2016-01-01

The National Agricultural Biotechnology Information Center developed an access portal to search, visualize, and share agricultural genomics data with a focus on South Korean information and resources. The portal features an agricultural biotechnology database containing a wide range of omics data from public and proprietary sources. We collected 28.4 TB of data from 162 agricultural organisms, with 10 types of omics data comprising next-generation sequencing sequence read archive, genome, gene, nucleotide, DNA chip, expressed sequence tag, interactome, protein structure, molecular marker, and single-nucleotide polymorphism datasets. Our genomic resources contain information on five animals, seven plants, and one fungus, which is accessed through a genome browser. We also developed a data submission and analysis system as a web service, with easy-to-use functions and cutting-edge algorithms, including those for handling next-generation sequencing data.

Genomicus 2018: karyotype evolutionary trees and on-the-fly synteny computing.

PubMed

Nguyen, Nga Thi Thuy; Vincens, Pierre; Roest Crollius, Hugues; Louis, Alexandra

2018-01-04

Since 2010, the Genomicus web server is available online at http://genomicus.biologie.ens.fr/genomicus. This graphical browser provides access to comparative genomic analyses in four different phyla (Vertebrate, Plants, Fungi, and non vertebrate Metazoans). Users can analyse genomic information from extant species, as well as ancestral gene content and gene order for vertebrates and flowering plants, in an integrated evolutionary context. New analyses and visualization tools have recently been implemented in Genomicus Vertebrate. Karyotype structures from several genomes can now be compared along an evolutionary pathway (Multi-KaryotypeView), and synteny blocks can be computed and visualized between any two genomes (PhylDiagView). © The Author(s) 2017. Published by Oxford University Press on behalf of Nucleic Acids Research.

Editing the Neuronal Genome: a CRISPR View of Chromatin Regulation in Neuronal Development, Function, and Plasticity.

PubMed

Yang, Marty G; West, Anne E

2016-12-01

The dynamic orchestration of gene expression is crucial for the proper differentiation, function, and adaptation of cells. In the brain, transcriptional regulation underlies the incredible diversity of neuronal cell types and contributes to the ability of neurons to adapt their function to the environment. Recently, novel methods for genome and epigenome editing have begun to revolutionize our understanding of gene regulatory mechanisms. In particular, the clustered regularly interspaced short palindromic repeats (CRISPR)/Cas9 system has proven to be a particularly accessible and adaptable technique for genome engineering. Here, we review the use of CRISPR/Cas9 in neurobiology and discuss how these studies have advanced understanding of nervous system development and plasticity. We cover four especially salient applications of CRISPR/Cas9: testing the consequences of enhancer mutations, tagging genes and gene products for visualization in live cells, directly activating or repressing enhancers in vivo , and manipulating the epigenome. In each case, we summarize findings from recent studies and discuss evolving adaptations of the method.

A novel bioinformatics method for efficient knowledge discovery by BLSOM from big genomic sequence data.

PubMed

Bai, Yu; Iwasaki, Yuki; Kanaya, Shigehiko; Zhao, Yue; Ikemura, Toshimichi

2014-01-01

With remarkable increase of genomic sequence data of a wide range of species, novel tools are needed for comprehensive analyses of the big sequence data. Self-Organizing Map (SOM) is an effective tool for clustering and visualizing high-dimensional data such as oligonucleotide composition on one map. By modifying the conventional SOM, we have previously developed Batch-Learning SOM (BLSOM), which allows classification of sequence fragments according to species, solely depending on the oligonucleotide composition. In the present study, we introduce the oligonucleotide BLSOM used for characterization of vertebrate genome sequences. We first analyzed pentanucleotide compositions in 100 kb sequences derived from a wide range of vertebrate genomes and then the compositions in the human and mouse genomes in order to investigate an efficient method for detecting differences between the closely related genomes. BLSOM can recognize the species-specific key combination of oligonucleotide frequencies in each genome, which is called a "genome signature," and the specific regions specifically enriched in transcription-factor-binding sequences. Because the classification and visualization power is very high, BLSOM is an efficient powerful tool for extracting a wide range of information from massive amounts of genomic sequences (i.e., big sequence data).

Oncogenomic portals for the visualization and analysis of genome-wide cancer data

PubMed Central

Klonowska, Katarzyna; Czubak, Karol; Wojciechowska, Marzena; Handschuh, Luiza; Zmienko, Agnieszka; Figlerowicz, Marek; Dams-Kozlowska, Hanna; Kozlowski, Piotr

2016-01-01

Somatically acquired genomic alterations that drive oncogenic cellular processes are of great scientific and clinical interest. Since the initiation of large-scale cancer genomic projects (e.g., the Cancer Genome Project, The Cancer Genome Atlas, and the International Cancer Genome Consortium cancer genome projects), a number of web-based portals have been created to facilitate access to multidimensional oncogenomic data and assist with the interpretation of the data. The portals provide the visualization of small-size mutations, copy number variations, methylation, and gene/protein expression data that can be correlated with the available clinical, epidemiological, and molecular features. Additionally, the portals enable to analyze the gathered data with the use of various user-friendly statistical tools. Herein, we present a highly illustrated review of seven portals, i.e., Tumorscape, UCSC Cancer Genomics Browser, ICGC Data Portal, COSMIC, cBioPortal, IntOGen, and BioProfiling.de. All of the selected portals are user-friendly and can be exploited by scientists from different cancer-associated fields, including those without bioinformatics background. It is expected that the use of the portals will contribute to a better understanding of cancer molecular etiology and will ultimately accelerate the translation of genomic knowledge into clinical practice. PMID:26484415

Oncogenomic portals for the visualization and analysis of genome-wide cancer data.

PubMed

Klonowska, Katarzyna; Czubak, Karol; Wojciechowska, Marzena; Handschuh, Luiza; Zmienko, Agnieszka; Figlerowicz, Marek; Dams-Kozlowska, Hanna; Kozlowski, Piotr

2016-01-05

Somatically acquired genomic alterations that drive oncogenic cellular processes are of great scientific and clinical interest. Since the initiation of large-scale cancer genomic projects (e.g., the Cancer Genome Project, The Cancer Genome Atlas, and the International Cancer Genome Consortium cancer genome projects), a number of web-based portals have been created to facilitate access to multidimensional oncogenomic data and assist with the interpretation of the data. The portals provide the visualization of small-size mutations, copy number variations, methylation, and gene/protein expression data that can be correlated with the available clinical, epidemiological, and molecular features. Additionally, the portals enable to analyze the gathered data with the use of various user-friendly statistical tools. Herein, we present a highly illustrated review of seven portals, i.e., Tumorscape, UCSC Cancer Genomics Browser, ICGC Data Portal, COSMIC, cBioPortal, IntOGen, and BioProfiling.de. All of the selected portals are user-friendly and can be exploited by scientists from different cancer-associated fields, including those without bioinformatics background. It is expected that the use of the portals will contribute to a better understanding of cancer molecular etiology and will ultimately accelerate the translation of genomic knowledge into clinical practice.

Genome Variation Map: a data repository of genome variations in BIG Data Center

PubMed Central

Tian, Dongmei; Li, Cuiping; Tang, Bixia; Dong, Lili; Xiao, Jingfa; Bao, Yiming; Zhao, Wenming; He, Hang

2018-01-01

Abstract The Genome Variation Map (GVM; http://bigd.big.ac.cn/gvm/) is a public data repository of genome variations. As a core resource in the BIG Data Center, Beijing Institute of Genomics, Chinese Academy of Sciences, GVM dedicates to collect, integrate and visualize genome variations for a wide range of species, accepts submissions of different types of genome variations from all over the world and provides free open access to all publicly available data in support of worldwide research activities. Unlike existing related databases, GVM features integration of a large number of genome variations for a broad diversity of species including human, cultivated plants and domesticated animals. Specifically, the current implementation of GVM not only houses a total of ∼4.9 billion variants for 19 species including chicken, dog, goat, human, poplar, rice and tomato, but also incorporates 8669 individual genotypes and 13 262 manually curated high-quality genotype-to-phenotype associations for non-human species. In addition, GVM provides friendly intuitive web interfaces for data submission, browse, search and visualization. Collectively, GVM serves as an important resource for archiving genomic variation data, helpful for better understanding population genetic diversity and deciphering complex mechanisms associated with different phenotypes. PMID:29069473

RPAN: rice pan-genome browser for ∼3000 rice genomes.

PubMed

Sun, Chen; Hu, Zhiqiang; Zheng, Tianqing; Lu, Kuangchen; Zhao, Yue; Wang, Wensheng; Shi, Jianxin; Wang, Chunchao; Lu, Jinyuan; Zhang, Dabing; Li, Zhikang; Wei, Chaochun

2017-01-25

A pan-genome is the union of the gene sets of all the individuals of a clade or a species and it provides a new dimension of genome complexity with the presence/absence variations (PAVs) of genes among these genomes. With the progress of sequencing technologies, pan-genome study is becoming affordable for eukaryotes with large-sized genomes. The Asian cultivated rice, Oryza sativa L., is one of the major food sources for the world and a model organism in plant biology. Recently, the 3000 Rice Genome Project (3K RGP) sequenced more than 3000 rice genomes with a mean sequencing depth of 14.3×, which provided a tremendous resource for rice research. In this paper, we present a genome browser, Rice Pan-genome Browser (RPAN), as a tool to search and visualize the rice pan-genome derived from 3K RGP. RPAN contains a database of the basic information of 3010 rice accessions, including genomic sequences, gene annotations, PAV information and gene expression data of the rice pan-genome. At least 12 000 novel genes absent in the reference genome were included. RPAN also provides multiple search and visualization functions. RPAN can be a rich resource for rice biology and rice breeding. It is available at http://cgm.sjtu.edu.cn/3kricedb/ or http://www.rmbreeding.cn/pan3k. © The Author(s) 2016. Published by Oxford University Press on behalf of Nucleic Acids Research.

Plant Reactome: a resource for plant pathways and comparative analysis

PubMed Central

Naithani, Sushma; Preece, Justin; D'Eustachio, Peter; Gupta, Parul; Amarasinghe, Vindhya; Dharmawardhana, Palitha D.; Wu, Guanming; Fabregat, Antonio; Elser, Justin L.; Weiser, Joel; Keays, Maria; Fuentes, Alfonso Munoz-Pomer; Petryszak, Robert; Stein, Lincoln D.; Ware, Doreen; Jaiswal, Pankaj

2017-01-01

Plant Reactome (http://plantreactome.gramene.org/) is a free, open-source, curated plant pathway database portal, provided as part of the Gramene project. The database provides intuitive bioinformatics tools for the visualization, analysis and interpretation of pathway knowledge to support genome annotation, genome analysis, modeling, systems biology, basic research and education. Plant Reactome employs the structural framework of a plant cell to show metabolic, transport, genetic, developmental and signaling pathways. We manually curate molecular details of pathways in these domains for reference species Oryza sativa (rice) supported by published literature and annotation of well-characterized genes. Two hundred twenty-two rice pathways, 1025 reactions associated with 1173 proteins, 907 small molecules and 256 literature references have been curated to date. These reference annotations were used to project pathways for 62 model, crop and evolutionarily significant plant species based on gene homology. Database users can search and browse various components of the database, visualize curated baseline expression of pathway-associated genes provided by the Expression Atlas and upload and analyze their Omics datasets. The database also offers data access via Application Programming Interfaces (APIs) and in various standardized pathway formats, such as SBML and BioPAX. PMID:27799469

The Reactome pathway Knowledgebase

PubMed Central

Fabregat, Antonio; Sidiropoulos, Konstantinos; Garapati, Phani; Gillespie, Marc; Hausmann, Kerstin; Haw, Robin; Jassal, Bijay; Jupe, Steven; Korninger, Florian; McKay, Sheldon; Matthews, Lisa; May, Bruce; Milacic, Marija; Rothfels, Karen; Shamovsky, Veronica; Webber, Marissa; Weiser, Joel; Williams, Mark; Wu, Guanming; Stein, Lincoln; Hermjakob, Henning; D'Eustachio, Peter

2016-01-01

The Reactome Knowledgebase (www.reactome.org) provides molecular details of signal transduction, transport, DNA replication, metabolism and other cellular processes as an ordered network of molecular transformations—an extended version of a classic metabolic map, in a single consistent data model. Reactome functions both as an archive of biological processes and as a tool for discovering unexpected functional relationships in data such as gene expression pattern surveys or somatic mutation catalogues from tumour cells. Over the last two years we redeveloped major components of the Reactome web interface to improve usability, responsiveness and data visualization. A new pathway diagram viewer provides a faster, clearer interface and smooth zooming from the entire reaction network to the details of individual reactions. Tool performance for analysis of user datasets has been substantially improved, now generating detailed results for genome-wide expression datasets within seconds. The analysis module can now be accessed through a RESTFul interface, facilitating its inclusion in third party applications. A new overview module allows the visualization of analysis results on a genome-wide Reactome pathway hierarchy using a single screen page. The search interface now provides auto-completion as well as a faceted search to narrow result lists efficiently. PMID:26656494

Lotus Base: An integrated information portal for the model legume Lotus japonicus

PubMed Central

Mun, Terry; Bachmann, Asger; Gupta, Vikas; Stougaard, Jens; Andersen, Stig U.

2016-01-01

Lotus japonicus is a well-characterized model legume widely used in the study of plant-microbe interactions. However, datasets from various Lotus studies are poorly integrated and lack interoperability. We recognize the need for a comprehensive repository that allows comprehensive and dynamic exploration of Lotus genomic and transcriptomic data. Equally important are user-friendly in-browser tools designed for data visualization and interpretation. Here, we present Lotus Base, which opens to the research community a large, established LORE1 insertion mutant population containing an excess of 120,000 lines, and serves the end-user tightly integrated data from Lotus, such as the reference genome, annotated proteins, and expression profiling data. We report the integration of expression data from the L. japonicus gene expression atlas project, and the development of tools to cluster and export such data, allowing users to construct, visualize, and annotate co-expression gene networks. Lotus Base takes advantage of modern advances in browser technology to deliver powerful data interpretation for biologists. Its modular construction and publicly available application programming interface enable developers to tap into the wealth of integrated Lotus data. Lotus Base is freely accessible at: https://lotus.au.dk. PMID:28008948

NABIC: A New Access Portal to Search, Visualize, and Share Agricultural Genomics Data

PubMed Central

Seol, Young-Joo; Lee, Tae-Ho; Park, Dong-Suk; Kim, Chang-Kug

2016-01-01

The National Agricultural Biotechnology Information Center developed an access portal to search, visualize, and share agricultural genomics data with a focus on South Korean information and resources. The portal features an agricultural biotechnology database containing a wide range of omics data from public and proprietary sources. We collected 28.4 TB of data from 162 agricultural organisms, with 10 types of omics data comprising next-generation sequencing sequence read archive, genome, gene, nucleotide, DNA chip, expressed sequence tag, interactome, protein structure, molecular marker, and single-nucleotide polymorphism datasets. Our genomic resources contain information on five animals, seven plants, and one fungus, which is accessed through a genome browser. We also developed a data submission and analysis system as a web service, with easy-to-use functions and cutting-edge algorithms, including those for handling next-generation sequencing data. PMID:26848255

STAR: an integrated solution to management and visualization of sequencing data

PubMed Central

Wang, Tao; Liu, Jie; Shen, Li; Tonti-Filippini, Julian; Zhu, Yun; Jia, Haiyang; Lister, Ryan; Whitaker, John W.; Ecker, Joseph R.; Millar, A. Harvey; Ren, Bing; Wang, Wei

2013-01-01

Motivation: Easily visualization of complex data features is a necessary step to conduct studies on next-generation sequencing (NGS) data. We developed STAR, an integrated web application that enables online management, visualization and track-based analysis of NGS data. Results: STAR is a multilayer web service system. On the client side, STAR leverages JavaScript, HTML5 Canvas and asynchronous communications to deliver a smoothly scrolling desktop-like graphical user interface with a suite of in-browser analysis tools that range from providing simple track configuration controls to sophisticated feature detection within datasets. On the server side, STAR supports private session state retention via an account management system and provides data management modules that enable collection, visualization and analysis of third-party sequencing data from the public domain with over thousands of tracks hosted to date. Overall, STAR represents a next-generation data exploration solution to match the requirements of NGS data, enabling both intuitive visualization and dynamic analysis of data. Availability and implementation: STAR browser system is freely available on the web at http://wanglab.ucsd.edu/star/browser and https://github.com/angell1117/STAR-genome-browser. Contact: wei-wang@ucsd.edu PMID:24078702

Visualization and Phospholipid Identification (VaLID): online integrated search engine capable of identifying and visualizing glycerophospholipids with given mass

PubMed Central

Figeys, Daniel; Fai, Stephen; Bennett, Steffany A. L.

2013-01-01

Motivation: Establishing phospholipid identities in large lipidomic datasets is a labour-intensive process. Where genomics and proteomics capitalize on sequence-based signatures, glycerophospholipids lack easily definable molecular fingerprints. Carbon chain length, degree of unsaturation, linkage, and polar head group identity must be calculated from mass to charge (m/z) ratios under defined mass spectrometry (MS) conditions. Given increasing MS sensitivity, many m/z values are not represented in existing prediction engines. To address this need, Visualization and Phospholipid Identification is a web-based application that returns all theoretically possible phospholipids for any m/z value and MS condition. Visualization algorithms produce multiple chemical structure files for each species. Curated lipids detected by the Canadian Institutes of Health Research Training Program in Neurodegenerative Lipidomics are provided as high-resolution structures. Availability: VaLID is available through the Canadian Institutes of Health Research Training Program in Neurodegenerative Lipidomics resources web site at https://www.med.uottawa.ca/lipidomics/resources.html. Contacts: lipawrd@uottawa.ca Supplementary Information: Supplementary data are available at Bioinformatics online. PMID:23162086

CRISPR/Cas9-mediated knock-in of an optimized TetO repeat for live cell imaging of endogenous loci.

PubMed

Tasan, Ipek; Sustackova, Gabriela; Zhang, Liguo; Kim, Jiah; Sivaguru, Mayandi; HamediRad, Mohammad; Wang, Yuchuan; Genova, Justin; Ma, Jian; Belmont, Andrew S; Zhao, Huimin

2018-06-15

Nuclear organization has an important role in determining genome function; however, it is not clear how spatiotemporal organization of the genome relates to functionality. To elucidate this relationship, a method for tracking any locus of interest is desirable. Recently clustered regularly interspaced short palindromic repeats (CRISPR)/CRISPR-associated protein 9 (Cas9) or transcription activator-like effectors were adapted for imaging endogenous loci; however, they are mostly limited to visualization of repetitive regions. Here, we report an efficient and scalable method named SHACKTeR (Short Homology and CRISPR/Cas9-mediated Knock-in of a TetO Repeat) for live cell imaging of specific chromosomal regions without the need for a pre-existing repetitive sequence. SHACKTeR requires only two modifications to the genome: CRISPR/Cas9-mediated knock-in of an optimized TetO repeat and its visualization by TetR-EGFP expression. Our simplified knock-in protocol, utilizing short homology arms integrated by polymerase chain reaction, was successful at labeling 10 different loci in HCT116 cells. We also showed the feasibility of knock-in into lamina-associated, heterochromatin regions, demonstrating that these regions prefer non-homologous end joining for knock-in. Using SHACKTeR, we were able to observe DNA replication at a specific locus by long-term live cell imaging. We anticipate the general applicability and scalability of our method will enhance causative analyses between gene function and compartmentalization in a high-throughput manner.

G23D: Online tool for mapping and visualization of genomic variants on 3D protein structures.

PubMed

Solomon, Oz; Kunik, Vered; Simon, Amos; Kol, Nitzan; Barel, Ortal; Lev, Atar; Amariglio, Ninette; Somech, Raz; Rechavi, Gidi; Eyal, Eran

2016-08-26

Evaluation of the possible implications of genomic variants is an increasingly important task in the current high throughput sequencing era. Structural information however is still not routinely exploited during this evaluation process. The main reasons can be attributed to the partial structural coverage of the human proteome and the lack of tools which conveniently convert genomic positions, which are the frequent output of genomic pipelines, to proteins and structure coordinates. We present G23D, a tool for conversion of human genomic coordinates to protein coordinates and protein structures. G23D allows mapping of genomic positions/variants on evolutionary related (and not only identical) protein three dimensional (3D) structures as well as on theoretical models. By doing so it significantly extends the space of variants for which structural insight is feasible. To facilitate interpretation of the variant consequence, pathogenic variants, functional sites and polymorphism sites are displayed on protein sequence and structure diagrams alongside the input variants. G23D also provides modeling of the mutant structure, analysis of intra-protein contacts and instant access to functional predictions and predictions of thermo-stability changes. G23D is available at http://www.sheba-cancer.org.il/G23D . G23D extends the fraction of variants for which structural analysis is applicable and provides better and faster accessibility for structural data to biologists and geneticists who routinely work with genomic information.

Visualization of IAV Genomes at the Single-Cell Level.

PubMed

Wang, Dan; Ma, Wenjun

2017-10-01

Different influenza A viruses (IAVs) infect the same cell in a host, and can subsequently produce new viruses through genome reassortment. By combining padlock probe RNA labeling with a single-cell analysis, a new approach effectively captures IAV genome trafficking and defines a time window for genome reassortment from same-cell coinfections. Copyright © 2017 Elsevier Ltd. All rights reserved.

Using Interactive Data Visualizations for Exploratory Analysis in Undergraduate Genomics Coursework: Field Study Findings and Guidelines

NASA Astrophysics Data System (ADS)

Mirel, Barbara; Kumar, Anuj; Nong, Paige; Su, Gang; Meng, Fan

2016-02-01

Life scientists increasingly use visual analytics to explore large data sets and generate hypotheses. Undergraduate biology majors should be learning these same methods. Yet visual analytics is one of the most underdeveloped areas of undergraduate biology education. This study sought to determine the feasibility of undergraduate biology majors conducting exploratory analysis using the same interactive data visualizations as practicing scientists. We examined 22 upper level undergraduates in a genomics course as they engaged in a case-based inquiry with an interactive heat map. We qualitatively and quantitatively analyzed students' visual analytic behaviors, reasoning and outcomes to identify student performance patterns, commonly shared efficiencies and task completion. We analyzed students' successes and difficulties in applying knowledge and skills relevant to the visual analytics case and related gaps in knowledge and skill to associated tool designs. Findings show that undergraduate engagement in visual analytics is feasible and could be further strengthened through tool usability improvements. We identify these improvements. We speculate, as well, on instructional considerations that our findings suggested may also enhance visual analytics in case-based modules.

Using Interactive Data Visualizations for Exploratory Analysis in Undergraduate Genomics Coursework: Field Study Findings and Guidelines

PubMed Central

Kumar, Anuj; Nong, Paige; Su, Gang; Meng, Fan

2016-01-01

Life scientists increasingly use visual analytics to explore large data sets and generate hypotheses. Undergraduate biology majors should be learning these same methods. Yet visual analytics is one of the most underdeveloped areas of undergraduate biology education. This study sought to determine the feasibility of undergraduate biology majors conducting exploratory analysis using the same interactive data visualizations as practicing scientists. We examined 22 upper level undergraduates in a genomics course as they engaged in a case-based inquiry with an interactive heat map. We qualitatively and quantitatively analyzed students’ visual analytic behaviors, reasoning and outcomes to identify student performance patterns, commonly shared efficiencies and task completion. We analyzed students’ successes and difficulties in applying knowledge and skills relevant to the visual analytics case and related gaps in knowledge and skill to associated tool designs. Findings show that undergraduate engagement in visual analytics is feasible and could be further strengthened through tool usability improvements. We identify these improvements. We speculate, as well, on instructional considerations that our findings suggested may also enhance visual analytics in case-based modules. PMID:26877625

The i5k Workspace@NAL—enabling genomic data access, visualization and curation of arthropod genomes

PubMed Central

Poelchau, Monica; Childers, Christopher; Moore, Gary; Tsavatapalli, Vijaya; Evans, Jay; Lee, Chien-Yueh; Lin, Han; Lin, Jun-Wei; Hackett, Kevin

2015-01-01

The 5000 arthropod genomes initiative (i5k) has tasked itself with coordinating the sequencing of 5000 insect or related arthropod genomes. The resulting influx of data, mostly from small research groups or communities with little bioinformatics experience, will require visualization, dissemination and curation, preferably from a centralized platform. The National Agricultural Library (NAL) has implemented the i5k Workspace@NAL (http://i5k.nal.usda.gov/) to help meet the i5k initiative's genome hosting needs. Any i5k member is encouraged to contact the i5k Workspace with their genome project details. Once submitted, new content will be accessible via organism pages, genome browsers and BLAST search engines, which are implemented via the open-source Tripal framework, a web interface for the underlying Chado database schema. We also implement the Web Apollo software for groups that choose to curate gene models. New content will add to the existing body of 35 arthropod species, which include species relevant for many aspects of arthropod genomic research, including agriculture, invasion biology, systematics, ecology and evolution, and developmental research. PMID:25332403

GenomeGems: evaluation of genetic variability from deep sequencing data

PubMed Central

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

Optofluidic Single-Cell Genome Amplification of Sub-micron Bacteria in the Ocean Subsurface

PubMed Central

Landry, Zachary C.; Vergin, Kevin; Mannenbach, Christopher; Block, Stephen; Yang, Qiao; Blainey, Paul; Carlson, Craig; Giovannoni, Stephen

2018-01-01

Optofluidic single-cell genome amplification was used to obtain genome sequences from sub-micron cells collected from the euphotic and mesopelagic zones of the northwestern Sargasso Sea. Plankton cells were visually selected and manually sorted with an optical trap, yielding 20 partial genome sequences representing seven bacterial phyla. Two organisms, E01-9C-26 (Gammaproteobacteria), represented by four single cell genomes, and Opi.OSU.00C, an uncharacterized Verrucomicrobia, were the first of their types retrieved by single cell genome sequencing and were studied in detail. Metagenomic data showed that E01-9C-26 is found throughout the dark ocean, while Opi.OSU.00C was observed to bloom transiently in the nutrient-depleted euphotic zone of the late spring and early summer. The E01-9C-26 genomes had an estimated size of 4.76–5.05 Mbps, and contained “O” and “W”-type monooxygenase genes related to methane and ammonium monooxygenases that were previously reported from ocean metagenomes. Metabolic reconstruction indicated E01-9C-26 are likely versatile methylotrophs capable of scavenging C1 compounds, methylated compounds, reduced sulfur compounds, and a wide range of amines, including D-amino acids. The genome sequences identified E01-9C-26 as a source of “O” and “W”-type monooxygenase genes related to methane and ammonium monooxygenases that were previously reported from ocean metagenomes, but are of unknown function. In contrast, Opi.OSU.00C genomes encode genes for catabolizing carbohydrate compounds normally associated with eukaryotic phytoplankton. This exploration of optofluidics showed that it was effective for retrieving diverse single-cell bacterioplankton genomes and has potential advantages in microbiology applications that require working with small sample volumes or targeting cells by their morphology.

SpectralNET – an application for spectral graph analysis and visualization

PubMed Central

Forman, Joshua J; Clemons, Paul A; Schreiber, Stuart L; Haggarty, Stephen J

2005-01-01

Background Graph theory provides a computational framework for modeling a variety of datasets including those emerging from genomics, proteomics, and chemical genetics. Networks of genes, proteins, small molecules, or other objects of study can be represented as graphs of nodes (vertices) and interactions (edges) that can carry different weights. SpectralNET is a flexible application for analyzing and visualizing these biological and chemical networks. Results Available both as a standalone .NET executable and as an ASP.NET web application, SpectralNET was designed specifically with the analysis of graph-theoretic metrics in mind, a computational task not easily accessible using currently available applications. Users can choose either to upload a network for analysis using a variety of input formats, or to have SpectralNET generate an idealized random network for comparison to a real-world dataset. Whichever graph-generation method is used, SpectralNET displays detailed information about each connected component of the graph, including graphs of degree distribution, clustering coefficient by degree, and average distance by degree. In addition, extensive information about the selected vertex is shown, including degree, clustering coefficient, various distance metrics, and the corresponding components of the adjacency, Laplacian, and normalized Laplacian eigenvectors. SpectralNET also displays several graph visualizations, including a linear dimensionality reduction for uploaded datasets (Principal Components Analysis) and a non-linear dimensionality reduction that provides an elegant view of global graph structure (Laplacian eigenvectors). Conclusion SpectralNET provides an easily accessible means of analyzing graph-theoretic metrics for data modeling and dimensionality reduction. SpectralNET is publicly available as both a .NET application and an ASP.NET web application from . Source code is available upon request. PMID:16236170

SpectralNET--an application for spectral graph analysis and visualization.

PubMed

Forman, Joshua J; Clemons, Paul A; Schreiber, Stuart L; Haggarty, Stephen J

2005-10-19

Graph theory provides a computational framework for modeling a variety of datasets including those emerging from genomics, proteomics, and chemical genetics. Networks of genes, proteins, small molecules, or other objects of study can be represented as graphs of nodes (vertices) and interactions (edges) that can carry different weights. SpectralNET is a flexible application for analyzing and visualizing these biological and chemical networks. Available both as a standalone .NET executable and as an ASP.NET web application, SpectralNET was designed specifically with the analysis of graph-theoretic metrics in mind, a computational task not easily accessible using currently available applications. Users can choose either to upload a network for analysis using a variety of input formats, or to have SpectralNET generate an idealized random network for comparison to a real-world dataset. Whichever graph-generation method is used, SpectralNET displays detailed information about each connected component of the graph, including graphs of degree distribution, clustering coefficient by degree, and average distance by degree. In addition, extensive information about the selected vertex is shown, including degree, clustering coefficient, various distance metrics, and the corresponding components of the adjacency, Laplacian, and normalized Laplacian eigenvectors. SpectralNET also displays several graph visualizations, including a linear dimensionality reduction for uploaded datasets (Principal Components Analysis) and a non-linear dimensionality reduction that provides an elegant view of global graph structure (Laplacian eigenvectors). SpectralNET provides an easily accessible means of analyzing graph-theoretic metrics for data modeling and dimensionality reduction. SpectralNET is publicly available as both a .NET application and an ASP.NET web application from http://chembank.broad.harvard.edu/resources/. Source code is available upon request.

VAT: a computational framework to functionally annotate variants in personal genomes within a cloud-computing environment.

PubMed

Habegger, Lukas; Balasubramanian, Suganthi; Chen, David Z; Khurana, Ekta; Sboner, Andrea; Harmanci, Arif; Rozowsky, Joel; Clarke, Declan; Snyder, Michael; Gerstein, Mark

2012-09-01

The functional annotation of variants obtained through sequencing projects is generally assumed to be a simple intersection of genomic coordinates with genomic features. However, complexities arise for several reasons, including the differential effects of a variant on alternatively spliced transcripts, as well as the difficulty in assessing the impact of small insertions/deletions and large structural variants. Taking these factors into consideration, we developed the Variant Annotation Tool (VAT) to functionally annotate variants from multiple personal genomes at the transcript level as well as obtain summary statistics across genes and individuals. VAT also allows visualization of the effects of different variants, integrates allele frequencies and genotype data from the underlying individuals and facilitates comparative analysis between different groups of individuals. VAT can either be run through a command-line interface or as a web application. Finally, in order to enable on-demand access and to minimize unnecessary transfers of large data files, VAT can be run as a virtual machine in a cloud-computing environment. VAT is implemented in C and PHP. The VAT web service, Amazon Machine Image, source code and detailed documentation are available at vat.gersteinlab.org.

Visualization of A- and B-genome chromosomes in wheat (Triticum aestivum L.) x jointed goatgrass (Aegilops cylindrica Host) backcross progenies.

PubMed

Wang, Z N; Hang, A; Hansen, J; Burton, C; Mallory-Smith, C A; Zemetra, R S

2000-12-01

Wheat (Triticum aestivum) and jointed goatgrass (Aegilops cylindrica) can cross with each other, and their self-fertile backcross progenies frequently have extra chromosomes and chromosome segments, presumably retained from wheat, raising the possibility that a herbicide resistance gene might transfer from wheat to jointed goatgrass. Genomic in situ hybridization (GISH) was used to clarify the origin of these extra chromosomes. By using T. durum DNA (AABB genome) as a probe and jointed goatgrass DNA (CCDD genome) as blocking DNA, one, two, and three A- or B-genome chromosomes were identified in three BC2S2 individuals where 2n = 29, 30, and 31 chromosomes, respectively. A translocation between wheat and jointed goatgrass chromosomes was also detected in an individual with 30 chromosomes. In pollen mother cells with meiotic configuration of 14 II + 2 I, the two univalents were identified as being retained from the A or B genome of wheat. By using Ae. markgrafii DNA (CC genome) as a probe and wheat DNA (AABBDD genome) as blocking DNA. 14 C-genome chromosomes were visualized in all BC2S2 individuals. The GISH procedure provides a powerful tool to detect the A or B-genome chromatin in a jointed goatgrass background, making it possible to assess the risk of transfer of herbicide resistance genes located on the A or B genome of wheat to jointed goatgrass.

Genome instability in Novel Lolium multiflorum x L. arundinaceum hybrids

USDA-ARS?s Scientific Manuscript database

We have identified a method whereby Lolium multiflorum (Lm) or L. arundinaceum (Fa) genomes are preferentially eliminated through a mitotic loss behavior in interspecific Lm x Fa F1 hybrids,generating either dihaploid Lm lines or Fa lines. The genome instability has been visualized phenotypically an...

Extension modules for storage, visualization and querying of genomic, genetic and breeding data in Tripal databases

PubMed Central

Lee, Taein; Cheng, Chun-Huai; Ficklin, Stephen; Yu, Jing; Humann, Jodi; Main, Dorrie

2017-01-01

Abstract Tripal is an open-source database platform primarily used for development of genomic, genetic and breeding databases. We report here on the release of the Chado Loader, Chado Data Display and Chado Search modules to extend the functionality of the core Tripal modules. These new extension modules provide additional tools for (1) data loading, (2) customized visualization and (3) advanced search functions for supported data types such as organism, marker, QTL/Mendelian Trait Loci, germplasm, map, project, phenotype, genotype and their respective metadata. The Chado Loader module provides data collection templates in Excel with defined metadata and data loaders with front end forms. The Chado Data Display module contains tools to visualize each data type and the metadata which can be used as is or customized as desired. The Chado Search module provides search and download functionality for the supported data types. Also included are the tools to visualize map and species summary. The use of materialized views in the Chado Search module enables better performance as well as flexibility of data modeling in Chado, allowing existing Tripal databases with different metadata types to utilize the module. These Tripal Extension modules are implemented in the Genome Database for Rosaceae (rosaceae.org), CottonGen (cottongen.org), Citrus Genome Database (citrusgenomedb.org), Genome Database for Vaccinium (vaccinium.org) and the Cool Season Food Legume Database (coolseasonfoodlegume.org). Database URL: https://www.citrusgenomedb.org/, https://www.coolseasonfoodlegume.org/, https://www.cottongen.org/, https://www.rosaceae.org/, https://www.vaccinium.org/

iSyTE 2.0: a database for expression-based gene discovery in the eye

PubMed Central

Kakrana, Atul; Yang, Andrian; Anand, Deepti; Djordjevic, Djordje; Ramachandruni, Deepti; Singh, Abhyudai; Huang, Hongzhan

2018-01-01

Abstract Although successful in identifying new cataract-linked genes, the previous version of the database iSyTE (integrated Systems Tool for Eye gene discovery) was based on expression information on just three mouse lens stages and was functionally limited to visualization by only UCSC-Genome Browser tracks. To increase its efficacy, here we provide an enhanced iSyTE version 2.0 (URL: http://research.bioinformatics.udel.edu/iSyTE) based on well-curated, comprehensive genome-level lens expression data as a one-stop portal for the effective visualization and analysis of candidate genes in lens development and disease. iSyTE 2.0 includes all publicly available lens Affymetrix and Illumina microarray datasets representing a broad range of embryonic and postnatal stages from wild-type and specific gene-perturbation mouse mutants with eye defects. Further, we developed a new user-friendly web interface for direct access and cogent visualization of the curated expression data, which supports convenient searches and a range of downstream analyses. The utility of these new iSyTE 2.0 features is illustrated through examples of established genes associated with lens development and pathobiology, which serve as tutorials for its application by the end-user. iSyTE 2.0 will facilitate the prioritization of eye development and disease-linked candidate genes in studies involving transcriptomics or next-generation sequencing data, linkage analysis and GWAS approaches. PMID:29036527

Real-space and real-time dynamics of CRISPR-Cas9 visualized by high-speed atomic force microscopy.

PubMed

Shibata, Mikihiro; Nishimasu, Hiroshi; Kodera, Noriyuki; Hirano, Seiichi; Ando, Toshio; Uchihashi, Takayuki; Nureki, Osamu

2017-11-10

The CRISPR-associated endonuclease Cas9 binds to a guide RNA and cleaves double-stranded DNA with a sequence complementary to the RNA guide. The Cas9-RNA system has been harnessed for numerous applications, such as genome editing. Here we use high-speed atomic force microscopy (HS-AFM) to visualize the real-space and real-time dynamics of CRISPR-Cas9 in action. HS-AFM movies indicate that, whereas apo-Cas9 adopts unexpected flexible conformations, Cas9-RNA forms a stable bilobed structure and interrogates target sites on the DNA by three-dimensional diffusion. These movies also provide real-time visualization of the Cas9-mediated DNA cleavage process. Notably, the Cas9 HNH nuclease domain fluctuates upon DNA binding, and subsequently adopts an active conformation, where the HNH active site is docked at the cleavage site in the target DNA. Collectively, our HS-AFM data extend our understanding of the action mechanism of CRISPR-Cas9.

GAC: Gene Associations with Clinical, a web based application.

PubMed

Zhang, Xinyan; Rupji, Manali; Kowalski, Jeanne

2017-01-01

We present GAC, a shiny R based tool for interactive visualization of clinical associations based on high-dimensional data. The tool provides a web-based suite to perform supervised principal component analysis (SuperPC), an approach that uses both high-dimensional data, such as gene expression, combined with clinical data to infer clinical associations. We extended the approach to address binary outcomes, in addition to continuous and time-to-event data in our package, thereby increasing the use and flexibility of SuperPC.  Additionally, the tool provides an interactive visualization for summarizing results based on a forest plot for both binary and time-to-event data.  In summary, the GAC suite of tools provide a one stop shop for conducting statistical analysis to identify and visualize the association between a clinical outcome of interest and high-dimensional data types, such as genomic data. Our GAC package has been implemented in R and is available via http://shinygispa.winship.emory.edu/GAC/. The developmental repository is available at https://github.com/manalirupji/GAC.

Lessons learnt on the analysis of large sequence data in animal genomics.

PubMed

Biscarini, F; Cozzi, P; Orozco-Ter Wengel, P

2018-04-06

The 'omics revolution has made a large amount of sequence data available to researchers and the industry. This has had a profound impact in the field of bioinformatics, stimulating unprecedented advancements in this discipline. Mostly, this is usually looked at from the perspective of human 'omics, in particular human genomics. Plant and animal genomics, however, have also been deeply influenced by next-generation sequencing technologies, with several genomics applications now popular among researchers and the breeding industry. Genomics tends to generate huge amounts of data, and genomic sequence data account for an increasing proportion of big data in biological sciences, due largely to decreasing sequencing and genotyping costs and to large-scale sequencing and resequencing projects. The analysis of big data poses a challenge to scientists, as data gathering currently takes place at a faster pace than does data processing and analysis, and the associated computational burden is increasingly taxing, making even simple manipulation, visualization and transferring of data a cumbersome operation. The time consumed by the processing and analysing of huge data sets may be at the expense of data quality assessment and critical interpretation. Additionally, when analysing lots of data, something is likely to go awry-the software may crash or stop-and it can be very frustrating to track the error. We herein review the most relevant issues related to tackling these challenges and problems, from the perspective of animal genomics, and provide researchers that lack extensive computing experience with guidelines that will help when processing large genomic data sets. © 2018 Stichting International Foundation for Animal Genetics.

Genome Variation Map: a data repository of genome variations in BIG Data Center.

PubMed

Song, Shuhui; Tian, Dongmei; Li, Cuiping; Tang, Bixia; Dong, Lili; Xiao, Jingfa; Bao, Yiming; Zhao, Wenming; He, Hang; Zhang, Zhang

2018-01-04

The Genome Variation Map (GVM; http://bigd.big.ac.cn/gvm/) is a public data repository of genome variations. As a core resource in the BIG Data Center, Beijing Institute of Genomics, Chinese Academy of Sciences, GVM dedicates to collect, integrate and visualize genome variations for a wide range of species, accepts submissions of different types of genome variations from all over the world and provides free open access to all publicly available data in support of worldwide research activities. Unlike existing related databases, GVM features integration of a large number of genome variations for a broad diversity of species including human, cultivated plants and domesticated animals. Specifically, the current implementation of GVM not only houses a total of ∼4.9 billion variants for 19 species including chicken, dog, goat, human, poplar, rice and tomato, but also incorporates 8669 individual genotypes and 13 262 manually curated high-quality genotype-to-phenotype associations for non-human species. In addition, GVM provides friendly intuitive web interfaces for data submission, browse, search and visualization. Collectively, GVM serves as an important resource for archiving genomic variation data, helpful for better understanding population genetic diversity and deciphering complex mechanisms associated with different phenotypes. © The Author(s) 2017. Published by Oxford University Press on behalf of Nucleic Acids Research.

Analysis of experience-regulated transcriptome and imprintome during critical periods of mouse visual system development reveals spatiotemporal dynamics.

PubMed

Hsu, Chi-Lin; Chou, Chih-Hsuan; Huang, Shih-Chuan; Lin, Chia-Yi; Lin, Meng-Ying; Tung, Chun-Che; Lin, Chun-Yen; Lai, Ivan Pochou; Zou, Yan-Fang; Youngson, Neil A; Lin, Shau-Ping; Yang, Chang-Hao; Chen, Shih-Kuo; Gau, Susan Shur-Fen; Huang, Hsien-Sung

2018-03-15

Visual system development is light-experience dependent, which strongly implicates epigenetic mechanisms in light-regulated maturation. Among many epigenetic processes, genomic imprinting is an epigenetic mechanism through which monoallelic gene expression occurs in a parent-of-origin-specific manner. It is unknown if genomic imprinting contributes to visual system development. We profiled the transcriptome and imprintome during critical periods of mouse visual system development under normal- and dark-rearing conditions using B6/CAST F1 hybrid mice. We identified experience-regulated, isoform-specific and brain-region-specific imprinted genes. We also found imprinted microRNAs were predominantly clustered into the Dlk1-Dio3 imprinted locus with light experience affecting some imprinted miRNA expression. Our findings provide the first comprehensive analysis of light-experience regulation of the transcriptome and imprintome during critical periods of visual system development. Our results may contribute to therapeutic strategies for visual impairments and circadian rhythm disorders resulting from a dysfunctional imprintome.

CyanoBase: the cyanobacteria genome database update 2010.

PubMed

Nakao, Mitsuteru; Okamoto, Shinobu; Kohara, Mitsuyo; Fujishiro, Tsunakazu; Fujisawa, Takatomo; Sato, Shusei; Tabata, Satoshi; Kaneko, Takakazu; Nakamura, Yasukazu

2010-01-01

CyanoBase (http://genome.kazusa.or.jp/cyanobase) is the genome database for cyanobacteria, which are model organisms for photosynthesis. The database houses cyanobacteria species information, complete genome sequences, genome-scale experiment data, gene information, gene annotations and mutant information. In this version, we updated these datasets and improved the navigation and the visual display of the data views. In addition, a web service API now enables users to retrieve the data in various formats with other tools, seamlessly.

Pathway collages: personalized multi-pathway diagrams.

PubMed

Paley, Suzanne; O'Maille, Paul E; Weaver, Daniel; Karp, Peter D

2016-12-13

Metabolic pathway diagrams are a classical way of visualizing a linked cascade of biochemical reactions. However, to understand some biochemical situations, viewing a single pathway is insufficient, whereas viewing the entire metabolic network results in information overload. How do we enable scientists to rapidly construct personalized multi-pathway diagrams that depict a desired collection of interacting pathways that emphasize particular pathway interactions? We define software for constructing personalized multi-pathway diagrams called pathway-collages using a combination of manual and automatic layouts. The user specifies a set of pathways of interest for the collage from a Pathway/Genome Database. Layouts for the individual pathways are generated by the Pathway Tools software, and are sent to a Javascript Pathway Collage application implemented using Cytoscape.js. That application allows the user to re-position pathways; define connections between pathways; change visual style parameters; and paint metabolomics, gene expression, and reaction flux data onto the collage to obtain a desired multi-pathway diagram. We demonstrate the use of pathway collages in two application areas: a metabolomics study of pathogen drug response, and an Escherichia coli metabolic model. Pathway collages enable facile construction of personalized multi-pathway diagrams.

Enabling the democratization of the genomics revolution with a fully integrated web-based bioinformatics platform

DOE Office of Scientific and Technical Information (OSTI.GOV)

Li, Po-E; Lo, Chien -Chi; Anderson, Joseph J.

Continued advancements in sequencing technologies have fueled the development of new sequencing applications and promise to flood current databases with raw data. A number of factors prevent the seamless and easy use of these data, including the breadth of project goals, the wide array of tools that individually perform fractions of any given analysis, the large number of associated software/hardware dependencies, and the detailed expertise required to perform these analyses. To address these issues, we have developed an intuitive web-based environment with a wide assortment of integrated and cutting-edge bioinformatics tools in pre-configured workflows. These workflows, coupled with the easemore » of use of the environment, provide even novice next-generation sequencing users with the ability to perform many complex analyses with only a few mouse clicks and, within the context of the same environment, to visualize and further interrogate their results. As a result, this bioinformatics platform is an initial attempt at Empowering the Development of Genomics Expertise (EDGE) in a wide range of applications for microbial research.« less

Enabling the democratization of the genomics revolution with a fully integrated web-based bioinformatics platform

PubMed Central

Li, Po-E; Lo, Chien-Chi; Anderson, Joseph J.; Davenport, Karen W.; Bishop-Lilly, Kimberly A.; Xu, Yan; Ahmed, Sanaa; Feng, Shihai; Mokashi, Vishwesh P.; Chain, Patrick S.G.

2017-01-01

Continued advancements in sequencing technologies have fueled the development of new sequencing applications and promise to flood current databases with raw data. A number of factors prevent the seamless and easy use of these data, including the breadth of project goals, the wide array of tools that individually perform fractions of any given analysis, the large number of associated software/hardware dependencies, and the detailed expertise required to perform these analyses. To address these issues, we have developed an intuitive web-based environment with a wide assortment of integrated and cutting-edge bioinformatics tools in pre-configured workflows. These workflows, coupled with the ease of use of the environment, provide even novice next-generation sequencing users with the ability to perform many complex analyses with only a few mouse clicks and, within the context of the same environment, to visualize and further interrogate their results. This bioinformatics platform is an initial attempt at Empowering the Development of Genomics Expertise (EDGE) in a wide range of applications for microbial research. PMID:27899609

Enabling the democratization of the genomics revolution with a fully integrated web-based bioinformatics platform

DOE PAGES

Li, Po-E; Lo, Chien -Chi; Anderson, Joseph J.; ...

2016-11-24

Continued advancements in sequencing technologies have fueled the development of new sequencing applications and promise to flood current databases with raw data. A number of factors prevent the seamless and easy use of these data, including the breadth of project goals, the wide array of tools that individually perform fractions of any given analysis, the large number of associated software/hardware dependencies, and the detailed expertise required to perform these analyses. To address these issues, we have developed an intuitive web-based environment with a wide assortment of integrated and cutting-edge bioinformatics tools in pre-configured workflows. These workflows, coupled with the easemore » of use of the environment, provide even novice next-generation sequencing users with the ability to perform many complex analyses with only a few mouse clicks and, within the context of the same environment, to visualize and further interrogate their results. As a result, this bioinformatics platform is an initial attempt at Empowering the Development of Genomics Expertise (EDGE) in a wide range of applications for microbial research.« less

Operationalizing the Reciprocal Engagement Model of Genetic Counseling Practice: a Framework for the Scalable Delivery of Genomic Counseling and Testing.

PubMed

Schmidlen, Tara; Sturm, Amy C; Hovick, Shelly; Scheinfeldt, Laura; Scott Roberts, J; Morr, Lindsey; McElroy, Joseph; Toland, Amanda E; Christman, Michael; O'Daniel, Julianne M; Gordon, Erynn S; Bernhardt, Barbara A; Ormond, Kelly E; Sweet, Kevin

2018-02-19

With the advent of widespread genomic testing for diagnostic indications and disease risk assessment, there is increased need to optimize genetic counseling services to support the scalable delivery of precision medicine. Here, we describe how we operationalized the reciprocal engagement model of genetic counseling practice to develop a framework of counseling components and strategies for the delivery of genomic results. This framework was constructed based upon qualitative research with patients receiving genomic counseling following online receipt of potentially actionable complex disease and pharmacogenomics reports. Consultation with a transdisciplinary group of investigators, including practicing genetic counselors, was sought to ensure broad scope and applicability of these strategies for use with any large-scale genomic testing effort. We preserve the provision of pre-test education and informed consent as established in Mendelian/single-gene disease genetic counseling practice. Following receipt of genomic results, patients are afforded the opportunity to tailor the counseling agenda by selecting the specific test results they wish to discuss, specifying questions for discussion, and indicating their preference for counseling modality. The genetic counselor uses these patient preferences to set the genomic counseling session and to personalize result communication and risk reduction recommendations. Tailored visual aids and result summary reports divide areas of risk (genetic variant, family history, lifestyle) for each disease to facilitate discussion of multiple disease risks. Post-counseling, session summary reports are actively routed to both the patient and their physician team to encourage review and follow-up. Given the breadth of genomic information potentially resulting from genomic testing, this framework is put forth as a starting point to meet the need for scalable genetic counseling services in the delivery of precision medicine.

SpirPep: an in silico digestion-based platform to assist bioactive peptides discovery from a genome-wide database.

PubMed

Anekthanakul, Krittima; Hongsthong, Apiradee; Senachak, Jittisak; Ruengjitchatchawalya, Marasri

2018-04-20

Bioactive peptides, including biological sources-derived peptides with different biological activities, are protein fragments that influence the functions or conditions of organisms, in particular humans and animals. Conventional methods of identifying bioactive peptides are time-consuming and costly. To quicken the processes, several bioinformatics tools are recently used to facilitate screening of the potential peptides prior their activity assessment in vitro and/or in vivo. In this study, we developed an efficient computational method, SpirPep, which offers many advantages over the currently available tools. The SpirPep web application tool is a one-stop analysis and visualization facility to assist bioactive peptide discovery. The tool is equipped with 15 customized enzymes and 1-3 miscleavage options, which allows in silico digestion of protein sequences encoded by protein-coding genes from single, multiple, or genome-wide scaling, and then directly classifies the peptides by bioactivity using an in-house database that contains bioactive peptides collected from 13 public databases. With this tool, the resulting peptides are categorized by each selected enzyme, and shown in a tabular format where the peptide sequences can be tracked back to their original proteins. The developed tool and webpages are coded in PHP and HTML with CSS/JavaScript. Moreover, the tool allows protein-peptide alignment visualization by Generic Genome Browser (GBrowse) to display the region and details of the proteins and peptides within each parameter, while considering digestion design for the desirable bioactivity. SpirPep is efficient; it takes less than 20 min to digest 3000 proteins (751,860 amino acids) with 15 enzymes and three miscleavages for each enzyme, and only a few seconds for single enzyme digestion. Obviously, the tool identified more bioactive peptides than that of the benchmarked tool; an example of validated pentapeptide (FLPIL) from LC-MS/MS was demonstrated. The web and database server are available at http://spirpepapp.sbi.kmutt.ac.th . SpirPep, a web-based bioactive peptide discovery application, is an in silico-based tool with an overview of the results. The platform is a one-stop analysis and visualization facility; and offers advantages over the currently available tools. This tool may be useful for further bioactivity analysis and the quantitative discovery of desirable peptides.

Figure 4 from Integrative Genomics Viewer: Visualizing Big Data | Office of Cancer Genomics

Cancer.gov

Gene-list view of genomic data. The gene-list view allows users to compare data across a set of loci. The data in this figure includes copy number, mutation, and clinical data from 202 glioblastoma samples from TCGA. Adapted from Figure 7; Thorvaldsdottir H et al. 2012

Integrated Approach to Reconstruction of Microbial Regulatory Networks

DOE Office of Scientific and Technical Information (OSTI.GOV)

Rodionov, Dmitry A; Novichkov, Pavel S

2013-11-04

This project had the goal(s) of development of integrated bioinformatics platform for genome-scale inference and visualization of transcriptional regulatory networks (TRNs) in bacterial genomes. The work was done in Sanford-Burnham Medical Research Institute (SBMRI, P.I. D.A. Rodionov) and Lawrence Berkeley National Laboratory (LBNL, co-P.I. P.S. Novichkov). The developed computational resources include: (1) RegPredict web-platform for TRN inference and regulon reconstruction in microbial genomes, and (2) RegPrecise database for collection, visualization and comparative analysis of transcriptional regulons reconstructed by comparative genomics. These analytical resources were selected as key components in the DOE Systems Biology KnowledgeBase (SBKB). The high-quality data accumulated inmore » RegPrecise will provide essential datasets of reference regulons in diverse microbes to enable automatic reconstruction of draft TRNs in newly sequenced genomes. We outline our progress toward the three aims of this grant proposal, which were: Develop integrated platform for genome-scale regulon reconstruction; Infer regulatory annotations in several groups of bacteria and building of reference collections of microbial regulons; and Develop KnowledgeBase on microbial transcriptional regulation.« less

PhytoPath: an integrative resource for plant pathogen genomics.

PubMed

Pedro, Helder; Maheswari, Uma; Urban, Martin; Irvine, Alistair George; Cuzick, Alayne; McDowall, Mark D; Staines, Daniel M; Kulesha, Eugene; Hammond-Kosack, Kim Elizabeth; Kersey, Paul Julian

2016-01-04

PhytoPath (www.phytopathdb.org) is a resource for genomic and phenotypic data from plant pathogen species, that integrates phenotypic data for genes from PHI-base, an expertly curated catalog of genes with experimentally verified pathogenicity, with the Ensembl tools for data visualization and analysis. The resource is focused on fungi, protists (oomycetes) and bacterial plant pathogens that have genomes that have been sequenced and annotated. Genes with associated PHI-base data can be easily identified across all plant pathogen species using a BioMart-based query tool and visualized in their genomic context on the Ensembl genome browser. The PhytoPath resource contains data for 135 genomic sequences from 87 plant pathogen species, and 1364 genes curated for their role in pathogenicity and as targets for chemical intervention. Support for community annotation of gene models is provided using the WebApollo online gene editor, and we are working with interested communities to improve reference annotation for selected species. © The Author(s) 2015. Published by Oxford University Press on behalf of Nucleic Acids Research.

GMO detection in food and feed through screening by visual loop-mediated isothermal amplification assays.

PubMed

Wang, Cong; Li, Rong; Quan, Sheng; Shen, Ping; Zhang, Dabing; Shi, Jianxin; Yang, Litao

2015-06-01

Isothermal DNA/RNA amplification techniques are the primary methodology for developing on-spot rapid nucleic acid amplification assays, and the loop-mediated isothermal amplification (LAMP) technique has been developed and applied in the detection of foodborne pathogens, plant/animal viruses, and genetically modified (GM) food/feed contents. In this study, one set of LAMP assays targeting on eight frequently used universal elements, marker genes, and exogenous target genes, such as CaMV35S promoter, FMV35S promoter, NOS, bar, cry1Ac, CP4 epsps, pat, and NptII, were developed for visual screening of GM contents in plant-derived food samples with high efficiency and accuracy. For these eight LAMP assays, their specificity was evaluated by testing commercial GM plant events and their limits of detection were also determined, which are 10 haploid genome equivalents (HGE) for FMV35S promoter, cry1Ac, and pat assays, as well as five HGE for CaMV35S promoter, bar, NOS terminator, CP4 epsps, and NptII assays. The screening applicability of these LAMP assays was further validated successfully using practical canola, soybean, and maize samples. The results suggested that the established visual LAMP assays are applicable and cost-effective for GM screening in plant-derived food samples.

TEA: the epigenome platform for Arabidopsis methylome study.

PubMed

Su, Sheng-Yao; Chen, Shu-Hwa; Lu, I-Hsuan; Chiang, Yih-Shien; Wang, Yu-Bin; Chen, Pao-Yang; Lin, Chung-Yen

2016-12-22

Bisulfite sequencing (BS-seq) has become a standard technology to profile genome-wide DNA methylation at single-base resolution. It allows researchers to conduct genome-wise cytosine methylation analyses on issues about genomic imprinting, transcriptional regulation, cellular development and differentiation. One single data from a BS-Seq experiment is resolved into many features according to the sequence contexts, making methylome data analysis and data visualization a complex task. We developed a streamlined platform, TEA, for analyzing and visualizing data from whole-genome BS-Seq (WGBS) experiments conducted in the model plant Arabidopsis thaliana. To capture the essence of the genome methylation level and to meet the efficiency for running online, we introduce a straightforward method for measuring genome methylation in each sequence context by gene. The method is scripted in Java to process BS-Seq mapping results. Through a simple data uploading process, the TEA server deploys a web-based platform for deep analysis by linking data to an updated Arabidopsis annotation database and toolkits. TEA is an intuitive and efficient online platform for analyzing the Arabidopsis genomic DNA methylation landscape. It provides several ways to help users exploit WGBS data. TEA is freely accessible for academic users at: http://tea.iis.sinica.edu.tw .

The vertebrate ancestral repertoire of visual opsins, transducin alpha subunits and oxytocin/vasopressin receptors was established by duplication of their shared genomic region in the two rounds of early vertebrate genome duplications.

PubMed

Lagman, David; Ocampo Daza, Daniel; Widmark, Jenny; Abalo, Xesús M; Sundström, Görel; Larhammar, Dan

2013-11-02

Vertebrate color vision is dependent on four major color opsin subtypes: RH2 (green opsin), SWS1 (ultraviolet opsin), SWS2 (blue opsin), and LWS (red opsin). Together with the dim-light receptor rhodopsin (RH1), these form the family of vertebrate visual opsins. Vertebrate genomes contain many multi-membered gene families that can largely be explained by the two rounds of whole genome duplication (WGD) in the vertebrate ancestor (2R) followed by a third round in the teleost ancestor (3R). Related chromosome regions resulting from WGD or block duplications are said to form a paralogon. We describe here a paralogon containing the genes for visual opsins, the G-protein alpha subunit families for transducin (GNAT) and adenylyl cyclase inhibition (GNAI), the oxytocin and vasopressin receptors (OT/VP-R), and the L-type voltage-gated calcium channels (CACNA1-L). Sequence-based phylogenies and analyses of conserved synteny show that the above-mentioned gene families, and many neighboring gene families, expanded in the early vertebrate WGDs. This allows us to deduce the following evolutionary scenario: The vertebrate ancestor had a chromosome containing the genes for two visual opsins, one GNAT, one GNAI, two OT/VP-Rs and one CACNA1-L gene. This chromosome was quadrupled in 2R. Subsequent gene losses resulted in a set of five visual opsin genes, three GNAT and GNAI genes, six OT/VP-R genes and four CACNA1-L genes. These regions were duplicated again in 3R resulting in additional teleost genes for some of the families. Major chromosomal rearrangements have taken place in the teleost genomes. By comparison with the corresponding chromosomal regions in the spotted gar, which diverged prior to 3R, we could time these rearrangements to post-3R. We present an extensive analysis of the paralogon housing the visual opsin, GNAT and GNAI, OT/VP-R, and CACNA1-L gene families. The combined data imply that the early vertebrate WGD events contributed to the evolution of vision and the other neuronal and neuroendocrine functions exerted by the proteins encoded by these gene families. In pouched lamprey all five visual opsin genes have previously been identified, suggesting that lampreys diverged from the jawed vertebrates after 2R.

The BioCyc collection of microbial genomes and metabolic pathways.

PubMed

Karp, Peter D; Billington, Richard; Caspi, Ron; Fulcher, Carol A; Latendresse, Mario; Kothari, Anamika; Keseler, Ingrid M; Krummenacker, Markus; Midford, Peter E; Ong, Quang; Ong, Wai Kit; Paley, Suzanne M; Subhraveti, Pallavi

2017-08-17

BioCyc.org is a microbial genome Web portal that combines thousands of genomes with additional information inferred by computer programs, imported from other databases and curated from the biomedical literature by biologist curators. BioCyc also provides an extensive range of query tools, visualization services and analysis software. Recent advances in BioCyc include an expansion in the content of BioCyc in terms of both the number of genomes and the types of information available for each genome; an expansion in the amount of curated content within BioCyc; and new developments in the BioCyc software tools including redesigned gene/protein pages and metabolite pages; new search tools; a new sequence-alignment tool; a new tool for visualizing groups of related metabolic pathways; and a facility called SmartTables, which enables biologists to perform analyses that previously would have required a programmer's assistance. © The Author 2017. Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

UCSC Xena | Informatics Technology for Cancer Research (ITCR)

Cancer.gov

UCSC Xena securely analyzes and visualizes your private functional genomics data set in the context of public and shared genomic/phenotypic data sets such as TCGA, ICGC, TARGET, GTEx, and GA4GH (TOIL).

iSeq: Web-Based RNA-seq Data Analysis and Visualization.

PubMed

Zhang, Chao; Fan, Caoqi; Gan, Jingbo; Zhu, Ping; Kong, Lei; Li, Cheng

2018-01-01

Transcriptome sequencing (RNA-seq) is becoming a standard experimental methodology for genome-wide characterization and quantification of transcripts at single base-pair resolution. However, downstream analysis of massive amount of sequencing data can be prohibitively technical for wet-lab researchers. A functionally integrated and user-friendly platform is required to meet this demand. Here, we present iSeq, an R-based Web server, for RNA-seq data analysis and visualization. iSeq is a streamlined Web-based R application under the Shiny framework, featuring a simple user interface and multiple data analysis modules. Users without programming and statistical skills can analyze their RNA-seq data and construct publication-level graphs through a standardized yet customizable analytical pipeline. iSeq is accessible via Web browsers on any operating system at http://iseq.cbi.pku.edu.cn .

Millstone: software for multiplex microbial genome analysis and engineering

DOE Office of Scientific and Technical Information (OSTI.GOV)

Goodman, Daniel B.; Kuznetsov, Gleb; Lajoie, Marc J.

Inexpensive DNA sequencing and advances in genome editing have made computational analysis a major rate-limiting step in adaptive laboratory evolution and microbial genome engineering. Here, we describe Millstone, a web-based platform that automates genotype comparison and visualization for projects with up to hundreds of genomic samples. To enable iterative genome engineering, Millstone allows users to design oligonucleotide libraries and create successive versions of reference genomes. Millstone is open source and easily deployable to a cloud platform, local cluster, or desktop, making it a scalable solution for any lab.

Millstone: software for multiplex microbial genome analysis and engineering.

PubMed

Goodman, Daniel B; Kuznetsov, Gleb; Lajoie, Marc J; Ahern, Brian W; Napolitano, Michael G; Chen, Kevin Y; Chen, Changping; Church, George M

2017-05-25

Inexpensive DNA sequencing and advances in genome editing have made computational analysis a major rate-limiting step in adaptive laboratory evolution and microbial genome engineering. We describe Millstone, a web-based platform that automates genotype comparison and visualization for projects with up to hundreds of genomic samples. To enable iterative genome engineering, Millstone allows users to design oligonucleotide libraries and create successive versions of reference genomes. Millstone is open source and easily deployable to a cloud platform, local cluster, or desktop, making it a scalable solution for any lab.

Millstone: software for multiplex microbial genome analysis and engineering

DOE PAGES

Goodman, Daniel B.; Kuznetsov, Gleb; Lajoie, Marc J.; ...

2017-05-25

Inexpensive DNA sequencing and advances in genome editing have made computational analysis a major rate-limiting step in adaptive laboratory evolution and microbial genome engineering. Here, we describe Millstone, a web-based platform that automates genotype comparison and visualization for projects with up to hundreds of genomic samples. To enable iterative genome engineering, Millstone allows users to design oligonucleotide libraries and create successive versions of reference genomes. Millstone is open source and easily deployable to a cloud platform, local cluster, or desktop, making it a scalable solution for any lab.

RareVariantVis: new tool for visualization of causative variants in rare monogenic disorders using whole genome sequencing data.

PubMed

Stokowy, Tomasz; Garbulowski, Mateusz; Fiskerstrand, Torunn; Holdhus, Rita; Labun, Kornel; Sztromwasser, Pawel; Gilissen, Christian; Hoischen, Alexander; Houge, Gunnar; Petersen, Kjell; Jonassen, Inge; Steen, Vidar M

2016-10-01

The search for causative genetic variants in rare diseases of presumed monogenic inheritance has been boosted by the implementation of whole exome (WES) and whole genome (WGS) sequencing. In many cases, WGS seems to be superior to WES, but the analysis and visualization of the vast amounts of data is demanding. To aid this challenge, we have developed a new tool-RareVariantVis-for analysis of genome sequence data (including non-coding regions) for both germ line and somatic variants. It visualizes variants along their respective chromosomes, providing information about exact chromosomal position, zygosity and frequency, with point-and-click information regarding dbSNP IDs, gene association and variant inheritance. Rare variants as well as de novo variants can be flagged in different colors. We show the performance of the RareVariantVis tool in the Genome in a Bottle WGS data set. https://www.bioconductor.org/packages/3.3/bioc/html/RareVariantVis.html tomasz.stokowy@k2.uib.no 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.

CyanoBase: the cyanobacteria genome database update 2010

PubMed Central

Nakao, Mitsuteru; Okamoto, Shinobu; Kohara, Mitsuyo; Fujishiro, Tsunakazu; Fujisawa, Takatomo; Sato, Shusei; Tabata, Satoshi; Kaneko, Takakazu; Nakamura, Yasukazu

2010-01-01

CyanoBase (http://genome.kazusa.or.jp/cyanobase) is the genome database for cyanobacteria, which are model organisms for photosynthesis. The database houses cyanobacteria species information, complete genome sequences, genome-scale experiment data, gene information, gene annotations and mutant information. In this version, we updated these datasets and improved the navigation and the visual display of the data views. In addition, a web service API now enables users to retrieve the data in various formats with other tools, seamlessly. PMID:19880388

Bolbase: a comprehensive genomics database for Brassica oleracea.

PubMed

Yu, Jingyin; Zhao, Meixia; Wang, Xiaowu; Tong, Chaobo; Huang, Shunmou; Tehrim, Sadia; Liu, Yumei; Hua, Wei; Liu, Shengyi

2013-09-30

Brassica oleracea is a morphologically diverse species in the family Brassicaceae and contains a group of nutrition-rich vegetable crops, including common heading cabbage, cauliflower, broccoli, kohlrabi, kale, Brussels sprouts. This diversity along with its phylogenetic membership in a group of three diploid and three tetraploid species, and the recent availability of genome sequences within Brassica provide an unprecedented opportunity to study intra- and inter-species divergence and evolution in this species and its close relatives. We have developed a comprehensive database, Bolbase, which provides access to the B. oleracea genome data and comparative genomics information. The whole genome of B. oleracea is available, including nine fully assembled chromosomes and 1,848 scaffolds, with 45,758 predicted genes, 13,382 transposable elements, and 3,581 non-coding RNAs. Comparative genomics information is available, including syntenic regions among B. oleracea, Brassica rapa and Arabidopsis thaliana, synonymous (Ks) and non-synonymous (Ka) substitution rates between orthologous gene pairs, gene families or clusters, and differences in quantity, category, and distribution of transposable elements on chromosomes. Bolbase provides useful search and data mining tools, including a keyword search, a local BLAST server, and a customized GBrowse tool, which can be used to extract annotations of genome components, identify similar sequences and visualize syntenic regions among species. Users can download all genomic data and explore comparative genomics in a highly visual setting. Bolbase is the first resource platform for the B. oleracea genome and for genomic comparisons with its relatives, and thus it will help the research community to better study the function and evolution of Brassica genomes as well as enhance molecular breeding research. This database will be updated regularly with new features, improvements to genome annotation, and new genomic sequences as they become available. Bolbase is freely available at http://ocri-genomics.org/bolbase.

Expanded national database collection and data coverage in the FINDbase worldwide database for clinically relevant genomic variation allele frequencies

PubMed Central

Viennas, Emmanouil; Komianou, Angeliki; Mizzi, Clint; Stojiljkovic, Maja; Mitropoulou, Christina; Muilu, Juha; Vihinen, Mauno; Grypioti, Panagiota; Papadaki, Styliani; Pavlidis, Cristiana; Zukic, Branka; Katsila, Theodora; van der Spek, Peter J.; Pavlovic, Sonja; Tzimas, Giannis; Patrinos, George P.

2017-01-01

FINDbase (http://www.findbase.org) is a comprehensive data repository that records the prevalence of clinically relevant genomic variants in various populations worldwide, such as pathogenic variants leading mostly to monogenic disorders and pharmacogenomics biomarkers. The database also records the incidence of rare genetic diseases in various populations, all in well-distinct data modules. Here, we report extensive data content updates in all data modules, with direct implications to clinical pharmacogenomics. Also, we report significant new developments in FINDbase, namely (i) the release of a new version of the ETHNOS software that catalyzes development curation of national/ethnic genetic databases, (ii) the migration of all FINDbase data content into 90 distinct national/ethnic mutation databases, all built around Microsoft's PivotViewer (http://www.getpivot.com) software (iii) new data visualization tools and (iv) the interrelation of FINDbase with DruGeVar database with direct implications in clinical pharmacogenomics. The abovementioned updates further enhance the impact of FINDbase, as a key resource for Genomic Medicine applications. PMID:27924022

Editing the Neuronal Genome: a CRISPR View of Chromatin Regulation in Neuronal Development, Function, and Plasticity

PubMed Central

Yang, Marty G.; West, Anne E.

2016-01-01

The dynamic orchestration of gene expression is crucial for the proper differentiation, function, and adaptation of cells. In the brain, transcriptional regulation underlies the incredible diversity of neuronal cell types and contributes to the ability of neurons to adapt their function to the environment. Recently, novel methods for genome and epigenome editing have begun to revolutionize our understanding of gene regulatory mechanisms. In particular, the clustered regularly interspaced short palindromic repeats (CRISPR)/Cas9 system has proven to be a particularly accessible and adaptable technique for genome engineering. Here, we review the use of CRISPR/Cas9 in neurobiology and discuss how these studies have advanced understanding of nervous system development and plasticity. We cover four especially salient applications of CRISPR/Cas9: testing the consequences of enhancer mutations, tagging genes and gene products for visualization in live cells, directly activating or repressing enhancers in vivo, and manipulating the epigenome. In each case, we summarize findings from recent studies and discuss evolving adaptations of the method. PMID:28018138

Tripal: a construction toolkit for online genome databases.

PubMed

Ficklin, Stephen P; Sanderson, Lacey-Anne; Cheng, Chun-Huai; Staton, Margaret E; Lee, Taein; Cho, Il-Hyung; Jung, Sook; Bett, Kirstin E; Main, Doreen

2011-01-01

As the availability, affordability and magnitude of genomics and genetics research increases so does the need to provide online access to resulting data and analyses. Availability of a tailored online database is the desire for many investigators or research communities; however, managing the Information Technology infrastructure needed to create such a database can be an undesired distraction from primary research or potentially cost prohibitive. Tripal provides simplified site development by merging the power of Drupal, a popular web Content Management System with that of Chado, a community-derived database schema for storage of genomic, genetic and other related biological data. Tripal provides an interface that extends the content management features of Drupal to the data housed in Chado. Furthermore, Tripal provides a web-based Chado installer, genomic data loaders, web-based editing of data for organisms, genomic features, biological libraries, controlled vocabularies and stock collections. Also available are Tripal extensions that support loading and visualizations of NCBI BLAST, InterPro, Kyoto Encyclopedia of Genes and Genomes and Gene Ontology analyses, as well as an extension that provides integration of Tripal with GBrowse, a popular GMOD tool. An Application Programming Interface is available to allow creation of custom extensions by site developers, and the look-and-feel of the site is completely customizable through Drupal-based PHP template files. Addition of non-biological content and user-management is afforded through Drupal. Tripal is an open source and freely available software package found at http://tripal.sourceforge.net.

Tripal: a construction toolkit for online genome databases

PubMed Central

Sanderson, Lacey-Anne; Cheng, Chun-Huai; Staton, Margaret E.; Lee, Taein; Cho, Il-Hyung; Jung, Sook; Bett, Kirstin E.; Main, Doreen

2011-01-01

As the availability, affordability and magnitude of genomics and genetics research increases so does the need to provide online access to resulting data and analyses. Availability of a tailored online database is the desire for many investigators or research communities; however, managing the Information Technology infrastructure needed to create such a database can be an undesired distraction from primary research or potentially cost prohibitive. Tripal provides simplified site development by merging the power of Drupal, a popular web Content Management System with that of Chado, a community-derived database schema for storage of genomic, genetic and other related biological data. Tripal provides an interface that extends the content management features of Drupal to the data housed in Chado. Furthermore, Tripal provides a web-based Chado installer, genomic data loaders, web-based editing of data for organisms, genomic features, biological libraries, controlled vocabularies and stock collections. Also available are Tripal extensions that support loading and visualizations of NCBI BLAST, InterPro, Kyoto Encyclopedia of Genes and Genomes and Gene Ontology analyses, as well as an extension that provides integration of Tripal with GBrowse, a popular GMOD tool. An Application Programming Interface is available to allow creation of custom extensions by site developers, and the look-and-feel of the site is completely customizable through Drupal-based PHP template files. Addition of non-biological content and user-management is afforded through Drupal. Tripal is an open source and freely available software package found at http://tripal.sourceforge.net PMID:21959868

Assessing pooled BAC and whole genome shotgun strategies for assembly of complex genomes.

PubMed

Haiminen, Niina; Feltus, F Alex; Parida, Laxmi

2011-04-15

We investigate if pooling BAC clones and sequencing the pools can provide for more accurate assembly of genome sequences than the "whole genome shotgun" (WGS) approach. Furthermore, we quantify this accuracy increase. We compare the pooled BAC and WGS approaches using in silico simulations. Standard measures of assembly quality focus on assembly size and fragmentation, which are desirable for large whole genome assemblies. We propose additional measures enabling easy and visual comparison of assembly quality, such as rearrangements and redundant sequence content, relative to the known target sequence. The best assembly quality scores were obtained using 454 coverage of 15× linear and 5× paired (3kb insert size) reads (15L-5P) on Arabidopsis. This regime gave similarly good results on four additional plant genomes of very different GC and repeat contents. BAC pooling improved assembly scores over WGS assembly, coverage and redundancy scores improving the most. BAC pooling works better than WGS, however, both require a physical map to order the scaffolds. Pool sizes up to 12Mbp work well, suggesting this pooling density to be effective in medium-scale re-sequencing applications such as targeted sequencing of QTL intervals for candidate gene discovery. Assuming the current Roche/454 Titanium sequencing limitations, a 12 Mbp region could be re-sequenced with a full plate of linear reads and a half plate of paired-end reads, yielding 15L-5P coverage after read pre-processing. Our simulation suggests that massively over-sequencing may not improve accuracy. Our scoring measures can be used generally to evaluate and compare results of simulated genome assemblies.

ActiveDriverDB: human disease mutations and genome variation in post-translational modification sites of proteins

PubMed Central

Krassowski, Michal; Paczkowska, Marta; Cullion, Kim; Huang, Tina; Dzneladze, Irakli; Ouellette, B F Francis; Yamada, Joseph T; Fradet-Turcotte, Amelie

2018-01-01

Abstract Interpretation of genetic variation is needed for deciphering genotype-phenotype associations, mechanisms of inherited disease, and cancer driver mutations. Millions of single nucleotide variants (SNVs) in human genomes are known and thousands are associated with disease. An estimated 21% of disease-associated amino acid substitutions corresponding to missense SNVs are located in protein sites of post-translational modifications (PTMs), chemical modifications of amino acids that extend protein function. ActiveDriverDB is a comprehensive human proteo-genomics database that annotates disease mutations and population variants through the lens of PTMs. We integrated >385,000 published PTM sites with ∼3.6 million substitutions from The Cancer Genome Atlas (TCGA), the ClinVar database of disease genes, and human genome sequencing projects. The database includes site-specific interaction networks of proteins, upstream enzymes such as kinases, and drugs targeting these enzymes. We also predicted network-rewiring impact of mutations by analyzing gains and losses of kinase-bound sequence motifs. ActiveDriverDB provides detailed visualization, filtering, browsing and searching options for studying PTM-associated mutations. Users can upload mutation datasets interactively and use our application programming interface in pipelines. Integrative analysis of mutations and PTMs may help decipher molecular mechanisms of phenotypes and disease, as exemplified by case studies of TP53, BRCA2 and VHL. The open-source database is available at https://www.ActiveDriverDB.org. PMID:29126202

Gee Fu: a sequence version and web-services database tool for genomic assembly, genome feature and NGS data.

PubMed

Ramirez-Gonzalez, Ricardo; Caccamo, Mario; MacLean, Daniel

2011-10-01

Scientists now use high-throughput sequencing technologies and short-read assembly methods to create draft genome assemblies in just days. Tools and pipelines like the assembler, and the workflow management environments make it easy for a non-specialist to implement complicated pipelines to produce genome assemblies and annotations very quickly. Such accessibility results in a proliferation of assemblies and associated files, often for many organisms. These assemblies get used as a working reference by lots of different workers, from a bioinformatician doing gene prediction or a bench scientist designing primers for PCR. Here we describe Gee Fu, a database tool for genomic assembly and feature data, including next-generation sequence alignments. Gee Fu is an instance of a Ruby-On-Rails web application on a feature database that provides web and console interfaces for input, visualization of feature data via AnnoJ, access to data through a web-service interface, an API for direct data access by Ruby scripts and access to feature data stored in BAM files. Gee Fu provides a platform for storing and sharing different versions of an assembly and associated features that can be accessed and updated by bench biologists and bioinformaticians in ways that are easy and useful for each. http://tinyurl.com/geefu dan.maclean@tsl.ac.uk.

BusyBee Web: metagenomic data analysis by bootstrapped supervised binning and annotation

PubMed Central

Kiefer, Christina; Fehlmann, Tobias; Backes, Christina

2017-01-01

Abstract Metagenomics-based studies of mixed microbial communities are impacting biotechnology, life sciences and medicine. Computational binning of metagenomic data is a powerful approach for the culture-independent recovery of population-resolved genomic sequences, i.e. from individual or closely related, constituent microorganisms. Existing binning solutions often require a priori characterized reference genomes and/or dedicated compute resources. Extending currently available reference-independent binning tools, we developed the BusyBee Web server for the automated deconvolution of metagenomic data into population-level genomic bins using assembled contigs (Illumina) or long reads (Pacific Biosciences, Oxford Nanopore Technologies). A reversible compression step as well as bootstrapped supervised binning enable quick turnaround times. The binning results are represented in interactive 2D scatterplots. Moreover, bin quality estimates, taxonomic annotations and annotations of antibiotic resistance genes are computed and visualized. Ground truth-based benchmarks of BusyBee Web demonstrate comparably high performance to state-of-the-art binning solutions for assembled contigs and markedly improved performance for long reads (median F1 scores: 70.02–95.21%). Furthermore, the applicability to real-world metagenomic datasets is shown. In conclusion, our reference-independent approach automatically bins assembled contigs or long reads, exhibits high sensitivity and precision, enables intuitive inspection of the results, and only requires FASTA-formatted input. The web-based application is freely accessible at: https://ccb-microbe.cs.uni-saarland.de/busybee. PMID:28472498

ABACAS: algorithm-based automatic contiguation of assembled sequences

PubMed Central

Assefa, Samuel; Keane, Thomas M.; Otto, Thomas D.; Newbold, Chris; Berriman, Matthew

2009-01-01

Summary: Due to the availability of new sequencing technologies, we are now increasingly interested in sequencing closely related strains of existing finished genomes. Recently a number of de novo and mapping-based assemblers have been developed to produce high quality draft genomes from new sequencing technology reads. New tools are necessary to take contigs from a draft assembly through to a fully contiguated genome sequence. ABACAS is intended as a tool to rapidly contiguate (align, order, orientate), visualize and design primers to close gaps on shotgun assembled contigs based on a reference sequence. The input to ABACAS is a set of contigs which will be aligned to the reference genome, ordered and orientated, visualized in the ACT comparative browser, and optimal primer sequences are automatically generated. Availability and Implementation: ABACAS is implemented in Perl and is freely available for download from http://abacas.sourceforge.net Contact: sa4@sanger.ac.uk PMID:19497936

UCbase 2.0: ultraconserved sequences database (2014 update)

PubMed Central

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

BiQ Analyzer HT: locus-specific analysis of DNA methylation by high-throughput bisulfite sequencing

PubMed Central

Lutsik, Pavlo; Feuerbach, Lars; Arand, Julia; Lengauer, Thomas; Walter, Jörn; Bock, Christoph

2011-01-01

Bisulfite sequencing is a widely used method for measuring DNA methylation in eukaryotic genomes. The assay provides single-base pair resolution and, given sufficient sequencing depth, its quantitative accuracy is excellent. High-throughput sequencing of bisulfite-converted DNA can be applied either genome wide or targeted to a defined set of genomic loci (e.g. using locus-specific PCR primers or DNA capture probes). Here, we describe BiQ Analyzer HT (http://biq-analyzer-ht.bioinf.mpi-inf.mpg.de/), a user-friendly software tool that supports locus-specific analysis and visualization of high-throughput bisulfite sequencing data. The software facilitates the shift from time-consuming clonal bisulfite sequencing to the more quantitative and cost-efficient use of high-throughput sequencing for studying locus-specific DNA methylation patterns. In addition, it is useful for locus-specific visualization of genome-wide bisulfite sequencing data. PMID:21565797

Figure 2 from Integrative Genomics Viewer: Visualizing Big Data | Office of Cancer Genomics

Cancer.gov

Grouping and sorting genomic data in IGV. The IGV user interface displaying 202 glioblastoma samples from TCGA. Samples are grouped by tumor subtype (second annotation column) and data type (first annotation column) and sorted by copy number of the EGFR locus (middle column). Adapted from Figure 1; Robinson et al. 2011

Figure 5 from Integrative Genomics Viewer: Visualizing Big Data | Office of Cancer Genomics

Cancer.gov

Split-Screen View. The split-screen view is useful for exploring relationships of genomic features that are independent of chromosomal location. Color is used here to indicate mate pairs that map to different chromosomes, chromosomes 1 and 6, suggesting a translocation event. Adapted from Figure 8; Thorvaldsdottir H et al. 2012

CAS-viewer: web-based tool for splicing-guided integrative analysis of multi-omics cancer data.

PubMed

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.

B-CAN: a resource sharing platform to improve the operation, visualization and integrated analysis of TCGA breast cancer data.

PubMed

Wen, Can-Hong; Ou, Shao-Min; Guo, Xiao-Bo; Liu, Chen-Feng; Shen, Yan-Bo; You, Na; Cai, Wei-Hong; Shen, Wen-Jun; Wang, Xue-Qin; Tan, Hai-Zhu

2017-12-12

Breast cancer is a high-risk heterogeneous disease with myriad subtypes and complicated biological features. The Cancer Genome Atlas (TCGA) breast cancer database provides researchers with the large-scale genome and clinical data via web portals and FTP services. Researchers are able to gain new insights into their related fields, and evaluate experimental discoveries with TCGA. However, it is difficult for researchers who have little experience with database and bioinformatics to access and operate on because of TCGA's complex data format and diverse files. For ease of use, we build the breast cancer (B-CAN) platform, which enables data customization, data visualization, and private data center. The B-CAN platform runs on Apache server and interacts with the backstage of MySQL database by PHP. Users can customize data based on their needs by combining tables from original TCGA database and selecting variables from each table. The private data center is applicable for private data and two types of customized data. A key feature of the B-CAN is that it provides single table display and multiple table display. Customized data with one barcode corresponding to many records and processed customized data are allowed in Multiple Tables Display. The B-CAN is an intuitive and high-efficient data-sharing platform.

Plant Reactome: a resource for plant pathways and comparative analysis.

PubMed

Naithani, Sushma; Preece, Justin; D'Eustachio, Peter; Gupta, Parul; Amarasinghe, Vindhya; Dharmawardhana, Palitha D; Wu, Guanming; Fabregat, Antonio; Elser, Justin L; Weiser, Joel; Keays, Maria; Fuentes, Alfonso Munoz-Pomer; Petryszak, Robert; Stein, Lincoln D; Ware, Doreen; Jaiswal, Pankaj

2017-01-04

Plant Reactome (http://plantreactome.gramene.org/) is a free, open-source, curated plant pathway database portal, provided as part of the Gramene project. The database provides intuitive bioinformatics tools for the visualization, analysis and interpretation of pathway knowledge to support genome annotation, genome analysis, modeling, systems biology, basic research and education. Plant Reactome employs the structural framework of a plant cell to show metabolic, transport, genetic, developmental and signaling pathways. We manually curate molecular details of pathways in these domains for reference species Oryza sativa (rice) supported by published literature and annotation of well-characterized genes. Two hundred twenty-two rice pathways, 1025 reactions associated with 1173 proteins, 907 small molecules and 256 literature references have been curated to date. These reference annotations were used to project pathways for 62 model, crop and evolutionarily significant plant species based on gene homology. Database users can search and browse various components of the database, visualize curated baseline expression of pathway-associated genes provided by the Expression Atlas and upload and analyze their Omics datasets. The database also offers data access via Application Programming Interfaces (APIs) and in various standardized pathway formats, such as SBML and BioPAX. © The Author(s) 2016. Published by Oxford University Press on behalf of Nucleic Acids Research.

MCScanX: a toolkit for detection and evolutionary analysis of gene synteny and collinearity

PubMed Central

Wang, Yupeng; Tang, Haibao; DeBarry, Jeremy D.; Tan, Xu; Li, Jingping; Wang, Xiyin; Lee, Tae-ho; Jin, Huizhe; Marler, Barry; Guo, Hui; Kissinger, Jessica C.; Paterson, Andrew H.

2012-01-01

MCScan is an algorithm able to scan multiple genomes or subgenomes in order to identify putative homologous chromosomal regions, and align these regions using genes as anchors. The MCScanX toolkit implements an adjusted MCScan algorithm for detection of synteny and collinearity that extends the original software by incorporating 14 utility programs for visualization of results and additional downstream analyses. Applications of MCScanX to several sequenced plant genomes and gene families are shown as examples. MCScanX can be used to effectively analyze chromosome structural changes, and reveal the history of gene family expansions that might contribute to the adaptation of lineages and taxa. An integrated view of various modes of gene duplication can supplement the traditional gene tree analysis in specific families. The source code and documentation of MCScanX are freely available at http://chibba.pgml.uga.edu/mcscan2/. PMID:22217600

Maser: one-stop platform for NGS big data from analysis to visualization

PubMed Central

Kinjo, Sonoko; Monma, Norikazu; Misu, Sadahiko; Kitamura, Norikazu; Imoto, Junichi; Yoshitake, Kazutoshi; Gojobori, Takashi; Ikeo, Kazuho

2018-01-01

Abstract A major challenge in analyzing the data from high-throughput next-generation sequencing (NGS) is how to handle the huge amounts of data and variety of NGS tools and visualize the resultant outputs. To address these issues, we developed a cloud-based data analysis platform, Maser (Management and Analysis System for Enormous Reads), and an original genome browser, Genome Explorer (GE). Maser enables users to manage up to 2 terabytes of data to conduct analyses with easy graphical user interface operations and offers analysis pipelines in which several individual tools are combined as a single pipeline for very common and standard analyses. GE automatically visualizes genome assembly and mapping results output from Maser pipelines, without requiring additional data upload. With this function, the Maser pipelines can graphically display the results output from all the embedded tools and mapping results in a web browser. Therefore Maser realized a more user-friendly analysis platform especially for beginners by improving graphical display and providing the selected standard pipelines that work with built-in genome browser. In addition, all the analyses executed on Maser are recorded in the analysis history, helping users to trace and repeat the analyses. The entire process of analysis and its histories can be shared with collaborators or opened to the public. In conclusion, our system is useful for managing, analyzing, and visualizing NGS data and achieves traceability, reproducibility, and transparency of NGS analysis. Database URL: http://cell-innovation.nig.ac.jp/maser/ PMID:29688385

The CRISPR-Cas system - from bacterial immunity to genome engineering.

PubMed

Czarnek, Maria; Bereta, Joanna

2016-09-01

Precise and efficient genome modifications present a great value in attempts to comprehend the roles of particular genes and other genetic elements in biological processes as well as in various pathologies. In recent years novel methods of genome modification known as genome editing, which utilize so called "programmable" nucleases, came into use. A true revolution in genome editing has been brought about by the introduction of the CRISP-Cas (clustered regularly interspaced short palindromic repeats-CRISPR associated) system, in which one of such nucleases, i.e. Cas9, plays a major role. This system is based on the elements of the bacterial and archaeal mechanism responsible for acquired immunity against phage infections and transfer of foreign genetic material. Microorganisms incorporate fragments of foreign DNA into CRISPR loci present in their genomes, which enables fast recognition and elimination of future infections. There are several types of CRISPR-Cas systems among prokaryotes but only elements of CRISPR type II are employed in genome engineering. CRISPR-Cas type II utilizes small RNA molecules (crRNA and tracrRNA) to precisely direct the effector nuclease - Cas9 - to a specific site in the genome, i.e. to the sequence complementary to crRNA. Cas9 may be used to: (i) introduce stable changes into genomes e.g. in the process of generation of knock-out and knock-in animals and cell lines, (ii) activate or silence the expression of a gene of interest, and (iii) visualize specific sites in genomes of living cells. The CRISPR-Cas-based tools have been successfully employed for generation of animal and cell models of a number of diseases, e.g. specific types of cancer. In the future, the genome editing by programmable nucleases may find wide application in medicine e.g. in the therapies of certain diseases of genetic origin and in the therapy of HIV-infected patients.

MOST-visualization: software for producing automated textbook-style maps of genome-scale metabolic networks.

PubMed

Kelley, James J; Maor, Shay; Kim, Min Kyung; Lane, Anatoliy; Lun, Desmond S

2017-08-15

Visualization of metabolites, reactions and pathways in genome-scale metabolic networks (GEMs) can assist in understanding cellular metabolism. Three attributes are desirable in software used for visualizing GEMs: (i) automation, since GEMs can be quite large; (ii) production of understandable maps that provide ease in identification of pathways, reactions and metabolites; and (iii) visualization of the entire network to show how pathways are interconnected. No software currently exists for visualizing GEMs that satisfies all three characteristics, but MOST-Visualization, an extension of the software package MOST (Metabolic Optimization and Simulation Tool), satisfies (i), and by using a pre-drawn overview map of metabolism based on the Roche map satisfies (ii) and comes close to satisfying (iii). MOST is distributed for free on the GNU General Public License. The software and full documentation are available at http://most.ccib.rutgers.edu/. dslun@rutgers.edu. Supplementary data are available at Bioinformatics online. © The Author (2017). Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oup.com

VAT: a computational framework to functionally annotate variants in personal genomes within a cloud-computing environment

PubMed Central

Habegger, Lukas; Balasubramanian, Suganthi; Chen, David Z.; Khurana, Ekta; Sboner, Andrea; Harmanci, Arif; Rozowsky, Joel; Clarke, Declan; Snyder, Michael; Gerstein, Mark

2012-01-01

Summary: The functional annotation of variants obtained through sequencing projects is generally assumed to be a simple intersection of genomic coordinates with genomic features. However, complexities arise for several reasons, including the differential effects of a variant on alternatively spliced transcripts, as well as the difficulty in assessing the impact of small insertions/deletions and large structural variants. Taking these factors into consideration, we developed the Variant Annotation Tool (VAT) to functionally annotate variants from multiple personal genomes at the transcript level as well as obtain summary statistics across genes and individuals. VAT also allows visualization of the effects of different variants, integrates allele frequencies and genotype data from the underlying individuals and facilitates comparative analysis between different groups of individuals. VAT can either be run through a command-line interface or as a web application. Finally, in order to enable on-demand access and to minimize unnecessary transfers of large data files, VAT can be run as a virtual machine in a cloud-computing environment. Availability and Implementation: VAT is implemented in C and PHP. The VAT web service, Amazon Machine Image, source code and detailed documentation are available at vat.gersteinlab.org. Contact: lukas.habegger@yale.edu or mark.gerstein@yale.edu Supplementary Information: Supplementary data are available at Bioinformatics online. PMID:22743228

GDR (Genome Database for Rosaceae): integrated web-database for Rosaceae genomics and genetics data

PubMed Central

Jung, Sook; Staton, Margaret; Lee, Taein; Blenda, Anna; Svancara, Randall; Abbott, Albert; Main, Dorrie

2008-01-01

The Genome Database for Rosaceae (GDR) is a central repository of curated and integrated genetics and genomics data of Rosaceae, an economically important family which includes apple, cherry, peach, pear, raspberry, rose and strawberry. GDR contains annotated databases of all publicly available Rosaceae ESTs, the genetically anchored peach physical map, Rosaceae genetic maps and comprehensively annotated markers and traits. The ESTs are assembled to produce unigene sets of each genus and the entire Rosaceae. Other annotations include putative function, microsatellites, open reading frames, single nucleotide polymorphisms, gene ontology terms and anchored map position where applicable. Most of the published Rosaceae genetic maps can be viewed and compared through CMap, the comparative map viewer. The peach physical map can be viewed using WebFPC/WebChrom, and also through our integrated GDR map viewer, which serves as a portal to the combined genetic, transcriptome and physical mapping information. ESTs, BACs, markers and traits can be queried by various categories and the search result sites are linked to the mapping visualization tools. GDR also provides online analysis tools such as a batch BLAST/FASTA server for the GDR datasets, a sequence assembly server and microsatellite and primer detection tools. GDR is available at http://www.rosaceae.org. PMID:17932055

A brief introduction to web-based genome browsers.

PubMed

Wang, Jun; Kong, Lei; Gao, Ge; Luo, Jingchu

2013-03-01

Genome browser provides a graphical interface for users to browse, search, retrieve and analyze genomic sequence and annotation data. Web-based genome browsers can be classified into general genome browsers with multiple species and species-specific genome browsers. In this review, we attempt to give an overview for the main functions and features of web-based genome browsers, covering data visualization, retrieval, analysis and customization. To give a brief introduction to the multiple-species genome browser, we describe the user interface and main functions of the Ensembl and UCSC genome browsers using the human alpha-globin gene cluster as an example. We further use the MSU and the Rice-Map genome browsers to show some special features of species-specific genome browser, taking a rice transcription factor gene OsSPL14 as an example.

GUIDEseq: a bioconductor package to analyze GUIDE-Seq datasets for CRISPR-Cas nucleases.

PubMed

Zhu, Lihua Julie; Lawrence, Michael; Gupta, Ankit; Pagès, Hervé; Kucukural, Alper; Garber, Manuel; Wolfe, Scot A

2017-05-15

Genome editing technologies developed around the CRISPR-Cas9 nuclease system have facilitated the investigation of a broad range of biological questions. These nucleases also hold tremendous promise for treating a variety of genetic disorders. In the context of their therapeutic application, it is important to identify the spectrum of genomic sequences that are cleaved by a candidate nuclease when programmed with a particular guide RNA, as well as the cleavage efficiency of these sites. Powerful new experimental approaches, such as GUIDE-seq, facilitate the sensitive, unbiased genome-wide detection of nuclease cleavage sites within the genome. Flexible bioinformatics analysis tools for processing GUIDE-seq data are needed. Here, we describe an open source, open development software suite, GUIDEseq, for GUIDE-seq data analysis and annotation as a Bioconductor package in R. The GUIDEseq package provides a flexible platform with more than 60 adjustable parameters for the analysis of datasets associated with custom nuclease applications. These parameters allow data analysis to be tailored to different nuclease platforms with different length and complexity in their guide and PAM recognition sequences or their DNA cleavage position. They also enable users to customize sequence aggregation criteria, and vary peak calling thresholds that can influence the number of potential off-target sites recovered. GUIDEseq also annotates potential off-target sites that overlap with genes based on genome annotation information, as these may be the most important off-target sites for further characterization. In addition, GUIDEseq enables the comparison and visualization of off-target site overlap between different datasets for a rapid comparison of different nuclease configurations or experimental conditions. For each identified off-target, the GUIDEseq package outputs mapped GUIDE-Seq read count as well as cleavage score from a user specified off-target cleavage score prediction algorithm permitting the identification of genomic sequences with unexpected cleavage activity. The GUIDEseq package enables analysis of GUIDE-data from various nuclease platforms for any species with a defined genomic sequence. This software package has been used successfully to analyze several GUIDE-seq datasets. The software, source code and documentation are freely available at http://www.bioconductor.org/packages/release/bioc/html/GUIDEseq.html .

Visualizing the global secondary structure of a viral RNA genome with cryo-electron microscopy

PubMed Central

Garmann, Rees F.; Gopal, Ajaykumar; Athavale, Shreyas S.; Knobler, Charles M.; Gelbart, William M.; Harvey, Stephen C.

2015-01-01

The lifecycle, and therefore the virulence, of single-stranded (ss)-RNA viruses is regulated not only by their particular protein gene products, but also by the secondary and tertiary structure of their genomes. The secondary structure of the entire genomic RNA of satellite tobacco mosaic virus (STMV) was recently determined by selective 2′-hydroxyl acylation analyzed by primer extension (SHAPE). The SHAPE analysis suggested a single highly extended secondary structure with much less branching than occurs in the ensemble of structures predicted by purely thermodynamic algorithms. Here we examine the solution-equilibrated STMV genome by direct visualization with cryo-electron microscopy (cryo-EM), using an RNA of similar length transcribed from the yeast genome as a control. The cryo-EM data reveal an ensemble of branching patterns that are collectively consistent with the SHAPE-derived secondary structure model. Thus, our results both elucidate the statistical nature of the secondary structure of large ss-RNAs and give visual support for modern RNA structure determination methods. Additionally, this work introduces cryo-EM as a means to distinguish between competing secondary structure models if the models differ significantly in terms of the number and/or length of branches. Furthermore, with the latest advances in cryo-EM technology, we suggest the possibility of developing methods that incorporate restraints from cryo-EM into the next generation of algorithms for the determination of RNA secondary and tertiary structures. PMID:25752599

Aligning the unalignable: bacteriophage whole genome alignments.

PubMed

Bérard, Sèverine; Chateau, Annie; Pompidor, Nicolas; Guertin, Paul; Bergeron, Anne; Swenson, Krister M

2016-01-13

In recent years, many studies focused on the description and comparison of large sets of related bacteriophage genomes. Due to the peculiar mosaic structure of these genomes, few informative approaches for comparing whole genomes exist: dot plots diagrams give a mostly qualitative assessment of the similarity/dissimilarity between two or more genomes, and clustering techniques are used to classify genomes. Multiple alignments are conspicuously absent from this scene. Indeed, whole genome aligners interpret lack of similarity between sequences as an indication of rearrangements, insertions, or losses. This behavior makes them ill-prepared to align bacteriophage genomes, where even closely related strains can accomplish the same biological function with highly dissimilar sequences. In this paper, we propose a multiple alignment strategy that exploits functional collinearity shared by related strains of bacteriophages, and uses partial orders to capture mosaicism of sets of genomes. As classical alignments do, the computed alignments can be used to predict that genes have the same biological function, even in the absence of detectable similarity. The Alpha aligner implements these ideas in visual interactive displays, and is used to compute several examples of alignments of Staphylococcus aureus and Mycobacterium bacteriophages, involving up to 29 genomes. Using these datasets, we prove that Alpha alignments are at least as good as those computed by standard aligners. Comparison with the progressive Mauve aligner - which implements a partial order strategy, but whose alignments are linearized - shows a greatly improved interactive graphic display, while avoiding misalignments. Multiple alignments of whole bacteriophage genomes work, and will become an important conceptual and visual tool in comparative genomics of sets of related strains. A python implementation of Alpha, along with installation instructions for Ubuntu and OSX, is available on bitbucket (https://bitbucket.org/thekswenson/alpha).

Using Interactive Data Visualizations for Exploratory Analysis in Undergraduate Genomics Coursework: Field Study Findings and Guidelines

ERIC Educational Resources Information Center

Mirel, Barbara; Kumar, Anuj; Nong, Paige; Su, Gang; Meng, Fan

2016-01-01

Life scientists increasingly use visual analytics to explore large data sets and generate hypotheses. Undergraduate biology majors should be learning these same methods. Yet visual analytics is one of the most underdeveloped areas of undergraduate biology education. This study sought to determine the feasibility of undergraduate biology majors…

GAC: Gene Associations with Clinical, a web based application

PubMed Central

Zhang, Xinyan; Rupji, Manali; Kowalski, Jeanne

2018-01-01

We present GAC, a shiny R based tool for interactive visualization of clinical associations based on high-dimensional data. The tool provides a web-based suite to perform supervised principal component analysis (SuperPC), an approach that uses both high-dimensional data, such as gene expression, combined with clinical data to infer clinical associations. We extended the approach to address binary outcomes, in addition to continuous and time-to-event data in our package, thereby increasing the use and flexibility of SuperPC.  Additionally, the tool provides an interactive visualization for summarizing results based on a forest plot for both binary and time-to-event data.  In summary, the GAC suite of tools provide a one stop shop for conducting statistical analysis to identify and visualize the association between a clinical outcome of interest and high-dimensional data types, such as genomic data. Our GAC package has been implemented in R and is available via http://shinygispa.winship.emory.edu/GAC/. The developmental repository is available at https://github.com/manalirupji/GAC. PMID:29263780

Visualization of tandem repeat mutagenesis in Bacillus subtilis.

PubMed

Dormeyer, Miriam; Lentes, Sabine; Ballin, Patrick; Wilkens, Markus; Klumpp, Stefan; Kohlheyer, Dietrich; Stannek, Lorena; Grünberger, Alexander; Commichau, Fabian M

2018-03-01

Mutations are crucial for the emergence and evolution of proteins with novel functions, and thus for the diversity of life. Tandem repeats (TRs) are mutational hot spots that are present in the genomes of all organisms. Understanding the molecular mechanism underlying TR mutagenesis at the level of single cells requires the development of mutation reporter systems. Here, we present a mutation reporter system that is suitable to visualize mutagenesis of TRs occurring in single cells of the Gram-positive model bacterium Bacillus subtilis using microfluidic single-cell cultivation. The system allows measuring the elimination of TR units due to growth rate recovery. The cultivation of bacteria carrying the mutation reporter system in microfluidic chambers allowed us for the first time to visualize the emergence of a specific mutation at the level of single cells. The application of the mutation reporter system in combination with microfluidics might be helpful to elucidate the molecular mechanism underlying TR (in)stability in bacteria. Moreover, the mutation reporter system might be useful to assess whether mutations occur in response to nutrient starvation. Copyright © 2018 Elsevier B.V. All rights reserved.

Visualization of Genome Diversity in German Shepherd Dogs.

PubMed

Mortlock, Sally-Anne; Booth, Rachel; Mazrier, Hamutal; Khatkar, Mehar S; Williamson, Peter

2015-01-01

A loss of genetic diversity may lead to increased disease risks in subpopulations of dogs. The canine breed structure has contributed to relatively small effective population size in many breeds and can limit the options for selective breeding strategies to maintain diversity. With the completion of the canine genome sequencing project, and the subsequent reduction in the cost of genotyping on a genomic scale, evaluating diversity in dogs has become much more accurate and accessible. This provides a potential tool for advising dog breeders and developing breeding programs within a breed. A challenge in doing this is to present complex relationship data in a form that can be readily utilized. Here, we demonstrate the use of a pipeline, known as NetView, to visualize the network of relationships in a subpopulation of German Shepherd Dogs.

Visualization of the transmission of direct genomic values for paternal and maternal chromosomes for 15 traits in U.S. Brown Swiss, Holstein, and Jersey cattle

USDA-ARS?s Scientific Manuscript database

Reliable haplotypes are available for 171,420 Brown Swiss, Holstein, and Jersey bulls and cows that received genomic evaluations in April 2012. Differences in least-squares means of direct genomic values (DGV) for paternal and maternal haplotypes of Bos taurus autosome (BTA) 1, 6, 14, and 18 for lif...

Assessing pooled BAC and whole genome shotgun strategies for assembly of complex genomes

PubMed Central

2011-01-01

Background We investigate if pooling BAC clones and sequencing the pools can provide for more accurate assembly of genome sequences than the "whole genome shotgun" (WGS) approach. Furthermore, we quantify this accuracy increase. We compare the pooled BAC and WGS approaches using in silico simulations. Standard measures of assembly quality focus on assembly size and fragmentation, which are desirable for large whole genome assemblies. We propose additional measures enabling easy and visual comparison of assembly quality, such as rearrangements and redundant sequence content, relative to the known target sequence. Results The best assembly quality scores were obtained using 454 coverage of 15× linear and 5× paired (3kb insert size) reads (15L-5P) on Arabidopsis. This regime gave similarly good results on four additional plant genomes of very different GC and repeat contents. BAC pooling improved assembly scores over WGS assembly, coverage and redundancy scores improving the most. Conclusions BAC pooling works better than WGS, however, both require a physical map to order the scaffolds. Pool sizes up to 12Mbp work well, suggesting this pooling density to be effective in medium-scale re-sequencing applications such as targeted sequencing of QTL intervals for candidate gene discovery. Assuming the current Roche/454 Titanium sequencing limitations, a 12 Mbp region could be re-sequenced with a full plate of linear reads and a half plate of paired-end reads, yielding 15L-5P coverage after read pre-processing. Our simulation suggests that massively over-sequencing may not improve accuracy. Our scoring measures can be used generally to evaluate and compare results of simulated genome assemblies. PMID:21496274

Bolbase: a comprehensive genomics database for Brassica oleracea

PubMed Central

2013-01-01

Background Brassica oleracea is a morphologically diverse species in the family Brassicaceae and contains a group of nutrition-rich vegetable crops, including common heading cabbage, cauliflower, broccoli, kohlrabi, kale, Brussels sprouts. This diversity along with its phylogenetic membership in a group of three diploid and three tetraploid species, and the recent availability of genome sequences within Brassica provide an unprecedented opportunity to study intra- and inter-species divergence and evolution in this species and its close relatives. Description We have developed a comprehensive database, Bolbase, which provides access to the B. oleracea genome data and comparative genomics information. The whole genome of B. oleracea is available, including nine fully assembled chromosomes and 1,848 scaffolds, with 45,758 predicted genes, 13,382 transposable elements, and 3,581 non-coding RNAs. Comparative genomics information is available, including syntenic regions among B. oleracea, Brassica rapa and Arabidopsis thaliana, synonymous (Ks) and non-synonymous (Ka) substitution rates between orthologous gene pairs, gene families or clusters, and differences in quantity, category, and distribution of transposable elements on chromosomes. Bolbase provides useful search and data mining tools, including a keyword search, a local BLAST server, and a customized GBrowse tool, which can be used to extract annotations of genome components, identify similar sequences and visualize syntenic regions among species. Users can download all genomic data and explore comparative genomics in a highly visual setting. Conclusions Bolbase is the first resource platform for the B. oleracea genome and for genomic comparisons with its relatives, and thus it will help the research community to better study the function and evolution of Brassica genomes as well as enhance molecular breeding research. This database will be updated regularly with new features, improvements to genome annotation, and new genomic sequences as they become available. Bolbase is freely available at http://ocri-genomics.org/bolbase. PMID:24079801

Enabling the democratization of the genomics revolution with a fully integrated web-based bioinformatics platform.

PubMed

Li, Po-E; Lo, Chien-Chi; Anderson, Joseph J; Davenport, Karen W; Bishop-Lilly, Kimberly A; Xu, Yan; Ahmed, Sanaa; Feng, Shihai; Mokashi, Vishwesh P; Chain, Patrick S G

2017-01-09

Continued advancements in sequencing technologies have fueled the development of new sequencing applications and promise to flood current databases with raw data. A number of factors prevent the seamless and easy use of these data, including the breadth of project goals, the wide array of tools that individually perform fractions of any given analysis, the large number of associated software/hardware dependencies, and the detailed expertise required to perform these analyses. To address these issues, we have developed an intuitive web-based environment with a wide assortment of integrated and cutting-edge bioinformatics tools in pre-configured workflows. These workflows, coupled with the ease of use of the environment, provide even novice next-generation sequencing users with the ability to perform many complex analyses with only a few mouse clicks and, within the context of the same environment, to visualize and further interrogate their results. This bioinformatics platform is an initial attempt at Empowering the Development of Genomics Expertise (EDGE) in a wide range of applications for microbial research. © The Author(s) 2016. Published by Oxford University Press on behalf of Nucleic Acids Research.

SNPitty: An Intuitive Web Application for Interactive B-Allele Frequency and Copy Number Visualization of Next-Generation Sequencing Data.

PubMed

van Riet, Job; Krol, Niels M G; Atmodimedjo, Peggy N; Brosens, Erwin; van IJcken, Wilfred F J; Jansen, Maurice P H M; Martens, John W M; Looijenga, Leendert H; Jenster, Guido; Dubbink, Hendrikus J; Dinjens, Winand N M; van de Werken, Harmen J G

2018-03-01

Exploration and visualization of next-generation sequencing data are crucial for clinical diagnostics. Software allowing simultaneous visualization of multiple regions of interest coupled with dynamic heuristic filtering of genetic aberrations is, however, lacking. Therefore, the authors developed the web application SNPitty that allows interactive visualization and interrogation of variant call format files by using B-allele frequencies of single-nucleotide polymorphisms and single-nucleotide variants, coverage metrics, and copy numbers analysis results. SNPitty displays variant alleles and allelic imbalances with a focus on loss of heterozygosity and copy number variation using genome-wide heterozygous markers and somatic mutations. In addition, SNPitty is capable of generating predefined reports that summarize and highlight disease-specific targets of interest. SNPitty was validated for diagnostic interpretation of somatic events by showcasing a serial dilution series of glioma tissue. Additionally, SNPitty is demonstrated in four cancer-related scenarios encountered in daily clinical practice and on whole-exome sequencing data of peripheral blood from a Down syndrome patient. SNPitty allows detection of loss of heterozygosity, chromosomal and gene amplifications, homozygous or heterozygous deletions, somatic mutations, or any combination thereof in regions or genes of interest. Furthermore, SNPitty can be used to distinguish molecular relationships between multiple tumors from a single patient. On the basis of these data, the authors demonstrate that SNPitty is robust and user friendly in a wide range of diagnostic scenarios. Copyright © 2018 American Society for Investigative Pathology and the Association for Molecular Pathology. Published by Elsevier Inc. All rights reserved.

A web server for mining Comparative Genomic Hybridization (CGH) data

NASA Astrophysics Data System (ADS)

Liu, Jun; Ranka, Sanjay; Kahveci, Tamer

2007-11-01

Advances in cytogenetics and molecular biology has established that chromosomal alterations are critical in the pathogenesis of human cancer. Recurrent chromosomal alterations provide cytological and molecular markers for the diagnosis and prognosis of disease. They also facilitate the identification of genes that are important in carcinogenesis, which in the future may help in the development of targeted therapy. A large amount of publicly available cancer genetic data is now available and it is growing. There is a need for public domain tools that allow users to analyze their data and visualize the results. This chapter describes a web based software tool that will allow researchers to analyze and visualize Comparative Genomic Hybridization (CGH) datasets. It employs novel data mining methodologies for clustering and classification of CGH datasets as well as algorithms for identifying important markers (small set of genomic intervals with aberrations) that are potentially cancer signatures. The developed software will help in understanding the relationships between genomic aberrations and cancer types.

UCbase 2.0: ultraconserved sequences database (2014 update).

PubMed

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.

CHESS (CgHExpreSS): a comprehensive analysis tool for the analysis of genomic alterations and their effects on the expression profile of the genome.

PubMed

Lee, Mikyung; Kim, Yangseok

2009-12-16

Genomic alterations frequently occur in many cancer patients and play important mechanistic roles in the pathogenesis of cancer. Furthermore, they can modify the expression level of genes due to altered copy number in the corresponding region of the chromosome. An accumulating body of evidence supports the possibility that strong genome-wide correlation exists between DNA content and gene expression. Therefore, more comprehensive analysis is needed to quantify the relationship between genomic alteration and gene expression. A well-designed bioinformatics tool is essential to perform this kind of integrative analysis. A few programs have already been introduced for integrative analysis. However, there are many limitations in their performance of comprehensive integrated analysis using published software because of limitations in implemented algorithms and visualization modules. To address this issue, we have implemented the Java-based program CHESS to allow integrative analysis of two experimental data sets: genomic alteration and genome-wide expression profile. CHESS is composed of a genomic alteration analysis module and an integrative analysis module. The genomic alteration analysis module detects genomic alteration by applying a threshold based method or SW-ARRAY algorithm and investigates whether the detected alteration is phenotype specific or not. On the other hand, the integrative analysis module measures the genomic alteration's influence on gene expression. It is divided into two separate parts. The first part calculates overall correlation between comparative genomic hybridization ratio and gene expression level by applying following three statistical methods: simple linear regression, Spearman rank correlation and Pearson's correlation. In the second part, CHESS detects the genes that are differentially expressed according to the genomic alteration pattern with three alternative statistical approaches: Student's t-test, Fisher's exact test and Chi square test. By successive operations of two modules, users can clarify how gene expression levels are affected by the phenotype specific genomic alterations. As CHESS was developed in both Java application and web environments, it can be run on a web browser or a local machine. It also supports all experimental platforms if a properly formatted text file is provided to include the chromosomal position of probes and their gene identifiers. CHESS is a user-friendly tool for investigating disease specific genomic alterations and quantitative relationships between those genomic alterations and genome-wide gene expression profiling.

NemaPath: online exploration of KEGG-based metabolic pathways for nematodes

PubMed Central

Wylie, Todd; Martin, John; Abubucker, Sahar; Yin, Yong; Messina, David; Wang, Zhengyuan; McCarter, James P; Mitreva, Makedonka

2008-01-01

Background Nematode.net is a web-accessible resource for investigating gene sequences from parasitic and free-living nematode genomes. Beyond the well-characterized model nematode C. elegans, over 500,000 expressed sequence tags (ESTs) and nearly 600,000 genome survey sequences (GSSs) have been generated from 36 nematode species as part of the Parasitic Nematode Genomics Program undertaken by the Genome Center at Washington University School of Medicine. However, these sequencing data are not present in most publicly available protein databases, which only include sequences in Swiss-Prot. Swiss-Prot, in turn, relies on GenBank/Embl/DDJP for predicted proteins from complete genomes or full-length proteins. Description Here we present the NemaPath pathway server, a web-based pathway-level visualization tool for navigating putative metabolic pathways for over 30 nematode species, including 27 parasites. The NemaPath approach consists of two parts: 1) a backend tool to align and evaluate nematode genomic sequences (curated EST contigs) against the annotated Kyoto Encyclopedia of Genes and Genomes (KEGG) protein database; 2) a web viewing application that displays annotated KEGG pathway maps based on desired confidence levels of primary sequence similarity as defined by a user. NemaPath also provides cross-referenced access to nematode genome information provided by other tools available on Nematode.net, including: detailed NemaGene EST cluster information; putative translations; GBrowse EST cluster views; links from nematode data to external databases for corresponding synonymous C. elegans counterparts, subject matches in KEGG's gene database, and also KEGG Ontology (KO) identification. Conclusion The NemaPath server hosts metabolic pathway mappings for 30 nematode species and is available on the World Wide Web at . The nematode source sequences used for the metabolic pathway mappings are available via FTP , as provided by the Genome Center at Washington University School of Medicine. PMID:18983679

ENGINES: exploring single nucleotide variation in entire human genomes.

PubMed

Amigo, Jorge; Salas, Antonio; Phillips, Christopher

2011-04-19

Next generation ultra-sequencing technologies are starting to produce extensive quantities of data from entire human genome or exome sequences, and therefore new software is needed to present and analyse this vast amount of information. The 1000 Genomes project has recently released raw data for 629 complete genomes representing several human populations through their Phase I interim analysis and, although there are certain public tools available that allow exploration of these genomes, to date there is no tool that permits comprehensive population analysis of the variation catalogued by such data. We have developed a genetic variant site explorer able to retrieve data for Single Nucleotide Variation (SNVs), population by population, from entire genomes without compromising future scalability and agility. ENGINES (ENtire Genome INterface for Exploring SNVs) uses data from the 1000 Genomes Phase I to demonstrate its capacity to handle large amounts of genetic variation (>7.3 billion genotypes and 28 million SNVs), as well as deriving summary statistics of interest for medical and population genetics applications. The whole dataset is pre-processed and summarized into a data mart accessible through a web interface. The query system allows the combination and comparison of each available population sample, while searching by rs-number list, chromosome region, or genes of interest. Frequency and FST filters are available to further refine queries, while results can be visually compared with other large-scale Single Nucleotide Polymorphism (SNP) repositories such as HapMap or Perlegen. ENGINES is capable of accessing large-scale variation data repositories in a fast and comprehensive manner. It allows quick browsing of whole genome variation, while providing statistical information for each variant site such as allele frequency, heterozygosity or FST values for genetic differentiation. Access to the data mart generating scripts and to the web interface is granted from http://spsmart.cesga.es/engines.php. © 2011 Amigo et al; licensee BioMed Central Ltd.

Grohar: Automated Visualization of Genome-Scale Metabolic Models and Their Pathways.

PubMed

Moškon, Miha; Zimic, Nikolaj; Mraz, Miha

2018-05-01

Genome-scale metabolic models (GEMs) have become a powerful tool for the investigation of the entire metabolism of the organism in silico. These models are, however, often extremely hard to reconstruct and also difficult to apply to the selected problem. Visualization of the GEM allows us to easier comprehend the model, to perform its graphical analysis, to find and correct the faulty relations, to identify the parts of the system with a designated function, etc. Even though several approaches for the automatic visualization of GEMs have been proposed, metabolic maps are still manually drawn or at least require large amount of manual curation. We present Grohar, a computational tool for automatic identification and visualization of GEM (sub)networks and their metabolic fluxes. These (sub)networks can be specified directly by listing the metabolites of interest or indirectly by providing reference metabolic pathways from different sources, such as KEGG, SBML, or Matlab file. These pathways are identified within the GEM using three different pathway alignment algorithms. Grohar also supports the visualization of the model adjustments (e.g., activation or inhibition of metabolic reactions) after perturbations are induced.

TheCellMap.org: A Web-Accessible Database for Visualizing and Mining the Global Yeast Genetic Interaction Network

PubMed Central

Usaj, Matej; Tan, Yizhao; Wang, Wen; VanderSluis, Benjamin; Zou, Albert; Myers, Chad L.; Costanzo, Michael; Andrews, Brenda; Boone, Charles

2017-01-01

Providing access to quantitative genomic data is key to ensure large-scale data validation and promote new discoveries. TheCellMap.org serves as a central repository for storing and analyzing quantitative genetic interaction data produced by genome-scale Synthetic Genetic Array (SGA) experiments with the budding yeast Saccharomyces cerevisiae. In particular, TheCellMap.org allows users to easily access, visualize, explore, and functionally annotate genetic interactions, or to extract and reorganize subnetworks, using data-driven network layouts in an intuitive and interactive manner. PMID:28325812

TheCellMap.org: A Web-Accessible Database for Visualizing and Mining the Global Yeast Genetic Interaction Network.

PubMed

Usaj, Matej; Tan, Yizhao; Wang, Wen; VanderSluis, Benjamin; Zou, Albert; Myers, Chad L; Costanzo, Michael; Andrews, Brenda; Boone, Charles

2017-05-05

Providing access to quantitative genomic data is key to ensure large-scale data validation and promote new discoveries. TheCellMap.org serves as a central repository for storing and analyzing quantitative genetic interaction data produced by genome-scale Synthetic Genetic Array (SGA) experiments with the budding yeast Saccharomyces cerevisiae In particular, TheCellMap.org allows users to easily access, visualize, explore, and functionally annotate genetic interactions, or to extract and reorganize subnetworks, using data-driven network layouts in an intuitive and interactive manner. Copyright © 2017 Usaj et al.

E-RNAi: a web application for the multi-species design of RNAi reagents—2010 update

PubMed Central

Horn, Thomas; Boutros, Michael

2010-01-01

The design of RNA interference (RNAi) reagents is an essential step for performing loss-of-function studies in many experimental systems. The availability of sequenced and annotated genomes greatly facilitates RNAi experiments in an increasing number of organisms that were previously not genetically tractable. The E-RNAi web-service, accessible at http://www.e-rnai.org/, provides a computational resource for the optimized design and evaluation of RNAi reagents. The 2010 update of E-RNAi now covers 12 genomes, including Drosophila, Caenorhabditis elegans, human, emerging model organisms such as Schmidtea mediterranea and Acyrthosiphon pisum, as well as the medically relevant vectors Anopheles gambiae and Aedes aegypti. The web service calculates RNAi reagents based on the input of target sequences, sequence identifiers or by visual selection of target regions through a genome browser interface. It identifies optimized RNAi target-sites by ranking sequences according to their predicted specificity, efficiency and complexity. E-RNAi also facilitates the design of secondary RNAi reagents for validation experiments, evaluation of pooled siRNA reagents and batch design. Results are presented online, as a downloadable HTML report and as tab-delimited files. PMID:20444868

Genome editing: the breakthrough technology for inherited retinal disease?

PubMed

Smith, Andrew J; Carter, Stephen P; Kennedy, Breandán N

2017-10-01

Genetic alterations resulting in a dysfunctional retinal pigment epithelium and/or degenerating photoreceptors cause impaired vision. These juxtaposed cells in the retina of the posterior eye are crucial for the visual cycle or phototransduction. Deficits in these biochemical processes perturb neural processing of images capturing the external environment. Notably, there is a distinct lack of clinically approved pharmacological, cell- or gene-based therapies for inherited retinal disease. Gene editing technologies are rapidly advancing as a realistic therapeutic option. Areas covered: Recent discovery of endonuclease-mediated gene editing technologies has culminated in a surge of investigations into their therapeutic potential. In this review, the authors discuss gene editing technologies and their applicability in treating inherited retinal diseases, the limitations of the technology and the research obstacles to overcome before editing a patient's genome becomes a viable treatment option. Expert opinion: The ability to strategically edit a patient's genome constitutes a treatment revolution. However, concerns remain over the safety and efficacy of either transplanting iPSC-derived retinal cells following ex vivo gene editing, or with direct gene editing in vivo. Ultimately, further refinements to improve efficacy and safety profiles are paramount for gene editing to emerge as a widely available treatment option.

Genomics Analogy Model for Educators (GAME): VELCRO® Analogy Model to Enable the Learning of DNA Arrays for Visually Impaired and Blind Students

ERIC Educational Resources Information Center

Bello, Julia; Butler, Charles; Radavich, Rosanne; York, Alan; Oseto, Christian; Orvis, Kathryn; Pittendrigh, Barry R.

2007-01-01

Although members of the general public have often heard of the terms "genetic engineering" and, more recently, genomics, they typically have little to no knowledge about these topics, and in some cases are confused about basic concepts in these areas. There is currently a need for teaching models to explain concepts behind genomics.…

Genome image programs: visualization and interpretation of Escherichia coli microarray experiments.

PubMed

Zimmer, Daniel P; Paliy, Oleg; Thomas, Brian; Gyaneshwar, Prasad; Kustu, Sydney

2004-08-01

We have developed programs to facilitate analysis of microarray data in Escherichia coli. They fall into two categories: manipulation of microarray images and identification of known biological relationships among lists of genes. A program in the first category arranges spots from glass-slide DNA microarrays according to their position in the E. coli genome and displays them compactly in genome order. The resulting genome image is presented in a web browser with an image map that allows the user to identify genes in the reordered image. Another program in the first category aligns genome images from two or more experiments. These images assist in visualizing regions of the genome with common transcriptional control. Such regions include multigene operons and clusters of operons, which are easily identified as strings of adjacent, similarly colored spots. The images are also useful for assessing the overall quality of experiments. The second category of programs includes a database and a number of tools for displaying biological information about many E. coli genes simultaneously rather than one gene at a time, which facilitates identifying relationships among them. These programs have accelerated and enhanced our interpretation of results from E. coli DNA microarray experiments. Examples are given. Copyright 2004 Genetics Society of America

B-CAN: a resource sharing platform to improve the operation, visualization and integrated analysis of TCGA breast cancer data

PubMed Central

Wen, Can-Hong; Ou, Shao-Min; Guo, Xiao-Bo; Liu, Chen-Feng; Shen, Yan-Bo; You, Na; Cai, Wei-Hong; Shen, Wen-Jun; Wang, Xue-Qin; Tan, Hai-Zhu

2017-01-01

Breast cancer is a high-risk heterogeneous disease with myriad subtypes and complicated biological features. The Cancer Genome Atlas (TCGA) breast cancer database provides researchers with the large-scale genome and clinical data via web portals and FTP services. Researchers are able to gain new insights into their related fields, and evaluate experimental discoveries with TCGA. However, it is difficult for researchers who have little experience with database and bioinformatics to access and operate on because of TCGA’s complex data format and diverse files. For ease of use, we build the breast cancer (B-CAN) platform, which enables data customization, data visualization, and private data center. The B-CAN platform runs on Apache server and interacts with the backstage of MySQL database by PHP. Users can customize data based on their needs by combining tables from original TCGA database and selecting variables from each table. The private data center is applicable for private data and two types of customized data. A key feature of the B-CAN is that it provides single table display and multiple table display. Customized data with one barcode corresponding to many records and processed customized data are allowed in Multiple Tables Display. The B-CAN is an intuitive and high-efficient data-sharing platform. PMID:29312567

Variant Review with the Integrative Genomics Viewer.

PubMed

Robinson, James T; Thorvaldsdóttir, Helga; Wenger, Aaron M; Zehir, Ahmet; Mesirov, Jill P

2017-11-01

Manual review of aligned reads for confirmation and interpretation of variant calls is an important step in many variant calling pipelines for next-generation sequencing (NGS) data. Visual inspection can greatly increase the confidence in calls, reduce the risk of false positives, and help characterize complex events. The Integrative Genomics Viewer (IGV) was one of the first tools to provide NGS data visualization, and it currently provides a rich set of tools for inspection, validation, and interpretation of NGS datasets, as well as other types of genomic data. Here, we present a short overview of IGV's variant review features for both single-nucleotide variants and structural variants, with examples from both cancer and germline datasets. IGV is freely available at https://www.igv.org Cancer Res; 77(21); e31-34. ©2017 AACR . ©2017 American Association for Cancer Research.

CHiCP: a web-based tool for the integrative and interactive visualization of promoter capture Hi-C datasets.

PubMed

Schofield, E C; Carver, T; Achuthan, P; Freire-Pritchett, P; Spivakov, M; Todd, J A; Burren, O S

2016-08-15

Promoter capture Hi-C (PCHi-C) allows the genome-wide interrogation of physical interactions between distal DNA regulatory elements and gene promoters in multiple tissue contexts. Visual integration of the resultant chromosome interaction maps with other sources of genomic annotations can provide insight into underlying regulatory mechanisms. We have developed Capture HiC Plotter (CHiCP), a web-based tool that allows interactive exploration of PCHi-C interaction maps and integration with both public and user-defined genomic datasets. CHiCP is freely accessible from www.chicp.org and supports most major HTML5 compliant web browsers. Full source code and installation instructions are available from http://github.com/D-I-L/django-chicp ob219@cam.ac.uk. © The Author 2016. Published by Oxford University Press. All rights reserved.

Development and Application of Loop-Mediated Isothermal Amplification Assays for Rapid Visual Detection of cry2Ab and cry3A Genes in Genetically-Modified Crops

PubMed Central

Li, Feiwu; Yan, Wei; Long, Likun; Qi, Xing; Li, Congcong; Zhang, Shihong

2014-01-01

The cry2Ab and cry3A genes are two of the most important insect-resistant exogenous genes and had been widely used in genetically-modified crops. To develop more effective alternatives for the quick identification of genetically-modified organisms (GMOs) containing these genes, a rapid and visual loop-mediated isothermal amplification (LAMP) method to detect the cry2Ab and cry3A genes is described in this study. The LAMP assay can be finished within 60 min at an isothermal condition of 63 °C. The derived LAMP products can be obtained by a real-time turbidimeter via monitoring the white turbidity or directly observed by the naked eye through adding SYBR Green I dye. The specificity of the LAMP assay was determined by analyzing thirteen insect-resistant genetically-modified (GM) crop events with different Bt genes. Furthermore, the sensitivity of the LAMP assay was evaluated by diluting the template genomic DNA. Results showed that the limit of detection of the established LAMP assays was approximately five copies of haploid genomic DNA, about five-fold greater than that of conventional PCR assays. All of the results indicated that this established rapid and visual LAMP assay was quick, accurate and cost effective, with high specificity and sensitivity. In addition, this method does not need specific expensive instruments or facilities, which can provide a simpler and quicker approach to detecting the cry2Ab and cry3A genes in GM crops, especially for on-site, large-scale test purposes in the field. PMID:25167136

Development and application of loop-mediated isothermal amplification assays for rapid visual detection of cry2Ab and cry3A genes in genetically-modified crops.

PubMed

Li, Feiwu; Yan, Wei; Long, Likun; Qi, Xing; Li, Congcong; Zhang, Shihong

2014-08-27

The cry2Ab and cry3A genes are two of the most important insect-resistant exogenous genes and had been widely used in genetically-modified crops. To develop more effective alternatives for the quick identification of genetically-modified organisms (GMOs) containing these genes, a rapid and visual loop-mediated isothermal amplification (LAMP) method to detect the cry2Ab and cry3A genes is described in this study. The LAMP assay can be finished within 60 min at an isothermal condition of 63 °C. The derived LAMP products can be obtained by a real-time turbidimeter via monitoring the white turbidity or directly observed by the naked eye through adding SYBR Green I dye. The specificity of the LAMP assay was determined by analyzing thirteen insect-resistant genetically-modified (GM) crop events with different Bt genes. Furthermore, the sensitivity of the LAMP assay was evaluated by diluting the template genomic DNA. Results showed that the limit of detection of the established LAMP assays was approximately five copies of haploid genomic DNA, about five-fold greater than that of conventional PCR assays. All of the results indicated that this established rapid and visual LAMP assay was quick, accurate and cost effective, with high specificity and sensitivity. In addition, this method does not need specific expensive instruments or facilities, which can provide a simpler and quicker approach to detecting the cry2Ab and cry3A genes in GM crops, especially for on-site, large-scale test purposes in the field.

ExpressionDB: An open source platform for distributing genome-scale datasets.

PubMed

Hughes, Laura D; Lewis, Scott A; Hughes, Michael E

2017-01-01

RNA-sequencing (RNA-seq) and microarrays are methods for measuring gene expression across the entire transcriptome. Recent advances have made these techniques practical and affordable for essentially any laboratory with experience in molecular biology. A variety of computational methods have been developed to decrease the amount of bioinformatics expertise necessary to analyze these data. Nevertheless, many barriers persist which discourage new labs from using functional genomics approaches. Since high-quality gene expression studies have enduring value as resources to the entire research community, it is of particular importance that small labs have the capacity to share their analyzed datasets with the research community. Here we introduce ExpressionDB, an open source platform for visualizing RNA-seq and microarray data accommodating virtually any number of different samples. ExpressionDB is based on Shiny, a customizable web application which allows data sharing locally and online with customizable code written in R. ExpressionDB allows intuitive searches based on gene symbols, descriptions, or gene ontology terms, and it includes tools for dynamically filtering results based on expression level, fold change, and false-discovery rates. Built-in visualization tools include heatmaps, volcano plots, and principal component analysis, ensuring streamlined and consistent visualization to all users. All of the scripts for building an ExpressionDB with user-supplied data are freely available on GitHub, and the Creative Commons license allows fully open customization by end-users. We estimate that a demo database can be created in under one hour with minimal programming experience, and that a new database with user-supplied expression data can be completed and online in less than one day.

Live-cell CRISPR imaging in plants reveals dynamic telomere movements.

PubMed

Dreissig, Steven; Schiml, Simon; Schindele, Patrick; Weiss, Oda; Rutten, Twan; Schubert, Veit; Gladilin, Evgeny; Mette, Michael F; Puchta, Holger; Houben, Andreas

2017-08-01

Elucidating the spatiotemporal organization of the genome inside the nucleus is imperative to our understanding of the regulation of genes and non-coding sequences during development and environmental changes. Emerging techniques of chromatin imaging promise to bridge the long-standing gap between sequencing studies, which reveal genomic information, and imaging studies that provide spatial and temporal information of defined genomic regions. Here, we demonstrate such an imaging technique based on two orthologues of the bacterial clustered regularly interspaced short palindromic repeats (CRISPR)-CRISPR associated protein 9 (Cas9). By fusing eGFP/mRuby2 to catalytically inactive versions of Streptococcus pyogenes and Staphylococcus aureus Cas9, we show robust visualization of telomere repeats in live leaf cells of Nicotiana benthamiana. By tracking the dynamics of telomeres visualized by CRISPR-dCas9, we reveal dynamic telomere movements of up to 2 μm over 30 min during interphase. Furthermore, we show that CRISPR-dCas9 can be combined with fluorescence-labelled proteins to visualize DNA-protein interactions in vivo. By simultaneously using two dCas9 orthologues, we pave the way for the imaging of multiple genomic loci in live plants cells. CRISPR imaging bears the potential to significantly improve our understanding of the dynamics of chromosomes in live plant cells. © 2017 The Authors The Plant Journal published by John Wiley & Sons Ltd and Society for Experimental Biology.

Ensembl 2004.

PubMed

Birney, E; Andrews, D; Bevan, P; Caccamo, M; Cameron, G; Chen, Y; Clarke, L; Coates, G; Cox, T; Cuff, J; Curwen, V; Cutts, T; Down, T; Durbin, R; Eyras, E; Fernandez-Suarez, X M; Gane, P; Gibbins, B; Gilbert, J; Hammond, M; Hotz, H; Iyer, V; Kahari, A; Jekosch, K; Kasprzyk, A; Keefe, D; Keenan, S; Lehvaslaiho, H; McVicker, G; Melsopp, C; Meidl, P; Mongin, E; Pettett, R; Potter, S; Proctor, G; Rae, M; Searle, S; Slater, G; Smedley, D; Smith, J; Spooner, W; Stabenau, A; Stalker, J; Storey, R; Ureta-Vidal, A; Woodwark, C; Clamp, M; Hubbard, T

2004-01-01

The Ensembl (http://www.ensembl.org/) database project provides a bioinformatics framework to organize biology around the sequences of large genomes. It is a comprehensive and integrated source of annotation of large genome sequences, available via interactive website, web services or flat files. As well as being one of the leading sources of genome annotation, Ensembl is an open source software engineering project to develop a portable system able to handle very large genomes and associated requirements. The facilities of the system range from sequence analysis to data storage and visualization and installations exist around the world both in companies and at academic sites. With a total of nine genome sequences available from Ensembl and more genomes to follow, recent developments have focused mainly on closer integration between genomes and external data.

GenomePeek—an online tool for prokaryotic genome and metagenome analysis

DOE PAGES

McNair, Katelyn; Edwards, Robert A.

2015-06-16

As increases in prokaryotic sequencing take place, a method to quickly and accurately analyze this data is needed. Previous tools are mainly designed for metagenomic analysis and have limitations; such as long runtimes and significant false positive error rates. The online tool GenomePeek (edwards.sdsu.edu/GenomePeek) was developed to analyze both single genome and metagenome sequencing files, quickly and with low error rates. GenomePeek uses a sequence assembly approach where reads to a set of conserved genes are extracted, assembled and then aligned against the highly specific reference database. GenomePeek was found to be faster than traditional approaches while still keeping errormore » rates low, as well as offering unique data visualization options.« less

A Web Geographic Information System to share data and explorative analysis tools: The application to West Nile disease in the Mediterranean basin.

PubMed

Savini, Lara; Tora, Susanna; Di Lorenzo, Alessio; Cioci, Daniela; Monaco, Federica; Polci, Andrea; Orsini, Massimiliano; Calistri, Paolo; Conte, Annamaria

2018-01-01

In the last decades an increasing number of West Nile Disease cases was observed in equines and humans in the Mediterranean basin and surveillance systems are set up in numerous countries to manage and control the disease. The collection, storage and distribution of information on the spread of the disease becomes important for a shared intervention and control strategy. To this end, a Web Geographic Information System has been developed and disease data, climatic and environmental remote sensed data, full genome sequences of selected isolated strains are made available. This paper describes the Disease Monitoring Dashboard (DMD) web system application, the tools available for the preliminary analysis on climatic and environmental factors and the other interactive tools for epidemiological analysis. WNV occurrence data are collected from multiple official and unofficial sources. Whole genome sequences and metadata of WNV strains are retrieved from public databases or generated in the framework of the Italian surveillance activities. Climatic and environmental data are provided by NASA website. The Geographical Information System is composed by Oracle 10g Database and ESRI ArcGIS Server 10.03; the web mapping client application is developed with the ArcGIS API for Javascript and Phylocanvas library to facilitate and optimize the mash-up approach. ESRI ArcSDE 10.1 has been used to store spatial data. The DMD application is accessible through a generic web browser at https://netmed.izs.it/networkMediterraneo/. The system collects data through on-line forms and automated procedures and visualizes data as interactive graphs, maps and tables. The spatial and temporal dynamic visualization of disease events is managed by a time slider that returns results on both map and epidemiological curve. Climatic and environmental data can be associated to cases through python procedures and downloaded as Excel files. The system compiles multiple datasets through user-friendly web tools; it integrates entomological, veterinary and human surveillance, molecular information on pathogens and environmental and climatic data. The principal result of the DMD development is the transfer and dissemination of knowledge and technologies to develop strategies for integrated prevention and control measures of animal and human diseases.

The genomic applications in practice and prevention network.

PubMed

Khoury, Muin J; Feero, W Gregory; Reyes, Michele; Citrin, Toby; Freedman, Andrew; Leonard, Debra; Burke, Wylie; Coates, Ralph; Croyle, Robert T; Edwards, Karen; Kardia, Sharon; McBride, Colleen; Manolio, Teri; Randhawa, Gurvaneet; Rasooly, Rebekah; St Pierre, Jeannette; Terry, Sharon

2009-07-01

The authors describe the rationale and initial development of a new collaborative initiative, the Genomic Applications in Practice and Prevention Network. The network convened by the Centers for Disease Control and Prevention and the National Institutes of Health includes multiple stakeholders from academia, government, health care, public health, industry and consumers. The premise of Genomic Applications in Practice and Prevention Network is that there is an unaddressed chasm between gene discoveries and demonstration of their clinical validity and utility. This chasm is due to the lack of readily accessible information about the utility of most genomic applications and the lack of necessary knowledge by consumers and providers to implement what is known. The mission of Genomic Applications in Practice and Prevention Network is to accelerate and streamline the effective integration of validated genomic knowledge into the practice of medicine and public health, by empowering and sponsoring research, evaluating research findings, and disseminating high quality information on candidate genomic applications in practice and prevention. Genomic Applications in Practice and Prevention Network will develop a process that links ongoing collection of information on candidate genomic applications to four crucial domains: (1) knowledge synthesis and dissemination for new and existing technologies, and the identification of knowledge gaps, (2) a robust evidence-based recommendation development process, (3) translation research to evaluate validity, utility and impact in the real world and how to disseminate and implement recommended genomic applications, and (4) programs to enhance practice, education, and surveillance.

Octopus-toolkit: a workflow to automate mining of public epigenomic and transcriptomic next-generation sequencing data

PubMed Central

Kim, Taemook; Seo, Hogyu David; Hennighausen, Lothar; Lee, Daeyoup

2018-01-01

Abstract Octopus-toolkit is a stand-alone application for retrieving and processing large sets of next-generation sequencing (NGS) data with a single step. Octopus-toolkit is an automated set-up-and-analysis pipeline utilizing the Aspera, SRA Toolkit, FastQC, Trimmomatic, HISAT2, STAR, Samtools, and HOMER applications. All the applications are installed on the user's computer when the program starts. Upon the installation, it can automatically retrieve original files of various epigenomic and transcriptomic data sets, including ChIP-seq, ATAC-seq, DNase-seq, MeDIP-seq, MNase-seq and RNA-seq, from the gene expression omnibus data repository. The downloaded files can then be sequentially processed to generate BAM and BigWig files, which are used for advanced analyses and visualization. Currently, it can process NGS data from popular model genomes such as, human (Homo sapiens), mouse (Mus musculus), dog (Canis lupus familiaris), plant (Arabidopsis thaliana), zebrafish (Danio rerio), fruit fly (Drosophila melanogaster), worm (Caenorhabditis elegans), and budding yeast (Saccharomyces cerevisiae) genomes. With the processed files from Octopus-toolkit, the meta-analysis of various data sets, motif searches for DNA-binding proteins, and the identification of differentially expressed genes and/or protein-binding sites can be easily conducted with few commands by users. Overall, Octopus-toolkit facilitates the systematic and integrative analysis of available epigenomic and transcriptomic NGS big data. PMID:29420797

Genome engineering for microbial natural product discovery.

PubMed

Choi, Si-Sun; Katsuyama, Yohei; Bai, Linquan; Deng, Zixin; Ohnishi, Yasuo; Kim, Eung-Soo

2018-03-03

The discovery and development of microbial natural products (MNPs) have played pivotal roles in the fields of human medicine and its related biotechnology sectors over the past several decades. The post-genomic era has witnessed the development of microbial genome mining approaches to isolate previously unsuspected MNP biosynthetic gene clusters (BGCs) hidden in the genome, followed by various BGC awakening techniques to visualize compound production. Additional microbial genome engineering techniques have allowed higher MNP production titers, which could complement a traditional culture-based MNP chasing approach. Here, we describe recent developments in the MNP research paradigm, including microbial genome mining, NP BGC activation, and NP overproducing cell factory design. Copyright © 2018 Elsevier Ltd. All rights reserved.

A Guide to the PLAZA 3.0 Plant Comparative Genomic Database.

PubMed

Vandepoele, Klaas

2017-01-01

PLAZA 3.0 is an online resource for comparative genomics and offers a versatile platform to study gene functions and gene families or to analyze genome organization and evolution in the green plant lineage. Starting from genome sequence information for over 35 plant species, precomputed comparative genomic data sets cover homologous gene families, multiple sequence alignments, phylogenetic trees, and genomic colinearity information within and between species. Complementary functional data sets, a Workbench, and interactive visualization tools are available through a user-friendly web interface, making PLAZA an excellent starting point to translate sequence or omics data sets into biological knowledge. PLAZA is available at http://bioinformatics.psb.ugent.be/plaza/ .

Applications of CRISPR Genome Engineering in Cell Biology

PubMed Central

Wang, Fangyuan; Qi, Lei S.

2016-01-01

Recent advances in genome engineering are starting a revolution in biological research and translational applications. The CRISPR-associated RNA-guided endonuclease Cas9 and its variants enable diverse manipulations of genome function. In this review, we describe the development of Cas9 tools for a variety of applications in cell biology research, including the study of functional genomics, the creation of transgenic animal models, and genomic imaging. Novel genome engineering methods offer a new avenue to understand the causality between genome and phenotype, thus promising a fuller understanding of cell biology. PMID:27599850

Gnome View: A tool for visual representation of human genome data

DOE Office of Scientific and Technical Information (OSTI.GOV)

Pelkey, J.E.; Thomas, G.S.; Thurman, D.A.

1993-02-01

GnomeView is a tool for exploring data generated by the Human Gemone Project. GnomeView provides both graphical and textural styles of data presentation: employs an intuitive window-based graphical query interface: and integrates its underlying genome databases in such a way that the user can navigate smoothly across databases and between different levels of data. This paper describes GnomeView and discusses how it addresses various genome informatics issues.

An interactive web-based application for Comprehensive Analysis of RNAi-screen Data.

PubMed

Dutta, Bhaskar; Azhir, Alaleh; Merino, Louis-Henri; Guo, Yongjian; Revanur, Swetha; Madhamshettiwar, Piyush B; Germain, Ronald N; Smith, Jennifer A; Simpson, Kaylene J; Martin, Scott E; Buehler, Eugen; Beuhler, Eugen; Fraser, Iain D C

2016-02-23

RNAi screens are widely used in functional genomics. Although the screen data can be susceptible to a number of experimental biases, many of these can be corrected by computational analysis. For this purpose, here we have developed a web-based platform for integrated analysis and visualization of RNAi screen data named CARD (for Comprehensive Analysis of RNAi Data; available at https://card.niaid.nih.gov). CARD allows the user to seamlessly carry out sequential steps in a rigorous data analysis workflow, including normalization, off-target analysis, integration of gene expression data, optimal thresholds for hit selection and network/pathway analysis. To evaluate the utility of CARD, we describe analysis of three genome-scale siRNA screens and demonstrate: (i) a significant increase both in selection of subsequently validated hits and in rejection of false positives, (ii) an increased overlap of hits from independent screens of the same biology and (iii) insight to microRNA (miRNA) activity based on siRNA seed enrichment.

Retinal dystrophies, genomic applications in diagnosis and prospects for therapy

PubMed Central

Nash, Benjamin M.; Wright, Dale C.; Grigg, John R.; Bennetts, Bruce

2015-01-01

Retinal dystrophies (RDs) are degenerative diseases of the retina which have marked clinical and genetic heterogeneity. Common presentations among these disorders include night or colour blindness, tunnel vision and subsequent progression to complete blindness. The known causative disease genes have a variety of developmental and functional roles with mutations in more than 120 genes shown to be responsible for the phenotypes. In addition, mutations within the same gene have been shown to cause different disease phenotypes, even amongst affected individuals within the same family highlighting further levels of complexity. The known disease genes encode proteins involved in retinal cellular structures, phototransduction, the visual cycle, and photoreceptor structure or gene regulation. This review aims to demonstrate the high degree of genetic complexity in both the causative disease genes and their associated phenotypes, highlighting the more common clinical manifestation of retinitis pigmentosa (RP). The review also provides insight to recent advances in genomic molecular diagnosis and gene and cell-based therapies for the RDs. PMID:26835369

In vivo genome editing via CRISPR/Cas9 mediated homology-independent targeted integration

PubMed Central

Suzuki, Keiichiro; Tsunekawa, Yuji; Hernandez-Benitez, Reyna; Wu, Jun; Zhu, Jie; Kim, Euiseok J.; Hatanaka, Fumiyuki; Yamamoto, Mako; Araoka, Toshikazu; Li, Zhe; Kurita, Masakazu; Hishida, Tomoaki; Li, Mo; Aizawa, Emi; Guo, Shicheng; Chen, Song; Goebl, April; Soligalla, Rupa Devi; Qu, Jing; Jiang, Tingshuai; Fu, Xin; Jafari, Maryam; Esteban, Concepcion Rodriguez; Berggren, W. Travis; Lajara, Jeronimo; Nuñez-Delicado, Estrella; Guillen, Pedro; Campistol, Josep M.; Matsuzaki, Fumio; Liu, Guang-Hui; Magistretti, Pierre; Zhang, Kun; Callaway, Edward M.; Zhang, Kang; Belmonte, Juan Carlos Izpisua

2017-01-01

Targeted genome editing via engineered nucleases is an exciting area of biomedical research and holds potential for clinical applications. Despite rapid advances in the field, in vivo targeted transgene integration is still infeasible because current tools are inefficient1, especially for non-dividing cells, which compose most adult tissues. This poses a barrier for uncovering fundamental biological principles and developing treatments for a broad range of genetic disorders2. Based on clustered regularly interspaced short palindromic repeat/Cas9 (CRISPR/Cas9)3,4 technology, here we devise a homology-independent targeted integration (HITI) strategy, which allows for robust DNA knock-in in both dividing and non-dividing cells in vitro and, more importantly, in vivo (for example, in neurons of postnatal mammals). As a proof of concept of its therapeutic potential, we demonstrate the efficacy of HITI in improving visual function using a rat model of the retinal degeneration condition retinitis pigmentosa. The HITI method presented here establishes new avenues for basic research and targeted gene therapies. PMID:27851729

An interactive web-based application for Comprehensive Analysis of RNAi-screen Data

PubMed Central

Dutta, Bhaskar; Azhir, Alaleh; Merino, Louis-Henri; Guo, Yongjian; Revanur, Swetha; Madhamshettiwar, Piyush B.; Germain, Ronald N.; Smith, Jennifer A.; Simpson, Kaylene J.; Martin, Scott E.; Beuhler, Eugen; Fraser, Iain D. C.

2016-01-01

RNAi screens are widely used in functional genomics. Although the screen data can be susceptible to a number of experimental biases, many of these can be corrected by computational analysis. For this purpose, here we have developed a web-based platform for integrated analysis and visualization of RNAi screen data named CARD (for Comprehensive Analysis of RNAi Data; available at https://card.niaid.nih.gov). CARD allows the user to seamlessly carry out sequential steps in a rigorous data analysis workflow, including normalization, off-target analysis, integration of gene expression data, optimal thresholds for hit selection and network/pathway analysis. To evaluate the utility of CARD, we describe analysis of three genome-scale siRNA screens and demonstrate: (i) a significant increase both in selection of subsequently validated hits and in rejection of false positives, (ii) an increased overlap of hits from independent screens of the same biology and (iii) insight to microRNA (miRNA) activity based on siRNA seed enrichment. PMID:26902267

GIANT API: an application programming interface for functional genomics

PubMed Central

Roberts, Andrew M.; Wong, Aaron K.; Fisk, Ian; Troyanskaya, Olga G.

2016-01-01

GIANT API provides biomedical researchers programmatic access to tissue-specific and global networks in humans and model organisms, and associated tools, which includes functional re-prioritization of existing genome-wide association study (GWAS) data. Using tissue-specific interaction networks, researchers are able to predict relationships between genes specific to a tissue or cell lineage, identify the changing roles of genes across tissues and uncover disease-gene associations. Additionally, GIANT API enables computational tools like NetWAS, which leverages tissue-specific networks for re-prioritization of GWAS results. The web services covered by the API include 144 tissue-specific functional gene networks in human, global functional networks for human and six common model organisms and the NetWAS method. GIANT API conforms to the REST architecture, which makes it stateless, cacheable and highly scalable. It can be used by a diverse range of clients including web browsers, command terminals, programming languages and standalone apps for data analysis and visualization. The API is freely available for use at http://giant-api.princeton.edu. PMID:27098035

InCHlib - interactive cluster heatmap for web applications.

PubMed

Skuta, Ctibor; Bartůněk, Petr; Svozil, Daniel

2014-12-01

Hierarchical clustering is an exploratory data analysis method that reveals the groups (clusters) of similar objects. The result of the hierarchical clustering is a tree structure called dendrogram that shows the arrangement of individual clusters. To investigate the row/column hierarchical cluster structure of a data matrix, a visualization tool called 'cluster heatmap' is commonly employed. In the cluster heatmap, the data matrix is displayed as a heatmap, a 2-dimensional array in which the colour of each element corresponds to its value. The rows/columns of the matrix are ordered such that similar rows/columns are near each other. The ordering is given by the dendrogram which is displayed on the side of the heatmap. We developed InCHlib (Interactive Cluster Heatmap Library), a highly interactive and lightweight JavaScript library for cluster heatmap visualization and exploration. InCHlib enables the user to select individual or clustered heatmap rows, to zoom in and out of clusters or to flexibly modify heatmap appearance. The cluster heatmap can be augmented with additional metadata displayed in a different colour scale. In addition, to further enhance the visualization, the cluster heatmap can be interconnected with external data sources or analysis tools. Data clustering and the preparation of the input file for InCHlib is facilitated by the Python utility script inchlib_clust . The cluster heatmap is one of the most popular visualizations of large chemical and biomedical data sets originating, e.g., in high-throughput screening, genomics or transcriptomics experiments. The presented JavaScript library InCHlib is a client-side solution for cluster heatmap exploration. InCHlib can be easily deployed into any modern web application and configured to cooperate with external tools and data sources. Though InCHlib is primarily intended for the analysis of chemical or biological data, it is a versatile tool which application domain is not limited to the life sciences only.

Tumor Touch Imprints as Source for Whole Genome Analysis of Neuroblastoma Tumors

PubMed Central

Brunner, Clemens; Brunner-Herglotz, Bettina; Ziegler, Andrea; Frech, Christian; Amann, Gabriele; Ladenstein, Ruth; Ambros, Inge M.; Ambros, Peter F.

2016-01-01

Introduction Tumor touch imprints (TTIs) are routinely used for the molecular diagnosis of neuroblastomas by interphase fluorescence in-situ hybridization (I-FISH). However, in order to facilitate a comprehensive, up-to-date molecular diagnosis of neuroblastomas and to identify new markers to refine risk and therapy stratification methods, whole genome approaches are needed. We examined the applicability of an ultra-high density SNP array platform that identifies copy number changes of varying sizes down to a few exons for the detection of genomic changes in tumor DNA extracted from TTIs. Material and Methods DNAs were extracted from TTIs of 46 neuroblastoma and 4 other pediatric tumors. The DNAs were analyzed on the Cytoscan HD SNP array platform to evaluate numerical and structural genomic aberrations. The quality of the data obtained from TTIs was compared to that from randomly chosen fresh or fresh frozen solid tumors (n = 212) and I-FISH validation was performed. Results SNP array profiles were obtained from 48 (out of 50) TTI DNAs of which 47 showed genomic aberrations. The high marker density allowed for single gene analysis, e.g. loss of nine exons in the ATRX gene and the visualization of chromothripsis. Data quality was comparable to fresh or fresh frozen tumor SNP profiles. SNP array results were confirmed by I-FISH. Conclusion TTIs are an excellent source for SNP array processing with the advantage of simple handling, distribution and storage of tumor tissue on glass slides. The minimal amount of tumor tissue needed to analyze whole genomes makes TTIs an economic surrogate source in the molecular diagnostic work up of tumor samples. PMID:27560999

Triticeae Resources in Ensembl Plants

PubMed Central

Bolser, Dan M.; Kerhornou, Arnaud; Walts, Brandon; Kersey, Paul

2015-01-01

Recent developments in DNA sequencing have enabled the large and complex genomes of many crop species to be determined for the first time, even those previously intractable due to their polyploid nature. Indeed, over the course of the last 2 years, the genome sequences of several commercially important cereals, notably barley and bread wheat, have become available, as well as those of related wild species. While still incomplete, comparison with other, more completely assembled species suggests that coverage of genic regions is likely to be high. Ensembl Plants (http://plants.ensembl.org) is an integrative resource organizing, analyzing and visualizing genome-scale information for important crop and model plants. Available data include reference genome sequence, variant loci, gene models and functional annotation. For variant loci, individual and population genotypes, linkage information and, where available, phenotypic information are shown. Comparative analyses are performed on DNA and protein sequence alignments. The resulting genome alignments and gene trees, representing the implied evolutionary history of the gene family, are made available for visualization and analysis. Driven by the case of bread wheat, specific extensions to the analysis pipelines and web interface have recently been developed to support polyploid genomes. Data in Ensembl Plants is accessible through a genome browser incorporating various specialist interfaces for different data types, and through a variety of additional methods for programmatic access and data mining. These interfaces are consistent with those offered through the Ensembl interface for the genomes of non-plant species, including those of plant pathogens, pests and pollinators, facilitating the study of the plant in its environment. PMID:25432969

BigQ: a NoSQL based framework to handle genomic variants in i2b2.

PubMed

Gabetta, Matteo; Limongelli, Ivan; Rizzo, Ettore; Riva, Alberto; Segagni, Daniele; Bellazzi, Riccardo

2015-12-29

Precision medicine requires the tight integration of clinical and molecular data. To this end, it is mandatory to define proper technological solutions able to manage the overwhelming amount of high throughput genomic data needed to test associations between genomic signatures and human phenotypes. The i2b2 Center (Informatics for Integrating Biology and the Bedside) has developed a widely internationally adopted framework to use existing clinical data for discovery research that can help the definition of precision medicine interventions when coupled with genetic data. i2b2 can be significantly advanced by designing efficient management solutions of Next Generation Sequencing data. We developed BigQ, an extension of the i2b2 framework, which integrates patient clinical phenotypes with genomic variant profiles generated by Next Generation Sequencing. A visual programming i2b2 plugin allows retrieving variants belonging to the patients in a cohort by applying filters on genomic variant annotations. We report an evaluation of the query performance of our system on more than 11 million variants, showing that the implemented solution scales linearly in terms of query time and disk space with the number of variants. In this paper we describe a new i2b2 web service composed of an efficient and scalable document-based database that manages annotations of genomic variants and of a visual programming plug-in designed to dynamically perform queries on clinical and genetic data. The system therefore allows managing the fast growing volume of genomic variants and can be used to integrate heterogeneous genomic annotations.

ReadXplorer—visualization and analysis of mapped sequences

PubMed Central

Hilker, Rolf; Stadermann, Kai Bernd; Doppmeier, Daniel; Kalinowski, Jörn; Stoye, Jens; Straube, Jasmin; Winnebald, Jörn; Goesmann, Alexander

2014-01-01

Motivation: Fast algorithms and well-arranged visualizations are required for the comprehensive analysis of the ever-growing size of genomic and transcriptomic next-generation sequencing data. Results: ReadXplorer is a software offering straightforward visualization and extensive analysis functions for genomic and transcriptomic DNA sequences mapped on a reference. A unique specialty of ReadXplorer is the quality classification of the read mappings. It is incorporated in all analysis functions and displayed in ReadXplorer's various synchronized data viewers for (i) the reference sequence, its base coverage as (ii) normalizable plot and (iii) histogram, (iv) read alignments and (v) read pairs. ReadXplorer's analysis capability covers RNA secondary structure prediction, single nucleotide polymorphism and deletion–insertion polymorphism detection, genomic feature and general coverage analysis. Especially for RNA-Seq data, it offers differential gene expression analysis, transcription start site and operon detection as well as RPKM value and read count calculations. Furthermore, ReadXplorer can combine or superimpose coverage of different datasets. Availability and implementation: ReadXplorer is available as open-source software at http://www.readxplorer.org along with a detailed manual. Contact: rhilker@mikrobio.med.uni-giessen.de Supplementary information: Supplementary data are available at Bioinformatics online. PMID:24790157

e23D: database and visualization of A-to-I RNA editing sites mapped to 3D protein structures.

PubMed

Solomon, Oz; Eyal, Eran; Amariglio, Ninette; Unger, Ron; Rechavi, Gidi

2016-07-15

e23D, a database of A-to-I RNA editing sites from human, mouse and fly mapped to evolutionary related protein 3D structures, is presented. Genomic coordinates of A-to-I RNA editing sites are converted to protein coordinates and mapped onto 3D structures from PDB or theoretical models from ModBase. e23D allows visualization of the protein structure, modeling of recoding events and orientation of the editing with respect to nearby genomic functional sites from databases of disease causing mutations and genomic polymorphism. http://www.sheba-cancer.org.il/e23D CONTACT: oz.solomon@live.biu.ac.il or Eran.Eyal@sheba.health.gov.il. © The Author 2016. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

TCGA4U: A Web-Based Genomic Analysis Platform To Explore And Mine TCGA Genomic Data For Translational Research.

PubMed

Huang, Zhenzhen; Duan, Huilong; Li, Haomin

2015-01-01

Large-scale human cancer genomics projects, such as TCGA, generated large genomics data for further study. Exploring and mining these data to obtain meaningful analysis results can help researchers find potential genomics alterations that intervene the development and metastasis of tumors. We developed a web-based gene analysis platform, named TCGA4U, which used statistics methods and models to help translational investigators explore, mine and visualize human cancer genomic characteristic information from the TCGA datasets. Furthermore, through Gene Ontology (GO) annotation and clinical data integration, the genomic data were transformed into biological process, molecular function, cellular component and survival curves to help researchers identify potential driver genes. Clinical researchers without expertise in data analysis will benefit from such a user-friendly genomic analysis platform.

SOFIA: an R package for enhancing genetic visualization with Circos

USDA-ARS?s Scientific Manuscript database

Visualization of data from any stage of genetic and genomic research is one of the most useful approaches for detecting potential errors, ensuring accuracy and reproducibility, and presentation of the resulting data. Currently software such as Circos, ClicO FS, and RCircos, among others, provide too...

TreeGenes and CartograTree: Enabling visualization and analysis in forest tree genomics

Treesearch

E.S. Grau; S.A. Demurjian; H.A. Vasquez-Gross; D.G. Gessler; D.B. Neale; J.L. Wegrzyn

2017-01-01

Association studies integrating environmental, phenotypic, and genetic data are key in understanding forest tree resilience to climate change and disease. As genomic resources increase, both in terms of complete reference sequences and magnitude of individuals genotyped, researchers are better equipped to identify correlations between genetic variation and adaptive or...

Figure 1 from Integrative Genomics Viewer: Visualizing Big Data | Office of Cancer Genomics

Cancer.gov

A screenshot of the IGV user interface at the chromosome view. IGV user interface showing five data types (copy number, methylation, gene expression, and loss of heterozygosity; mutations are overlaid with black boxes) from approximately 80 glioblastoma multiforme samples. Adapted from Figure S1; Robinson et al. 2011

Fast neutron mutants database and web displays at SoyBase

USDA-ARS?s Scientific Manuscript database

SoyBase, the USDA-ARS soybean genetics and genomics database, has been expanded to include data for the fast neutron mutants produced by Bolon, Vance, et al. In addition to the expected text and sequence homology searches and visualization of the indels in the context of the genome sequence viewer, ...

GlobAl Distribution of GEnetic Traits (GADGET) web server: polygenic trait scores worldwide.

PubMed

Chande, Aroon T; Wang, Lu; Rishishwar, Lavanya; Conley, Andrew B; Norris, Emily T; Valderrama-Aguirre, Augusto; Jordan, I King

2018-05-18

Human populations from around the world show striking phenotypic variation across a wide variety of traits. Genome-wide association studies (GWAS) are used to uncover genetic variants that influence the expression of heritable human traits; accordingly, population-specific distributions of GWAS-implicated variants may shed light on the genetic basis of human phenotypic diversity. With this in mind, we developed the GlobAl Distribution of GEnetic Traits web server (GADGET http://gadget.biosci.gatech.edu). The GADGET web server provides users with a dynamic visual platform for exploring the relationship between worldwide genetic diversity and the genetic architecture underlying numerous human phenotypes. GADGET integrates trait-implicated single nucleotide polymorphisms (SNPs) from GWAS, with population genetic data from the 1000 Genomes Project, to calculate genome-wide polygenic trait scores (PTS) for 818 phenotypes in 2504 individual genomes. Population-specific distributions of PTS are shown for 26 human populations across 5 continental population groups, with traits ordered based on the extent of variation observed among populations. Users of GADGET can also upload custom trait SNP sets to visualize global PTS distributions for their own traits of interest.

ngs.plot: Quick mining and visualization of next-generation sequencing data by integrating genomic databases.

PubMed

Shen, Li; Shao, Ningyi; Liu, Xiaochuan; Nestler, Eric

2014-04-15

Understanding the relationship between the millions of functional DNA elements and their protein regulators, and how they work in conjunction to manifest diverse phenotypes, is key to advancing our understanding of the mammalian genome. Next-generation sequencing technology is now used widely to probe these protein-DNA interactions and to profile gene expression at a genome-wide scale. As the cost of DNA sequencing continues to fall, the interpretation of the ever increasing amount of data generated represents a considerable challenge. We have developed ngs.plot - a standalone program to visualize enrichment patterns of DNA-interacting proteins at functionally important regions based on next-generation sequencing data. We demonstrate that ngs.plot is not only efficient but also scalable. We use a few examples to demonstrate that ngs.plot is easy to use and yet very powerful to generate figures that are publication ready. We conclude that ngs.plot is a useful tool to help fill the gap between massive datasets and genomic information in this era of big sequencing data.

ngs.plot: Quick mining and visualization of next-generation sequencing data by integrating genomic databases

PubMed Central

2014-01-01

Background Understanding the relationship between the millions of functional DNA elements and their protein regulators, and how they work in conjunction to manifest diverse phenotypes, is key to advancing our understanding of the mammalian genome. Next-generation sequencing technology is now used widely to probe these protein-DNA interactions and to profile gene expression at a genome-wide scale. As the cost of DNA sequencing continues to fall, the interpretation of the ever increasing amount of data generated represents a considerable challenge. Results We have developed ngs.plot – a standalone program to visualize enrichment patterns of DNA-interacting proteins at functionally important regions based on next-generation sequencing data. We demonstrate that ngs.plot is not only efficient but also scalable. We use a few examples to demonstrate that ngs.plot is easy to use and yet very powerful to generate figures that are publication ready. Conclusions We conclude that ngs.plot is a useful tool to help fill the gap between massive datasets and genomic information in this era of big sequencing data. PMID:24735413

Visualization of specific repetitive genomic sequences with fluorescent TALEs in Arabidopsis thaliana

PubMed Central

Fujimoto, Satoru; Sugano, Shigeo S.; Kuwata, Keiko; Osakabe, Keishi; Matsunaga, Sachihiro

2016-01-01

Live imaging of the dynamics of nuclear organization provides the opportunity to uncover the mechanisms responsible for four-dimensional genome architecture. Here, we describe the use of fluorescent protein (FP) fusions of transcription activator-like effectors (TALEs) to visualize endogenous genomic sequences in Arabidopsis thaliana. The ability to engineer sequence-specific TALEs permits the investigation of precise genomic sequences. We could detect TALE-FP signals associated with centromeric, telomeric, and rDNA repeats and the signal distribution was consistent with that observed by fluorescent in situ hybridization. TALE-FPs are advantageous because they permit the observation of intact tissues. We used our TALE-FP method to investigate the nuclei of several multicellular plant tissues including roots, hypocotyls, leaves, and flowers. Because TALE-FPs permit live-cell imaging, we successfully observed the temporal dynamics of centromeres and telomeres in plant organs. Fusing TALEs to multimeric FPs enhanced the signal intensity when observing telomeres. We found that the mobility of telomeres was different in sub-nuclear regions. Transgenic plants stably expressing TALE-FPs will provide new insights into chromatin organization and dynamics in multicellular organisms. PMID:27811079

A versatile genome-scale PCR-based pipeline for high-definition DNA FISH.

PubMed

Bienko, Magda; Crosetto, Nicola; Teytelman, Leonid; Klemm, Sandy; Itzkovitz, Shalev; van Oudenaarden, Alexander

2013-02-01

We developed a cost-effective genome-scale PCR-based method for high-definition DNA FISH (HD-FISH). We visualized gene loci with diffraction-limited resolution, chromosomes as spot clusters and single genes together with transcripts by combining HD-FISH with single-molecule RNA FISH. We provide a database of over 4.3 million primer pairs targeting the human and mouse genomes that is readily usable for rapid and flexible generation of probes.

Visual Display of 5p-arm and 3p-arm miRNA Expression with a Mobile Application.

PubMed

Pan, Chao-Yu; Kuo, Wei-Ting; Chiu, Chien-Yuan; Lin, Wen-Chang

2017-01-01

MicroRNAs (miRNAs) play important roles in human cancers. In previous studies, we have demonstrated that both 5p-arm and 3p-arm of mature miRNAs could be expressed from the same precursor and we further interrogated the 5p-arm and 3p-arm miRNA expression with a comprehensive arm feature annotation list. To assist biologists to visualize the differential 5p-arm and 3p-arm miRNA expression patterns, we utilized a user-friendly mobile App to display. The Cancer Genome Atlas (TCGA) miRNA-Seq expression information. We have collected over 4,500 miRNA-Seq datasets from 15 TCGA cancer types and further processed them with the 5p-arm and 3p-arm annotation analysis pipeline. In order to be displayed with the RNA-Seq Viewer App, annotated 5p-arm and 3p-arm miRNA expression information and miRNA gene loci information were converted into SQLite tables. In this distinct application, for any given miRNA gene, 5p-arm miRNA is illustrated on the top of chromosome ideogram and 3p-arm miRNA is illustrated on the bottom of chromosome ideogram. Users can then easily interrogate the differentially 5p-arm/3p-arm expressed miRNAs with their mobile devices. This study demonstrates the feasibility and utility of RNA-Seq Viewer App in addition to mRNA-Seq data visualization.

PANDA: pathway and annotation explorer for visualizing and interpreting gene-centric data.

PubMed

Hart, Steven N; Moore, Raymond M; Zimmermann, Michael T; Oliver, Gavin R; Egan, Jan B; Bryce, Alan H; Kocher, Jean-Pierre A

2015-01-01

Objective. Bringing together genomics, transcriptomics, proteomics, and other -omics technologies is an important step towards developing highly personalized medicine. However, instrumentation has advances far beyond expectations and now we are able to generate data faster than it can be interpreted. Materials and Methods. We have developed PANDA (Pathway AND Annotation) Explorer, a visualization tool that integrates gene-level annotation in the context of biological pathways to help interpret complex data from disparate sources. PANDA is a web-based application that displays data in the context of well-studied pathways like KEGG, BioCarta, and PharmGKB. PANDA represents data/annotations as icons in the graph while maintaining the other data elements (i.e., other columns for the table of annotations). Custom pathways from underrepresented diseases can be imported when existing data sources are inadequate. PANDA also allows sharing annotations among collaborators. Results. In our first use case, we show how easy it is to view supplemental data from a manuscript in the context of a user's own data. Another use-case is provided describing how PANDA was leveraged to design a treatment strategy from the somatic variants found in the tumor of a patient with metastatic sarcomatoid renal cell carcinoma. Conclusion. PANDA facilitates the interpretation of gene-centric annotations by visually integrating this information with context of biological pathways. The application can be downloaded or used directly from our website: http://bioinformaticstools.mayo.edu/research/panda-viewer/.

Evolutionary interrogation of human biology in well-annotated genomic framework of rhesus macaque.

PubMed

Zhang, Shi-Jian; Liu, Chu-Jun; Yu, Peng; Zhong, Xiaoming; Chen, Jia-Yu; Yang, Xinzhuang; Peng, Jiguang; Yan, Shouyu; Wang, Chenqu; Zhu, Xiaotong; Xiong, Jingwei; Zhang, Yong E; Tan, Bertrand Chin-Ming; Li, Chuan-Yun

2014-05-01

With genome sequence and composition highly analogous to human, rhesus macaque represents a unique reference for evolutionary studies of human biology. Here, we developed a comprehensive genomic framework of rhesus macaque, the RhesusBase2, for evolutionary interrogation of human genes and the associated regulations. A total of 1,667 next-generation sequencing (NGS) data sets were processed, integrated, and evaluated, generating 51.2 million new functional annotation records. With extensive NGS annotations, RhesusBase2 refined the fine-scale structures in 30% of the macaque Ensembl transcripts, reporting an accurate, up-to-date set of macaque gene models. On the basis of these annotations and accurate macaque gene models, we further developed an NGS-oriented Molecular Evolution Gateway to access and visualize macaque annotations in reference to human orthologous genes and associated regulations (www.rhesusbase.org/molEvo). We highlighted the application of this well-annotated genomic framework in generating hypothetical link of human-biased regulations to human-specific traits, by using mechanistic characterization of the DIEXF gene as an example that provides novel clues to the understanding of digestive system reduction in human evolution. On a global scale, we also identified a catalog of 9,295 human-biased regulatory events, which may represent novel elements that have a substantial impact on shaping human transcriptome and possibly underpin recent human phenotypic evolution. Taken together, we provide an NGS data-driven, information-rich framework that will broadly benefit genomics research in general and serves as an important resource for in-depth evolutionary studies of human biology.

Genetic parameter estimates for carcass traits and visual scores including or not genomic information.

PubMed

Gordo, D G M; Espigolan, R; Tonussi, R L; Júnior, G A F; Bresolin, T; Magalhães, A F Braga; Feitosa, F L; Baldi, F; Carvalheiro, R; Tonhati, H; de Oliveira, H N; Chardulo, L A L; de Albuquerque, L G

2016-05-01

The objective of this study was to determine whether visual scores used as selection criteria in Nellore breeding programs are effective indicators of carcass traits measured after slaughter. Additionally, this study evaluated the effect of different structures of the relationship matrix ( and ) on the estimation of genetic parameters and on the prediction accuracy of breeding values. There were 13,524 animals for visual scores of conformation (CS), finishing precocity (FP), and muscling (MS) and 1,753, 1,747, and 1,564 for LM area (LMA), backfat thickness (BF), and HCW, respectively. Of these, 1,566 animals were genotyped using a high-density panel containing 777,962 SNP. Six analyses were performed using multitrait animal models, each including the 3 visual scores and 1 carcass trait. For the visual scores, the model included direct additive genetic and residual random effects and the fixed effects of contemporary group (defined by year of birth, management group at yearling, and farm) and the linear effect of age of animal at yearling. The same model was used for the carcass traits, replacing the effect of age of animal at yearling with the linear effect of age of animal at slaughter. The variance and covariance components were estimated by the REML method in analyses using the numerator relationship matrix () or combining the genomic and the numerator relationship matrices (). The heritability estimates for the visual scores obtained with the 2 methods were similar and of moderate magnitude (0.23-0.34), indicating that these traits should response to direct selection. The heritabilities for LMA, BF, and HCW were 0.13, 0.07, and 0.17, respectively, using matrix and 0.29, 0.16, and 0.23, respectively, using matrix . The genetic correlations between the visual scores and carcass traits were positive, and higher correlations were generally obtained when matrix was used. Considering the difficulties and cost of measuring carcass traits postmortem, visual scores of CS, FP, and MS could be used as selection criteria to improve HCW, BF, and LMA. The use of genomic information permitted the detection of greater additive genetic variability for LMA and BF. For HCW, the high magnitude of the genetic correlations with visual scores was probably sufficient to recover genetic variability. The methods provided similar breeding value accuracies, especially for the visual scores.

CoryneRegNet 3.0--an interactive systems biology platform for the analysis of gene regulatory networks in corynebacteria and Escherichia coli.

PubMed

Baumbach, Jan; Wittkop, Tobias; Rademacher, Katrin; Rahmann, Sven; Brinkrolf, Karina; Tauch, Andreas

2007-04-30

CoryneRegNet is an ontology-based data warehouse for the reconstruction and visualization of transcriptional regulatory interactions in prokaryotes. To extend the biological content of CoryneRegNet, we added comprehensive data on transcriptional regulations in the model organism Escherichia coli K-12, originally deposited in the international reference database RegulonDB. The enhanced web interface of CoryneRegNet offers several types of search options. The results of a search are displayed in a table-based style and include a visualization of the genetic organization of the respective gene region. Information on DNA binding sites of transcriptional regulators is depicted by sequence logos. The results can also be displayed by several layouters implemented in the graphical user interface GraphVis, allowing, for instance, the visualization of genome-wide network reconstructions and the homology-based inter-species comparison of reconstructed gene regulatory networks. In an application example, we compare the composition of the gene regulatory networks involved in the SOS response of E. coli and Corynebacterium glutamicum. CoryneRegNet is available at the following URL: http://www.cebitec.uni-bielefeld.de/groups/gi/software/coryneregnet/.

Mapping the Space of Genomic Signatures

PubMed Central

Kari, Lila; Hill, Kathleen A.; Sayem, Abu S.; Karamichalis, Rallis; Bryans, Nathaniel; Davis, Katelyn; Dattani, Nikesh S.

2015-01-01

We propose a computational method to measure and visualize interrelationships among any number of DNA sequences allowing, for example, the examination of hundreds or thousands of complete mitochondrial genomes. An "image distance" is computed for each pair of graphical representations of DNA sequences, and the distances are visualized as a Molecular Distance Map: Each point on the map represents a DNA sequence, and the spatial proximity between any two points reflects the degree of structural similarity between the corresponding sequences. The graphical representation of DNA sequences utilized, Chaos Game Representation (CGR), is genome- and species-specific and can thus act as a genomic signature. Consequently, Molecular Distance Maps could inform species identification, taxonomic classifications and, to a certain extent, evolutionary history. The image distance employed, Structural Dissimilarity Index (DSSIM), implicitly compares the occurrences of oligomers of length up to k (herein k = 9) in DNA sequences. We computed DSSIM distances for more than 5 million pairs of complete mitochondrial genomes, and used Multi-Dimensional Scaling (MDS) to obtain Molecular Distance Maps that visually display the sequence relatedness in various subsets, at different taxonomic levels. This general-purpose method does not require DNA sequence alignment and can thus be used to compare similar or vastly different DNA sequences, genomic or computer-generated, of the same or different lengths. We illustrate potential uses of this approach by applying it to several taxonomic subsets: phylum Vertebrata, (super)kingdom Protista, classes Amphibia-Insecta-Mammalia, class Amphibia, and order Primates. This analysis of an extensive dataset confirms that the oligomer composition of full mtDNA sequences can be a source of taxonomic information. This method also correctly finds the mtDNA sequences most closely related to that of the anatomically modern human (the Neanderthal, the Denisovan, and the chimp), and that the sequence most different from it in this dataset belongs to a cucumber. PMID:26000734

Update on RefSeq microbial genomes resources.

PubMed

Tatusova, Tatiana; Ciufo, Stacy; Federhen, Scott; Fedorov, Boris; McVeigh, Richard; O'Neill, Kathleen; Tolstoy, Igor; Zaslavsky, Leonid

2015-01-01

NCBI RefSeq genome collection http://www.ncbi.nlm.nih.gov/genome represents all three major domains of life: Eukarya, Bacteria and Archaea as well as Viruses. Prokaryotic genome sequences are the most rapidly growing part of the collection. During the year of 2014 more than 10,000 microbial genome assemblies have been publicly released bringing the total number of prokaryotic genomes close to 30,000. We continue to improve the quality and usability of the microbial genome resources by providing easy access to the data and the results of the pre-computed analysis, and improving analysis and visualization tools. A number of improvements have been incorporated into the Prokaryotic Genome Annotation Pipeline. Several new features have been added to RefSeq prokaryotic genomes data processing pipeline including the calculation of genome groups (clades) and the optimization of protein clusters generation using pan-genome approach. Published by Oxford University Press on behalf of Nucleic Acids Research 2014. This work is written by US Government employees and is in the public domain in the US.

The coffee genome hub: a resource for coffee genomes

PubMed Central

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

Basics and applications of genome editing technology.

PubMed

Yamamoto, Takashi; Sakamoto, Naoaki

2016-01-01

Genome editing with programmable site-specific nucleases is an emerging technology that enables the manipulation of targeted genes in many organisms and cell lines. Since the development of the CRISPR-Cas9 system in 2012, genome editing has rapidly become an indispensable technology for all life science researchers, applicable in various fields. In this seminar, we will introduce the basics of genome editing and focus on the recent development of genome editing tools and technologies for the modification of various organisms and discuss future directions of the genome editing research field, from basic to medical applications.

Versatile design and synthesis platform for visualizing genomes with Oligopaint FISH probes

PubMed Central

Beliveau, Brian J.; Joyce, Eric F.; Apostolopoulos, Nicholas; Yilmaz, Feyza; Fonseka, Chamith Y.; McCole, Ruth B.; Chang, Yiming; Li, Jin Billy; Senaratne, Tharanga Niroshini; Williams, Benjamin R.; Rouillard, Jean-Marie; Wu, Chao-ting

2012-01-01

A host of observations demonstrating the relationship between nuclear architecture and processes such as gene expression have led to a number of new technologies for interrogating chromosome positioning. Whereas some of these technologies reconstruct intermolecular interactions, others have enhanced our ability to visualize chromosomes in situ. Here, we describe an oligonucleotide- and PCR-based strategy for fluorescence in situ hybridization (FISH) and a bioinformatic platform that enables this technology to be extended to any organism whose genome has been sequenced. The oligonucleotide probes are renewable, highly efficient, and able to robustly label chromosomes in cell culture, fixed tissues, and metaphase spreads. Our method gives researchers precise control over the sequences they target and allows for single and multicolor imaging of regions ranging from tens of kilobases to megabases with the same basic protocol. We anticipate this technology will lead to an enhanced ability to visualize interphase and metaphase chromosomes. PMID:23236188

The MaizeGDB Genome Browser tutorial: one example of database outreach to biologists via video.

PubMed

Harper, Lisa C; Schaeffer, Mary L; Thistle, Jordan; Gardiner, Jack M; Andorf, Carson M; Campbell, Darwin A; Cannon, Ethalinda K S; Braun, Bremen L; Birkett, Scott M; Lawrence, Carolyn J; Sen, Taner Z

2011-01-01

Video tutorials are an effective way for researchers to quickly learn how to use online tools offered by biological databases. At MaizeGDB, we have developed a number of video tutorials that demonstrate how to use various tools and explicitly outline the caveats researchers should know to interpret the information available to them. One such popular video currently available is 'Using the MaizeGDB Genome Browser', which describes how the maize genome was sequenced and assembled as well as how the sequence can be visualized and interacted with via the MaizeGDB Genome Browser. Database

Optimizing ChIP-seq peak detectors using visual labels and supervised machine learning

PubMed Central

Goerner-Potvin, Patricia; Morin, Andreanne; Shao, Xiaojian; Pastinen, Tomi

2017-01-01

Motivation: Many peak detection algorithms have been proposed for ChIP-seq data analysis, but it is not obvious which algorithm and what parameters are optimal for any given dataset. In contrast, regions with and without obvious peaks can be easily labeled by visual inspection of aligned read counts in a genome browser. We propose a supervised machine learning approach for ChIP-seq data analysis, using labels that encode qualitative judgments about which genomic regions contain or do not contain peaks. The main idea is to manually label a small subset of the genome, and then learn a model that makes consistent peak predictions on the rest of the genome. Results: We created 7 new histone mark datasets with 12 826 visually determined labels, and analyzed 3 existing transcription factor datasets. We observed that default peak detection parameters yield high false positive rates, which can be reduced by learning parameters using a relatively small training set of labeled data from the same experiment type. We also observed that labels from different people are highly consistent. Overall, these data indicate that our supervised labeling method is useful for quantitatively training and testing peak detection algorithms. Availability and Implementation: Labeled histone mark data http://cbio.ensmp.fr/~thocking/chip-seq-chunk-db/, R package to compute the label error of predicted peaks https://github.com/tdhock/PeakError Contacts: toby.hocking@mail.mcgill.ca or guil.bourque@mcgill.ca Supplementary information: Supplementary data are available at Bioinformatics online. PMID:27797775

Optimizing ChIP-seq peak detectors using visual labels and supervised machine learning.

PubMed

Hocking, Toby Dylan; Goerner-Potvin, Patricia; Morin, Andreanne; Shao, Xiaojian; Pastinen, Tomi; Bourque, Guillaume

2017-02-15

Many peak detection algorithms have been proposed for ChIP-seq data analysis, but it is not obvious which algorithm and what parameters are optimal for any given dataset. In contrast, regions with and without obvious peaks can be easily labeled by visual inspection of aligned read counts in a genome browser. We propose a supervised machine learning approach for ChIP-seq data analysis, using labels that encode qualitative judgments about which genomic regions contain or do not contain peaks. The main idea is to manually label a small subset of the genome, and then learn a model that makes consistent peak predictions on the rest of the genome. We created 7 new histone mark datasets with 12 826 visually determined labels, and analyzed 3 existing transcription factor datasets. We observed that default peak detection parameters yield high false positive rates, which can be reduced by learning parameters using a relatively small training set of labeled data from the same experiment type. We also observed that labels from different people are highly consistent. Overall, these data indicate that our supervised labeling method is useful for quantitatively training and testing peak detection algorithms. Labeled histone mark data http://cbio.ensmp.fr/~thocking/chip-seq-chunk-db/ , R package to compute the label error of predicted peaks https://github.com/tdhock/PeakError. toby.hocking@mail.mcgill.ca or guil.bourque@mcgill.ca. Supplementary data are available at Bioinformatics online. © The Author 2016. Published by Oxford University Press.

AnnotateGenomicRegions: a web application.

PubMed

Zammataro, Luca; DeMolfetta, Rita; Bucci, Gabriele; Ceol, Arnaud; Muller, Heiko

2014-01-01

Modern genomic technologies produce large amounts of data that can be mapped to specific regions in the genome. Among the first steps in interpreting the results is annotation of genomic regions with known features such as genes, promoters, CpG islands etc. Several tools have been published to perform this task. However, using these tools often requires a significant amount of bioinformatics skills and/or downloading and installing dedicated software. Here we present AnnotateGenomicRegions, a web application that accepts genomic regions as input and outputs a selection of overlapping and/or neighboring genome annotations. Supported organisms include human (hg18, hg19), mouse (mm8, mm9, mm10), zebrafish (danRer7), and Saccharomyces cerevisiae (sacCer2, sacCer3). AnnotateGenomicRegions is accessible online on a public server or can be installed locally. Some frequently used annotations and genomes are embedded in the application while custom annotations may be added by the user. The increasing spread of genomic technologies generates the need for a simple-to-use annotation tool for genomic regions that can be used by biologists and bioinformaticians alike. AnnotateGenomicRegions meets this demand. AnnotateGenomicRegions is an open-source web application that can be installed on any personal computer or institute server. AnnotateGenomicRegions is available at: http://cru.genomics.iit.it/AnnotateGenomicRegions.

AnnotateGenomicRegions: a web application

PubMed Central

2014-01-01

Background Modern genomic technologies produce large amounts of data that can be mapped to specific regions in the genome. Among the first steps in interpreting the results is annotation of genomic regions with known features such as genes, promoters, CpG islands etc. Several tools have been published to perform this task. However, using these tools often requires a significant amount of bioinformatics skills and/or downloading and installing dedicated software. Results Here we present AnnotateGenomicRegions, a web application that accepts genomic regions as input and outputs a selection of overlapping and/or neighboring genome annotations. Supported organisms include human (hg18, hg19), mouse (mm8, mm9, mm10), zebrafish (danRer7), and Saccharomyces cerevisiae (sacCer2, sacCer3). AnnotateGenomicRegions is accessible online on a public server or can be installed locally. Some frequently used annotations and genomes are embedded in the application while custom annotations may be added by the user. Conclusions The increasing spread of genomic technologies generates the need for a simple-to-use annotation tool for genomic regions that can be used by biologists and bioinformaticians alike. AnnotateGenomicRegions meets this demand. AnnotateGenomicRegions is an open-source web application that can be installed on any personal computer or institute server. AnnotateGenomicRegions is available at: http://cru.genomics.iit.it/AnnotateGenomicRegions. PMID:24564446

EvoSNP-DB: A database of genetic diversity in East Asian populations.

PubMed

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/].

TADtool: visual parameter identification for TAD-calling algorithms.

PubMed

Kruse, Kai; Hug, Clemens B; Hernández-Rodríguez, Benjamín; Vaquerizas, Juan M

2016-10-15

Eukaryotic genomes are hierarchically organized into topologically associating domains (TADs). The computational identification of these domains and their associated properties critically depends on the choice of suitable parameters of TAD-calling algorithms. To reduce the element of trial-and-error in parameter selection, we have developed TADtool: an interactive plot to find robust TAD-calling parameters with immediate visual feedback. TADtool allows the direct export of TADs called with a chosen set of parameters for two of the most common TAD calling algorithms: directionality and insulation index. It can be used as an intuitive, standalone application or as a Python package for maximum flexibility. TADtool is available as a Python package from GitHub (https://github.com/vaquerizaslab/tadtool) or can be installed directly via PyPI, the Python package index (tadtool). kai.kruse@mpi-muenster.mpg.de, jmv@mpi-muenster.mpg.deSupplementary information: Supplementary data are available at Bioinformatics online. © The Author 2016. Published by Oxford University Press.

MutScan: fast detection and visualization of target mutations by scanning FASTQ data.

PubMed

Chen, Shifu; Huang, Tanxiao; Wen, Tiexiang; Li, Hong; Xu, Mingyan; Gu, Jia

2018-01-22

Some types of clinical genetic tests, such as cancer testing using circulating tumor DNA (ctDNA), require sensitive detection of known target mutations. However, conventional next-generation sequencing (NGS) data analysis pipelines typically involve different steps of filtering, which may cause miss-detection of key mutations with low frequencies. Variant validation is also indicated for key mutations detected by bioinformatics pipelines. Typically, this process can be executed using alignment visualization tools such as IGV or GenomeBrowse. However, these tools are too heavy and therefore unsuitable for validating mutations in ultra-deep sequencing data. We developed MutScan to address problems of sensitive detection and efficient validation for target mutations. MutScan involves highly optimized string-searching algorithms, which can scan input FASTQ files to grab all reads that support target mutations. The collected supporting reads for each target mutation will be piled up and visualized using web technologies such as HTML and JavaScript. Algorithms such as rolling hash and bloom filter are applied to accelerate scanning and make MutScan applicable to detect or visualize target mutations in a very fast way. MutScan is a tool for the detection and visualization of target mutations by only scanning FASTQ raw data directly. Compared to conventional pipelines, this offers a very high performance, executing about 20 times faster, and offering maximal sensitivity since it can grab mutations with even one single supporting read. MutScan visualizes detected mutations by generating interactive pile-ups using web technologies. These can serve to validate target mutations, thus avoiding false positives. Furthermore, MutScan can visualize all mutation records in a VCF file to HTML pages for cloud-friendly VCF validation. MutScan is an open source tool available at GitHub: https://github.com/OpenGene/MutScan.

BiologicalNetworks 2.0 - an integrative view of genome biology data

PubMed Central

2010-01-01

Background A significant problem in the study of mechanisms of an organism's development is the elucidation of interrelated factors which are making an impact on the different levels of the organism, such as genes, biological molecules, cells, and cell systems. Numerous sources of heterogeneous data which exist for these subsystems are still not integrated sufficiently enough to give researchers a straightforward opportunity to analyze them together in the same frame of study. Systematic application of data integration methods is also hampered by a multitude of such factors as the orthogonal nature of the integrated data and naming problems. Results Here we report on a new version of BiologicalNetworks, a research environment for the integral visualization and analysis of heterogeneous biological data. BiologicalNetworks can be queried for properties of thousands of different types of biological entities (genes/proteins, promoters, COGs, pathways, binding sites, and other) and their relations (interactions, co-expression, co-citations, and other). The system includes the build-pathways infrastructure for molecular interactions/relations and module discovery in high-throughput experiments. Also implemented in BiologicalNetworks are the Integrated Genome Viewer and Comparative Genomics Browser applications, which allow for the search and analysis of gene regulatory regions and their conservation in multiple species in conjunction with molecular pathways/networks, experimental data and functional annotations. Conclusions The new release of BiologicalNetworks together with its back-end database introduces extensive functionality for a more efficient integrated multi-level analysis of microarray, sequence, regulatory, and other data. BiologicalNetworks is freely available at http://www.biologicalnetworks.org. PMID:21190573

Applications of CRISPR Genome Engineering in Cell Biology.

PubMed

Wang, Fangyuan; Qi, Lei S

2016-11-01

Recent advances in genome engineering are starting a revolution in biological research and translational applications. The clustered regularly interspaced short palindromic repeats (CRISPR)-associated RNA-guided endonuclease CRISPR associated protein 9 (Cas9) and its variants enable diverse manipulations of genome function. In this review, we describe the development of Cas9 tools for a variety of applications in cell biology research, including the study of functional genomics, the creation of transgenic animal models, and genomic imaging. Novel genome engineering methods offer a new avenue to understand the causality between the genome and phenotype, thus promising a fuller understanding of cell biology. Copyright © 2016 Elsevier Ltd. All rights reserved.

Genomic analysis and geographic visualization of H5N1 and SARS-CoV.

PubMed

Hill, Andrew W; Alexandrov, Boyan; Guralnick, Robert P; Janies, Daniel

2007-10-11

Emerging infectious diseases and organisms present critical issues of national security public health, and economic welfare. We still understand little about the zoonotic potential of many viruses. To this end, we are developing novel database tools to manage comparative genomic datasets. These tools add value because they allow us to summarize the direction, frequency and order of genomic changes. We will perform numerous real world tests with our tools with both Avian Influenza and Coronaviruses.

Rhodobase, a meta-analytical tool for reconstructing gene regulatory networks in a model photosynthetic bacterium.

PubMed

Moskvin, Oleg V; Bolotin, Dmitry; Wang, Andrew; Ivanov, Pavel S; Gomelsky, Mark

2011-02-01

We present Rhodobase, a web-based meta-analytical tool for analysis of transcriptional regulation in a model anoxygenic photosynthetic bacterium, Rhodobacter sphaeroides. The gene association meta-analysis is based on the pooled data from 100 of R. sphaeroides whole-genome DNA microarrays. Gene-centric regulatory networks were visualized using the StarNet approach (Jupiter, D.C., VanBuren, V., 2008. A visual data mining tool that facilitates reconstruction of transcription regulatory networks. PLoS ONE 3, e1717) with several modifications. We developed a means to identify and visualize operons and superoperons. We designed a framework for the cross-genome search for transcription factor binding sites that takes into account high GC-content and oligonucleotide usage profile characteristic of the R. sphaeroides genome. To facilitate reconstruction of directional relationships between co-regulated genes, we screened upstream sequences (-400 to +20bp from start codons) of all genes for putative binding sites of bacterial transcription factors using a self-optimizing search method developed here. To test performance of the meta-analysis tools and transcription factor site predictions, we reconstructed selected nodes of the R. sphaeroides transcription factor-centric regulatory matrix. The test revealed regulatory relationships that correlate well with the experimentally derived data. The database of transcriptional profile correlations, the network visualization engine and the optimized search engine for transcription factor binding sites analysis are available at http://rhodobase.org. Copyright © 2010 Elsevier Ireland Ltd. All rights reserved.

Surveying the maize community for their diversity and pedigree visualization needs to prioritize tool development and curation

USDA-ARS?s Scientific Manuscript database

The Maize Genetics and Genomics Database (MaizeGDB) team prepared a survey to identify breeders’ needs for visualizing pedigrees, diversity data, and haplotypes in order to prioritize tool development and curation efforts at MaizeGDB. The survey was distributed to the maize research community on beh...

svviz: a read viewer for validating structural variants.

PubMed

Spies, Noah; Zook, Justin M; Salit, Marc; Sidow, Arend

2015-12-15

Visualizing read alignments is the most effective way to validate candidate structural variants (SVs) with existing data. We present svviz, a sequencing read visualizer for SVs that sorts and displays only reads relevant to a candidate SV. svviz works by searching input bam(s) for potentially relevant reads, realigning them against the inferred sequence of the putative variant allele as well as the reference allele and identifying reads that match one allele better than the other. Separate views of the two alleles are then displayed in a scrollable web browser view, enabling a more intuitive visualization of each allele, compared with the single reference genome-based view common to most current read browsers. The browser view facilitates examining the evidence for or against a putative variant, estimating zygosity, visualizing affected genomic annotations and manual refinement of breakpoints. svviz supports data from most modern sequencing platforms. svviz is implemented in python and freely available from http://svviz.github.io/. Published by Oxford University Press 2015. This work is written by US Government employees and is in the public domain in the US.

Setting Up the JBrowse Genome Browser

PubMed Central

Skinner, Mitchell E; Holmes, Ian H

2010-01-01

JBrowse is a web-based tool for visualizing genomic data. Unlike most other web-based genome browsers, JBrowse exploits the capabilities of the user's web browser to make scrolling and zooming fast and smooth. It supports the browsers used by almost all internet users, and is relatively simple to install. JBrowse can utilize multiple types of data in a variety of common genomic data formats, including genomic feature data in bioperl databases, GFF files, and BED files, and quantitative data in wiggle files. This unit describes how to obtain the JBrowse software, set it up on a Linux or Mac OS X computer running as a web server and incorporate genome annotation data from multiple sources into JBrowse. After completing the protocols described in this unit, the reader will have a web site that other users can visit to browse the genomic data. PMID:21154710

RefSeq microbial genomes database: new representation and annotation strategy.

PubMed

Tatusova, Tatiana; Ciufo, Stacy; Fedorov, Boris; O'Neill, Kathleen; Tolstoy, Igor

2014-01-01

The source of the microbial genomic sequences in the RefSeq collection is the set of primary sequence records submitted to the International Nucleotide Sequence Database public archives. These can be accessed through the Entrez search and retrieval system at http://www.ncbi.nlm.nih.gov/genome. Next-generation sequencing has enabled researchers to perform genomic sequencing at rates that were unimaginable in the past. Microbial genomes can now be sequenced in a matter of hours, which has led to a significant increase in the number of assembled genomes deposited in the public archives. This huge increase in DNA sequence data presents new challenges for the annotation, analysis and visualization bioinformatics tools. New strategies have been developed for the annotation and representation of reference genomes and sequence variations derived from population studies and clinical outbreaks.

The Genome-based Knowledge Management in Cycles model: a complex adaptive systems framework for implementation of genomic applications.

PubMed

Arar, Nedal; Knight, Sara J; Modell, Stephen M; Issa, Amalia M

2011-03-01

The main mission of the Genomic Applications in Practice and Prevention Network™ is to advance collaborative efforts involving partners from across the public health sector to realize the promise of genomics in healthcare and disease prevention. We introduce a new framework that supports the Genomic Applications in Practice and Prevention Network mission and leverages the characteristics of the complex adaptive systems approach. We call this framework the Genome-based Knowledge Management in Cycles model (G-KNOMIC). G-KNOMIC proposes that the collaborative work of multidisciplinary teams utilizing genome-based applications will enhance translating evidence-based genomic findings by creating ongoing knowledge management cycles. Each cycle consists of knowledge synthesis, knowledge evaluation, knowledge implementation and knowledge utilization. Our framework acknowledges that all the elements in the knowledge translation process are interconnected and continuously changing. It also recognizes the importance of feedback loops, and the ability of teams to self-organize within a dynamic system. We demonstrate how this framework can be used to improve the adoption of genomic technologies into practice using two case studies of genomic uptake.

A comprehensive and quantitative exploration of thousands of viral genomes

PubMed Central

Mahmoudabadi, Gita

2018-01-01

The complete assembly of viral genomes from metagenomic datasets (short genomic sequences gathered from environmental samples) has proven to be challenging, so there are significant blind spots when we view viral genomes through the lens of metagenomics. One approach to overcoming this problem is to leverage the thousands of complete viral genomes that are publicly available. Here we describe our efforts to assemble a comprehensive resource that provides a quantitative snapshot of viral genomic trends – such as gene density, noncoding percentage, and abundances of functional gene categories – across thousands of viral genomes. We have also developed a coarse-grained method for visualizing viral genome organization for hundreds of genomes at once, and have explored the extent of the overlap between bacterial and bacteriophage gene pools. Existing viral classification systems were developed prior to the sequencing era, so we present our analysis in a way that allows us to assess the utility of the different classification systems for capturing genomic trends. PMID:29624169

A comprehensive and quantitative exploration of thousands of viral genomes.

PubMed

Mahmoudabadi, Gita; Phillips, Rob

2018-04-19

The complete assembly of viral genomes from metagenomic datasets (short genomic sequences gathered from environmental samples) has proven to be challenging, so there are significant blind spots when we view viral genomes through the lens of metagenomics. One approach to overcoming this problem is to leverage the thousands of complete viral genomes that are publicly available. Here we describe our efforts to assemble a comprehensive resource that provides a quantitative snapshot of viral genomic trends - such as gene density, noncoding percentage, and abundances of functional gene categories - across thousands of viral genomes. We have also developed a coarse-grained method for visualizing viral genome organization for hundreds of genomes at once, and have explored the extent of the overlap between bacterial and bacteriophage gene pools. Existing viral classification systems were developed prior to the sequencing era, so we present our analysis in a way that allows us to assess the utility of the different classification systems for capturing genomic trends. © 2018, Mahmoudabadi et al.

A method for simultaneously delineating multiple targets in 3D-FISH using limited channels, lasers, and fluorochromes.

PubMed

Zhao, F Y; Yang, X; Chen, D Y; Ma, W Y; Zheng, J G; Zhang, X M

2014-01-01

Many studies have suggested a link between the spatial organization of genomes and fundamental biological processes such as genome reprogramming, gene expression, and differentiation. Multicolor fluorescence in situ hybridization on three-dimensionally preserved nuclei (3D-FISH), in combination with confocal microscopy, has become an effective technique for analyzing 3D genome structure and spatial patterns of defined nucleus targets including entire chromosome territories and single gene loci. This technique usually requires the simultaneous visualization of numerous targets labeled with different colored fluorochromes. Thus, the number of channels and lasers must be sufficient for the commonly used labeling scheme of 3D-FISH, "one probe-one target". However, these channels and lasers are usually restricted by a given microscope system. This paper presents a method for simultaneously delineating multiple targets in 3D-FISH using limited channels, lasers, and fluorochromes. In contrast to other labeling schemes, this method is convenient and simple for multicolor 3D-FISH studies, which may result in widespread adoption of the technique. Lastly, as an application of the method, the nucleus locations of chromosome territory 18/21 and centromere 18/21/13 in normal human lymphocytes were analyzed, which might present evidence of a radial higher order chromatin arrangement.

BloodChIP: a database of comparative genome-wide transcription factor binding profiles in human blood cells.

PubMed

Chacon, Diego; Beck, Dominik; Perera, Dilmi; Wong, Jason W H; Pimanda, John E

2014-01-01

The BloodChIP database (http://www.med.unsw.edu.au/CRCWeb.nsf/page/BloodChIP) supports exploration and visualization of combinatorial transcription factor (TF) binding at a particular locus in human CD34-positive and other normal and leukaemic cells or retrieval of target gene sets for user-defined combinations of TFs across one or more cell types. Increasing numbers of genome-wide TF binding profiles are being added to public repositories, and this trend is likely to continue. For the power of these data sets to be fully harnessed by experimental scientists, there is a need for these data to be placed in context and easily accessible for downstream applications. To this end, we have built a user-friendly database that has at its core the genome-wide binding profiles of seven key haematopoietic TFs in human stem/progenitor cells. These binding profiles are compared with binding profiles in normal differentiated and leukaemic cells. We have integrated these TF binding profiles with chromatin marks and expression data in normal and leukaemic cell fractions. All queries can be exported into external sites to construct TF-gene and protein-protein networks and to evaluate the association of genes with cellular processes and tissue expression.

The dissonance mutation at the no-on-transient-A locus of D. melanogaster: genetic control of courtship song and visual behaviors by a protein with putative RNA-binding motifs.

PubMed

Rendahl, K G; Jones, K R; Kulkarni, S J; Bagully, S H; Hall, J C

1992-02-01

Genetic and molecular results are here presented revealing that the dissonance (diss) courtship song mutation is an allele of the no-on-transient-A (nonA) locus of Drosophila melanogaster. diss (now called nonAdiss) was originally isolated as a mutant with aberrant pulse song, although it was then noted to exhibit defects in responses to visual stimuli as well. The lack of transient spikes in the electroretinogram (ERG) and optomotor blindness associated with nonAdiss are shown to be similar to the visual abnormalities caused by the original nonA mutations. nonAdiss failed to complement either the ERG or optomotor defects associated with four other nonA mutations. However, all four of these nonA mutants--which were isolated on visual criteria alone--sang a normal courtship song. nonAdiss complemented at least three of the nonA mutations with regard to the singing phenotype, as assessed by a new method for temporal analysis of the male's pulse song. Both visual and song abnormalities caused by nonAdiss were rescued by P-element-mediated transformation with overlapping 11 and 16 kilobase (kb) fragments of genomic DNA (originally cloned from the nonA locus by Jones and Rubin, 1990). Analysis of behavioral phenotypes in transformed flies carrying mutagenized versions of the 11 kb genomic fragment (in a nonAdiss genomic background) localized the rescuing DNA to a region containing an open reading frame that encodes a polypeptide (NONA) with similarity to a family of RNA-binding proteins. Immunohistochemical determination of NONA's spatial and temporal expression revealed that it is localized to the nuclei of cells in many neural and non-neural tissues, at all stages of the life cycle after very early in development. Genetic connections between the control of two quite different behaviors--reproductive and visual--are discussed, along with precedences for generally expressed gene products playing roles in specific behaviors.

QMachine: commodity supercomputing in web browsers.

PubMed

Wilkinson, Sean R; Almeida, Jonas S

2014-06-09

Ongoing advancements in cloud computing provide novel opportunities in scientific computing, especially for distributed workflows. Modern web browsers can now be used as high-performance workstations for querying, processing, and visualizing genomics' "Big Data" from sources like The Cancer Genome Atlas (TCGA) and the International Cancer Genome Consortium (ICGC) without local software installation or configuration. The design of QMachine (QM) was driven by the opportunity to use this pervasive computing model in the context of the Web of Linked Data in Biomedicine. QM is an open-sourced, publicly available web service that acts as a messaging system for posting tasks and retrieving results over HTTP. The illustrative application described here distributes the analyses of 20 Streptococcus pneumoniae genomes for shared suffixes. Because all analytical and data retrieval tasks are executed by volunteer machines, few server resources are required. Any modern web browser can submit those tasks and/or volunteer to execute them without installing any extra plugins or programs. A client library provides high-level distribution templates including MapReduce. This stark departure from the current reliance on expensive server hardware running "download and install" software has already gathered substantial community interest, as QM received more than 2.2 million API calls from 87 countries in 12 months. QM was found adequate to deliver the sort of scalable bioinformatics solutions that computation- and data-intensive workflows require. Paradoxically, the sandboxed execution of code by web browsers was also found to enable them, as compute nodes, to address critical privacy concerns that characterize biomedical environments.

Enabling functional genomics with genome engineering

PubMed Central

Hilton, Isaac B.; Gersbach, Charles A.

2015-01-01

Advances in genome engineering technologies have made the precise control over genome sequence and regulation possible across a variety of disciplines. These tools can expand our understanding of fundamental biological processes and create new opportunities for therapeutic designs. The rapid evolution of these methods has also catalyzed a new era of genomics that includes multiple approaches to functionally characterize and manipulate the regulation of genomic information. Here, we review the recent advances of the most widely adopted genome engineering platforms and their application to functional genomics. This includes engineered zinc finger proteins, TALEs/TALENs, and the CRISPR/Cas9 system as nucleases for genome editing, transcription factors for epigenome editing, and other emerging applications. We also present current and potential future applications of these tools, as well as their current limitations and areas for future advances. PMID:26430154

shinyCircos: an R/Shiny application for interactive creation of Circos plot.

PubMed

Yu, Yiming; Ouyang, Yidan; Yao, Wen

2018-04-01

Creation of Circos plot is one of the most efficient approaches to visualize genomic data. However, the installation and use of existing tools to make Circos plot are challenging for users lacking of coding experiences. To address this issue, we developed an R/Shiny application shinyCircos, a graphical user interface for interactive creation of Circos plot. shinyCircos can be easily installed either on computers for personal use or on local or public servers to provide online use to the community. Furthermore, various types of Circos plots could be easily generated and decorated with simple mouse-click. shinyCircos and its manual are freely available at https://github.com/venyao/shinyCircos. shinyCircos is deployed at https://yimingyu.shinyapps.io/shinycircos/ and http://shinycircos.ncpgr.cn/ for online use. diana1983941@mail.hzau.edu.cn or yaowen@henau.edu.cn.

Closing the gap between knowledge and clinical application: challenges for genomic translation.

PubMed

Burke, Wylie; Korngiebel, Diane M

2015-01-01

Despite early predictions and rapid progress in research, the introduction of personal genomics into clinical practice has been slow. Several factors contribute to this translational gap between knowledge and clinical application. The evidence available to support genetic test use is often limited, and implementation of new testing programs can be challenging. In addition, the heterogeneity of genomic risk information points to the need for strategies to select and deliver the information most appropriate for particular clinical needs. Accomplishing these tasks also requires recognition that some expectations for personal genomics are unrealistic, notably expectations concerning the clinical utility of genomic risk assessment for common complex diseases. Efforts are needed to improve the body of evidence addressing clinical outcomes for genomics, apply implementation science to personal genomics, and develop realistic goals for genomic risk assessment. In addition, translational research should emphasize the broader benefits of genomic knowledge, including applications of genomic research that provide clinical benefit outside the context of personal genomic risk.

BioSAVE: display of scored annotation within a sequence context.

PubMed

Pollock, Richard F; Adryan, Boris

2008-03-20

Visualization of sequence annotation is a common feature in many bioinformatics tools. For many applications it is desirable to restrict the display of such annotation according to a score cutoff, as biological interpretation can be difficult in the presence of the entire data. Unfortunately, many visualisation solutions are somewhat static in the way they handle such score cutoffs. We present BioSAVE, a sequence annotation viewer with on-the-fly selection of visualisation thresholds for each feature. BioSAVE is a versatile OS X program for visual display of scored features (annotation) within a sequence context. The program reads sequence and additional supplementary annotation data (e.g., position weight matrix matches, conservation scores, structural domains) from a variety of commonly used file formats and displays them graphically. Onscreen controls then allow for live customisation of these graphics, including on-the-fly selection of visualisation thresholds for each feature. Possible applications of the program include display of transcription factor binding sites in a genomic context or the visualisation of structural domain assignments in protein sequences and many more. The dynamic visualisation of these annotations is useful, e.g., for the determination of cutoff values of predicted features to match experimental data. Program, source code and exemplary files are freely available at the BioSAVE homepage.

BioSAVE: Display of scored annotation within a sequence context

PubMed Central

Pollock, Richard F; Adryan, Boris

2008-01-01

Background Visualization of sequence annotation is a common feature in many bioinformatics tools. For many applications it is desirable to restrict the display of such annotation according to a score cutoff, as biological interpretation can be difficult in the presence of the entire data. Unfortunately, many visualisation solutions are somewhat static in the way they handle such score cutoffs. Results We present BioSAVE, a sequence annotation viewer with on-the-fly selection of visualisation thresholds for each feature. BioSAVE is a versatile OS X program for visual display of scored features (annotation) within a sequence context. The program reads sequence and additional supplementary annotation data (e.g., position weight matrix matches, conservation scores, structural domains) from a variety of commonly used file formats and displays them graphically. Onscreen controls then allow for live customisation of these graphics, including on-the-fly selection of visualisation thresholds for each feature. Conclusion Possible applications of the program include display of transcription factor binding sites in a genomic context or the visualisation of structural domain assignments in protein sequences and many more. The dynamic visualisation of these annotations is useful, e.g., for the determination of cutoff values of predicted features to match experimental data. Program, source code and exemplary files are freely available at the BioSAVE homepage. PMID:18366701

The MaizeGDB Genome Browser tutorial: one example of database outreach to biologists via video

PubMed Central

Harper, Lisa C.; Schaeffer, Mary L.; Thistle, Jordan; Gardiner, Jack M.; Andorf, Carson M.; Campbell, Darwin A.; Cannon, Ethalinda K.S.; Braun, Bremen L.; Birkett, Scott M.; Lawrence, Carolyn J.; Sen, Taner Z.

2011-01-01

Video tutorials are an effective way for researchers to quickly learn how to use online tools offered by biological databases. At MaizeGDB, we have developed a number of video tutorials that demonstrate how to use various tools and explicitly outline the caveats researchers should know to interpret the information available to them. One such popular video currently available is ‘Using the MaizeGDB Genome Browser’, which describes how the maize genome was sequenced and assembled as well as how the sequence can be visualized and interacted with via the MaizeGDB Genome Browser. Database URL: http://www.maizegdb.org/ PMID:21565781

RegPrecise 3.0--a resource for genome-scale exploration of transcriptional regulation in bacteria.

PubMed

Novichkov, Pavel S; Kazakov, Alexey E; Ravcheev, Dmitry A; Leyn, Semen A; Kovaleva, Galina Y; Sutormin, Roman A; Kazanov, Marat D; Riehl, William; Arkin, Adam P; Dubchak, Inna; Rodionov, Dmitry A

2013-11-01

Genome-scale prediction of gene regulation and reconstruction of transcriptional regulatory networks in prokaryotes is one of the critical tasks of modern genomics. Bacteria from different taxonomic groups, whose lifestyles and natural environments are substantially different, possess highly diverged transcriptional regulatory networks. The comparative genomics approaches are useful for in silico reconstruction of bacterial regulons and networks operated by both transcription factors (TFs) and RNA regulatory elements (riboswitches). RegPrecise (http://regprecise.lbl.gov) is a web resource for collection, visualization and analysis of transcriptional regulons reconstructed by comparative genomics. We significantly expanded a reference collection of manually curated regulons we introduced earlier. RegPrecise 3.0 provides access to inferred regulatory interactions organized by phylogenetic, structural and functional properties. Taxonomy-specific collections include 781 TF regulogs inferred in more than 160 genomes representing 14 taxonomic groups of Bacteria. TF-specific collections include regulogs for a selected subset of 40 TFs reconstructed across more than 30 taxonomic lineages. Novel collections of regulons operated by RNA regulatory elements (riboswitches) include near 400 regulogs inferred in 24 bacterial lineages. RegPrecise 3.0 provides four classifications of the reference regulons implemented as controlled vocabularies: 55 TF protein families; 43 RNA motif families; ~150 biological processes or metabolic pathways; and ~200 effectors or environmental signals. Genome-wide visualization of regulatory networks and metabolic pathways covered by the reference regulons are available for all studied genomes. A separate section of RegPrecise 3.0 contains draft regulatory networks in 640 genomes obtained by an conservative propagation of the reference regulons to closely related genomes. RegPrecise 3.0 gives access to the transcriptional regulons reconstructed in bacterial genomes. Analytical capabilities include exploration of: regulon content, structure and function; TF binding site motifs; conservation and variations in genome-wide regulatory networks across all taxonomic groups of Bacteria. RegPrecise 3.0 was selected as a core resource on transcriptional regulation of the Department of Energy Systems Biology Knowledgebase, an emerging software and data environment designed to enable researchers to collaboratively generate, test and share new hypotheses about gene and protein functions, perform large-scale analyses, and model interactions in microbes, plants, and their communities.

Using the Saccharomyces Genome Database (SGD) for analysis of genomic information

PubMed Central

Skrzypek, Marek S.; Hirschman, Jodi

2011-01-01

Analysis of genomic data requires access to software tools that place the sequence-derived information in the context of biology. The Saccharomyces Genome Database (SGD) integrates functional information about budding yeast genes and their products with a set of analysis tools that facilitate exploring their biological details. This unit describes how the various types of functional data available at SGD can be searched, retrieved, and analyzed. Starting with the guided tour of the SGD Home page and Locus Summary page, this unit highlights how to retrieve data using YeastMine, how to visualize genomic information with GBrowse, how to explore gene expression patterns with SPELL, and how to use Gene Ontology tools to characterize large-scale datasets. PMID:21901739

D3GB: An Interactive Genome Browser for R, Python, and WordPress.

PubMed

Barrios, David; Prieto, Carlos

2017-05-01

Genome browsers are useful not only for showing final results but also for improving analysis protocols, testing data quality, and generating result drafts. Its integration in analysis pipelines allows the optimization of parameters, which leads to better results. New developments that facilitate the creation and utilization of genome browsers could contribute to improving analysis results and supporting the quick visualization of genomic data. D3 Genome Browser is an interactive genome browser that can be easily integrated in analysis protocols and shared on the Web. It is distributed as an R package, a Python module, and a WordPress plugin to facilitate its integration in pipelines and the utilization of platform capabilities. It is compatible with popular data formats such as GenBank, GFF, BED, FASTA, and VCF, and enables the exploration of genomic data with a Web browser.

The topography of mutational processes in breast cancer genomes.

PubMed

Morganella, Sandro; Alexandrov, Ludmil B; Glodzik, Dominik; Zou, Xueqing; Davies, Helen; Staaf, Johan; Sieuwerts, Anieta M; Brinkman, Arie B; Martin, Sancha; Ramakrishna, Manasa; Butler, Adam; Kim, Hyung-Yong; Borg, Åke; Sotiriou, Christos; Futreal, P Andrew; Campbell, Peter J; Span, Paul N; Van Laere, Steven; Lakhani, Sunil R; Eyfjord, Jorunn E; Thompson, Alastair M; Stunnenberg, Hendrik G; van de Vijver, Marc J; Martens, John W M; Børresen-Dale, Anne-Lise; Richardson, Andrea L; Kong, Gu; Thomas, Gilles; Sale, Julian; Rada, Cristina; Stratton, Michael R; Birney, Ewan; Nik-Zainal, Serena

2016-05-02

Somatic mutations in human cancers show unevenness in genomic distribution that correlate with aspects of genome structure and function. These mutations are, however, generated by multiple mutational processes operating through the cellular lineage between the fertilized egg and the cancer cell, each composed of specific DNA damage and repair components and leaving its own characteristic mutational signature on the genome. Using somatic mutation catalogues from 560 breast cancer whole-genome sequences, here we show that each of 12 base substitution, 2 insertion/deletion (indel) and 6 rearrangement mutational signatures present in breast tissue, exhibit distinct relationships with genomic features relating to transcription, DNA replication and chromatin organization. This signature-based approach permits visualization of the genomic distribution of mutational processes associated with APOBEC enzymes, mismatch repair deficiency and homologous recombinational repair deficiency, as well as mutational processes of unknown aetiology. Furthermore, it highlights mechanistic insights including a putative replication-dependent mechanism of APOBEC-related mutagenesis.

Enabling functional genomics with genome engineering.

PubMed

Hilton, Isaac B; Gersbach, Charles A

2015-10-01

Advances in genome engineering technologies have made the precise control over genome sequence and regulation possible across a variety of disciplines. These tools can expand our understanding of fundamental biological processes and create new opportunities for therapeutic designs. The rapid evolution of these methods has also catalyzed a new era of genomics that includes multiple approaches to functionally characterize and manipulate the regulation of genomic information. Here, we review the recent advances of the most widely adopted genome engineering platforms and their application to functional genomics. This includes engineered zinc finger proteins, TALEs/TALENs, and the CRISPR/Cas9 system as nucleases for genome editing, transcription factors for epigenome editing, and other emerging applications. We also present current and potential future applications of these tools, as well as their current limitations and areas for future advances. © 2015 Hilton and Gersbach; Published by Cold Spring Harbor Laboratory Press.

3D chromosome rendering from Hi-C data using virtual reality

NASA Astrophysics Data System (ADS)

Zhu, Yixin; Selvaraj, Siddarth; Weber, Philip; Fang, Jennifer; Schulze, Jürgen P.; Ren, Bing

2015-01-01

Most genome browsers display DNA linearly, using single-dimensional depictions that are useful to examine certain epigenetic mechanisms such as DNA methylation. However, these representations are insufficient to visualize intrachromosomal interactions and relationships between distal genome features. Relationships between DNA regions may be difficult to decipher or missed entirely if those regions are distant in one dimension but could be spatially proximal when mapped to three-dimensional space. For example, the visualization of enhancers folding over genes is only fully expressed in three-dimensional space. Thus, to accurately understand DNA behavior during gene expression, a means to model chromosomes is essential. Using coordinates generated from Hi-C interaction frequency data, we have created interactive 3D models of whole chromosome structures and its respective domains. We have also rendered information on genomic features such as genes, CTCF binding sites, and enhancers. The goal of this article is to present the procedure, findings, and conclusions of our models and renderings.

BigWig and BigBed: enabling browsing of large distributed datasets.

PubMed

Kent, W J; Zweig, A S; Barber, G; Hinrichs, A S; Karolchik, D

2010-09-01

BigWig and BigBed files are compressed binary indexed files containing data at several resolutions that allow the high-performance display of next-generation sequencing experiment results in the UCSC Genome Browser. The visualization is implemented using a multi-layered software approach that takes advantage of specific capabilities of web-based protocols and Linux and UNIX operating systems files, R trees and various indexing and compression tricks. As a result, only the data needed to support the current browser view is transmitted rather than the entire file, enabling fast remote access to large distributed data sets. Binaries for the BigWig and BigBed creation and parsing utilities may be downloaded at http://hgdownload.cse.ucsc.edu/admin/exe/linux.x86_64/. Source code for the creation and visualization software is freely available for non-commercial use at http://hgdownload.cse.ucsc.edu/admin/jksrc.zip, implemented in C and supported on Linux. The UCSC Genome Browser is available at http://genome.ucsc.edu.

SEURAT: visual analytics for the integrated analysis of microarray data.

PubMed

Gribov, Alexander; Sill, Martin; Lück, Sonja; Rücker, Frank; Döhner, Konstanze; Bullinger, Lars; Benner, Axel; Unwin, Antony

2010-06-03

In translational cancer research, gene expression data is collected together with clinical data and genomic data arising from other chip based high throughput technologies. Software tools for the joint analysis of such high dimensional data sets together with clinical data are required. We have developed an open source software tool which provides interactive visualization capability for the integrated analysis of high-dimensional gene expression data together with associated clinical data, array CGH data and SNP array data. The different data types are organized by a comprehensive data manager. Interactive tools are provided for all graphics: heatmaps, dendrograms, barcharts, histograms, eventcharts and a chromosome browser, which displays genetic variations along the genome. All graphics are dynamic and fully linked so that any object selected in a graphic will be highlighted in all other graphics. For exploratory data analysis the software provides unsupervised data analytics like clustering, seriation algorithms and biclustering algorithms. The SEURAT software meets the growing needs of researchers to perform joint analysis of gene expression, genomical and clinical data.

An interactive environment for agile analysis and visualization of ChIP-sequencing data.

PubMed

Lerdrup, Mads; Johansen, Jens Vilstrup; Agrawal-Singh, Shuchi; Hansen, Klaus

2016-04-01

To empower experimentalists with a means for fast and comprehensive chromatin immunoprecipitation sequencing (ChIP-seq) data analyses, we introduce an integrated computational environment, EaSeq. The software combines the exploratory power of genome browsers with an extensive set of interactive and user-friendly tools for genome-wide abstraction and visualization. It enables experimentalists to easily extract information and generate hypotheses from their own data and public genome-wide datasets. For demonstration purposes, we performed meta-analyses of public Polycomb ChIP-seq data and established a new screening approach to analyze more than 900 datasets from mouse embryonic stem cells for factors potentially associated with Polycomb recruitment. EaSeq, which is freely available and works on a standard personal computer, can substantially increase the throughput of many analysis workflows, facilitate transparency and reproducibility by automatically documenting and organizing analyses, and enable a broader group of scientists to gain insights from ChIP-seq data.

Next Generation Sequence Analysis and Computational Genomics Using Graphical Pipeline Workflows

PubMed Central

Torri, Federica; Dinov, Ivo D.; Zamanyan, Alen; Hobel, Sam; Genco, Alex; Petrosyan, Petros; Clark, Andrew P.; Liu, Zhizhong; Eggert, Paul; Pierce, Jonathan; Knowles, James A.; Ames, Joseph; Kesselman, Carl; Toga, Arthur W.; Potkin, Steven G.; Vawter, Marquis P.; Macciardi, Fabio

2012-01-01

Whole-genome and exome sequencing have already proven to be essential and powerful methods to identify genes responsible for simple Mendelian inherited disorders. These methods can be applied to complex disorders as well, and have been adopted as one of the current mainstream approaches in population genetics. These achievements have been made possible by next generation sequencing (NGS) technologies, which require substantial bioinformatics resources to analyze the dense and complex sequence data. The huge analytical burden of data from genome sequencing might be seen as a bottleneck slowing the publication of NGS papers at this time, especially in psychiatric genetics. We review the existing methods for processing NGS data, to place into context the rationale for the design of a computational resource. We describe our method, the Graphical Pipeline for Computational Genomics (GPCG), to perform the computational steps required to analyze NGS data. The GPCG implements flexible workflows for basic sequence alignment, sequence data quality control, single nucleotide polymorphism analysis, copy number variant identification, annotation, and visualization of results. These workflows cover all the analytical steps required for NGS data, from processing the raw reads to variant calling and annotation. The current version of the pipeline is freely available at http://pipeline.loni.ucla.edu. These applications of NGS analysis may gain clinical utility in the near future (e.g., identifying miRNA signatures in diseases) when the bioinformatics approach is made feasible. Taken together, the annotation tools and strategies that have been developed to retrieve information and test hypotheses about the functional role of variants present in the human genome will help to pinpoint the genetic risk factors for psychiatric disorders. PMID:23139896

RATT: Rapid Annotation Transfer Tool

PubMed Central

Otto, Thomas D.; Dillon, Gary P.; Degrave, Wim S.; Berriman, Matthew

2011-01-01

Second-generation sequencing technologies have made large-scale sequencing projects commonplace. However, making use of these datasets often requires gene function to be ascribed genome wide. Although tool development has kept pace with the changes in sequence production, for tasks such as mapping, de novo assembly or visualization, genome annotation remains a challenge. We have developed a method to rapidly provide accurate annotation for new genomes using previously annotated genomes as a reference. The method, implemented in a tool called RATT (Rapid Annotation Transfer Tool), transfers annotations from a high-quality reference to a new genome on the basis of conserved synteny. We demonstrate that a Mycobacterium tuberculosis genome or a single 2.5 Mb chromosome from a malaria parasite can be annotated in less than five minutes with only modest computational resources. RATT is available at http://ratt.sourceforge.net. PMID:21306991

CRISPR Mediated Genome Engineering and its Application in Industry.

PubMed

Kaboli, Saeed; Babazada, Hasan

2018-01-01

The CRISPR (clustered regularly interspaced short palindromic repeat)-Cas9 (CRISPR-associated nuclease 9) method has been dramatically changing the field of genome engineering. It is a rapid, highly efficient and versatile tool for precise modification of genome that uses a guide RNA (gRNA) to target Cas9 to a specific sequence. This novel RNA-guided genome-editing technique has become a revolutionary tool in biomedical science and has many innovative applications in different fields. In this review, we briefly introduce the Cas9-mediated genome-editing tool, summarize the recent advances in CRISPR/Cas9 technology to engineer the genomes of a wide variety of organisms, and discuss their applications to treatment of fungal and viral disease. We also discuss advantageous of CRISPR/Cas9 technology to drug design, creation of animal model, and to food, agricultural and energy sciences. Adoption of the CRISPR/Cas9 technology in biomedical and biotechnological researches would create innovative applications of it not only for breeding of strains exhibiting desired traits for specific industrial and medical applications, but also for investigation of genome function.

Catch the live show: Visualizing damaged DNA in vivo.

PubMed

Oshidari, Roxanne; Mekhail, Karim

2018-06-01

The health of an organism is intimately linked to its ability to repair damaged DNA. Importantly, DNA repair processes are highly dynamic. This highlights the necessity of characterizing DNA repair in live cells. Advanced genome editing and imaging approaches allow us to visualize damaged DNA and its associated factors in real time. Here, we summarize both established and recent methods that are used to induce DNA damage and visualize damaged DNA and its repair in live cells. Copyright © 2018 Elsevier Inc. All rights reserved.

Building international genomics collaboration for global health security

DOE Office of Scientific and Technical Information (OSTI.GOV)

Cui, Helen H.; Erkkila, Tracy; Chain, Patrick S. G.

Genome science and technologies are transforming life sciences globally in many ways and becoming a highly desirable area for international collaboration to strengthen global health. The Genome Science Program at the Los Alamos National Laboratory is leveraging a long history of expertise in genomics research to assist multiple partner nations in advancing their genomics and bioinformatics capabilities. The capability development objectives focus on providing a molecular genomics-based scientific approach for pathogen detection, characterization, and biosurveillance applications. The general approaches include introduction of basic principles in genomics technologies, training on laboratory methodologies and bioinformatic analysis of resulting data, procurement, and installationmore » of next-generation sequencing instruments, establishing bioinformatics software capabilities, and exploring collaborative applications of the genomics capabilities in public health. Genome centers have been established with public health and research institutions in the Republic of Georgia, Kingdom of Jordan, Uganda, and Gabon; broader collaborations in genomics applications have also been developed with research institutions in many other countries.« less

Building international genomics collaboration for global health security

DOE PAGES

Cui, Helen H.; Erkkila, Tracy; Chain, Patrick S. G.; ...

2015-12-07

Genome science and technologies are transforming life sciences globally in many ways and becoming a highly desirable area for international collaboration to strengthen global health. The Genome Science Program at the Los Alamos National Laboratory is leveraging a long history of expertise in genomics research to assist multiple partner nations in advancing their genomics and bioinformatics capabilities. The capability development objectives focus on providing a molecular genomics-based scientific approach for pathogen detection, characterization, and biosurveillance applications. The general approaches include introduction of basic principles in genomics technologies, training on laboratory methodologies and bioinformatic analysis of resulting data, procurement, and installationmore » of next-generation sequencing instruments, establishing bioinformatics software capabilities, and exploring collaborative applications of the genomics capabilities in public health. Genome centers have been established with public health and research institutions in the Republic of Georgia, Kingdom of Jordan, Uganda, and Gabon; broader collaborations in genomics applications have also been developed with research institutions in many other countries.« less

A survey of tools for variant analysis of next-generation genome sequencing data

PubMed Central

Pabinger, Stephan; Dander, Andreas; Fischer, Maria; Snajder, Rene; Sperk, Michael; Efremova, Mirjana; Krabichler, Birgit; Speicher, Michael R.; Zschocke, Johannes

2014-01-01

Recent advances in genome sequencing technologies provide unprecedented opportunities to characterize individual genomic landscapes and identify mutations relevant for diagnosis and therapy. Specifically, whole-exome sequencing using next-generation sequencing (NGS) technologies is gaining popularity in the human genetics community due to the moderate costs, manageable data amounts and straightforward interpretation of analysis results. While whole-exome and, in the near future, whole-genome sequencing are becoming commodities, data analysis still poses significant challenges and led to the development of a plethora of tools supporting specific parts of the analysis workflow or providing a complete solution. Here, we surveyed 205 tools for whole-genome/whole-exome sequencing data analysis supporting five distinct analytical steps: quality assessment, alignment, variant identification, variant annotation and visualization. We report an overview of the functionality, features and specific requirements of the individual tools. We then selected 32 programs for variant identification, variant annotation and visualization, which were subjected to hands-on evaluation using four data sets: one set of exome data from two patients with a rare disease for testing identification of germline mutations, two cancer data sets for testing variant callers for somatic mutations, copy number variations and structural variations, and one semi-synthetic data set for testing identification of copy number variations. Our comprehensive survey and evaluation of NGS tools provides a valuable guideline for human geneticists working on Mendelian disorders, complex diseases and cancers. PMID:23341494

PGG.Population: a database for understanding the genomic diversity and genetic ancestry of human populations

PubMed Central

Zhang, Chao; Gao, Yang; Liu, Jiaojiao; Xue, Zhe; Lu, Yan; Deng, Lian; Tian, Lei; Feng, Qidi

2018-01-01

Abstract There are a growing number of studies focusing on delineating genetic variations that are associated with complex human traits and diseases due to recent advances in next-generation sequencing technologies. However, identifying and prioritizing disease-associated causal variants relies on understanding the distribution of genetic variations within and among populations. The PGG.Population database documents 7122 genomes representing 356 global populations from 107 countries and provides essential information for researchers to understand human genomic diversity and genetic ancestry. These data and information can facilitate the design of research studies and the interpretation of results of both evolutionary and medical studies involving human populations. The database is carefully maintained and constantly updated when new data are available. We included miscellaneous functions and a user-friendly graphical interface for visualization of genomic diversity, population relationships (genetic affinity), ancestral makeup, footprints of natural selection, and population history etc. Moreover, PGG.Population provides a useful feature for users to analyze data and visualize results in a dynamic style via online illustration. The long-term ambition of the PGG.Population, together with the joint efforts from other researchers who contribute their data to our database, is to create a comprehensive depository of geographic and ethnic variation of human genome, as well as a platform bringing influence on future practitioners of medicine and clinical investigators. PGG.Population is available at https://www.pggpopulation.org. PMID:29112749

Archelosaurian Color Vision, Parietal Eye Loss, and the Crocodylian Nocturnal Bottleneck.

PubMed

Emerling, Christopher A

2017-03-01

Vertebrate color vision has evolved partly through the modification of five ancestral visual opsin proteins via gene duplication, loss, and shifts in spectral sensitivity. While many vertebrates, particularly mammals, birds, and fishes, have had their visual opsin repertoires studied in great detail, testudines (turtles) and crocodylians have largely been neglected. Here I examine the genomic basis for color vision in four species of turtles and four species of crocodylians, and demonstrate that while turtles appear to vary in their number of visual opsins, crocodylians experienced a reduction in their color discrimination capacity after their divergence from Aves. Based on the opsin sequences present in their genomes and previous measurements of crocodylian cones, I provide evidence that crocodylians have co-opted the rod opsin (RH1) for cone function. This suggests that some crocodylians might have reinvented trichromatic color vision in a novel way, analogous to several primate lineages. The loss of visual opsins in crocodylians paralleled the loss of various anatomical features associated with photoreception, attributed to a "nocturnal bottleneck" similar to that hypothesized for Mesozoic mammals. I further queried crocodylian genomes for nonvisual opsins and genes associated with protection from ultraviolet light, and found evidence for gene inactivation or loss for several of these genes. Two genes, encoding parietopsin and parapinopsin, were additionally inactivated in birds and turtles, likely co-occurring with the loss of the parietal eye in these lineages. © The Author 2016. Published by Oxford University Press on behalf of the Society for Molecular Biology and Evolution. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

GIANT API: an application programming interface for functional genomics.

PubMed

Roberts, Andrew M; Wong, Aaron K; Fisk, Ian; Troyanskaya, Olga G

2016-07-08

GIANT API provides biomedical researchers programmatic access to tissue-specific and global networks in humans and model organisms, and associated tools, which includes functional re-prioritization of existing genome-wide association study (GWAS) data. Using tissue-specific interaction networks, researchers are able to predict relationships between genes specific to a tissue or cell lineage, identify the changing roles of genes across tissues and uncover disease-gene associations. Additionally, GIANT API enables computational tools like NetWAS, which leverages tissue-specific networks for re-prioritization of GWAS results. The web services covered by the API include 144 tissue-specific functional gene networks in human, global functional networks for human and six common model organisms and the NetWAS method. GIANT API conforms to the REST architecture, which makes it stateless, cacheable and highly scalable. It can be used by a diverse range of clients including web browsers, command terminals, programming languages and standalone apps for data analysis and visualization. The API is freely available for use at http://giant-api.princeton.edu. © The Author(s) 2016. Published by Oxford University Press on behalf of Nucleic Acids Research.

Structural Analysis of Biodiversity

PubMed Central

Sirovich, Lawrence; Stoeckle, Mark Y.; Zhang, Yu

2010-01-01

Large, recently-available genomic databases cover a wide range of life forms, suggesting opportunity for insights into genetic structure of biodiversity. In this study we refine our recently-described technique using indicator vectors to analyze and visualize nucleotide sequences. The indicator vector approach generates correlation matrices, dubbed Klee diagrams, which represent a novel way of assembling and viewing large genomic datasets. To explore its potential utility, here we apply the improved algorithm to a collection of almost 17000 DNA barcode sequences covering 12 widely-separated animal taxa, demonstrating that indicator vectors for classification gave correct assignment in all 11000 test cases. Indicator vector analysis revealed discontinuities corresponding to species- and higher-level taxonomic divisions, suggesting an efficient approach to classification of organisms from poorly-studied groups. As compared to standard distance metrics, indicator vectors preserve diagnostic character probabilities, enable automated classification of test sequences, and generate high-information density single-page displays. These results support application of indicator vectors for comparative analysis of large nucleotide data sets and raise prospect of gaining insight into broad-scale patterns in the genetic structure of biodiversity. PMID:20195371

ARG-based genome-wide analysis of cacao cultivars.

PubMed

Utro, Filippo; Cornejo, Omar Eduardo; Livingstone, Donald; Motamayor, Juan Carlos; Parida, Laxmi

2012-01-01

Ancestral recombinations graph (ARG) is a topological structure that captures the relationship between the extant genomic sequences in terms of genetic events including recombinations. IRiS is a system that estimates the ARG on sequences of individuals, at genomic scales, capturing the relationship between these individuals of the species. Recently, this system was used to estimate the ARG of the recombining X Chromosome of a collection of human populations using relatively dense, bi-allelic SNP data. While the ARG is a natural model for capturing the inter-relationship between a single chromosome of the individuals of a species, it is not immediately apparent how the model can utilize whole-genome (across chromosomes) diploid data. Also, the sheer complexity of an ARG structure presents a challenge to graph visualization techniques. In this paper we examine the ARG reconstruction for (1) genome-wide or multiple chromosomes, (2) multi-allelic and (3) extremely sparse data. To aid in the visualization of the results of the reconstructed ARG, we additionally construct a much simplified topology, a classification tree, suggested by the ARG.As the test case, we study the problem of extracting the relationship between populations of Theobroma cacao. The chocolate tree is an outcrossing species in the wild, due to self-incompatibility mechanisms at play. Thus a principled approach to understanding the inter-relationships between the different populations must take the shuffling of the genomic segments into account. The polymorphisms in the test data are short tandem repeats (STR) and are multi-allelic (sometimes as high as 30 distinct possible values at a locus). Each is at a genomic location that is bilaterally transmitted, hence the ARG is a natural model for this data. Another characteristic of this plant data set is that while it is genome-wide, across 10 linkage groups or chromosomes, it is very sparse, i.e., only 96 loci from a genome of approximately 400 megabases. The results are visualized both as MDS plots and as classification trees. To evaluate the accuracy of the ARG approach, we compare the results with those available in literature. We have extended the ARG model to incorporate genome-wide (ensemble of multiple chromosomes) data in a natural way. We present a simple scheme to implement this in practice. Finally, this is the first time that a plant population data set is being studied by estimating its underlying ARG. We demonstrate an overall precision of 0.92 and an overall recall of 0.93 of the ARG-based classification, with respect to the gold standard. While we have corroborated the classification of the samples with that in literature, this opens the door to other potential studies that can be made on the ARG.

ARG-based genome-wide analysis of cacao cultivars

PubMed Central

2012-01-01

Background Ancestral recombinations graph (ARG) is a topological structure that captures the relationship between the extant genomic sequences in terms of genetic events including recombinations. IRiS is a system that estimates the ARG on sequences of individuals, at genomic scales, capturing the relationship between these individuals of the species. Recently, this system was used to estimate the ARG of the recombining X Chromosome of a collection of human populations using relatively dense, bi-allelic SNP data. Results While the ARG is a natural model for capturing the inter-relationship between a single chromosome of the individuals of a species, it is not immediately apparent how the model can utilize whole-genome (across chromosomes) diploid data. Also, the sheer complexity of an ARG structure presents a challenge to graph visualization techniques. In this paper we examine the ARG reconstruction for (1) genome-wide or multiple chromosomes, (2) multi-allelic and (3) extremely sparse data. To aid in the visualization of the results of the reconstructed ARG, we additionally construct a much simplified topology, a classification tree, suggested by the ARG. As the test case, we study the problem of extracting the relationship between populations of Theobroma cacao. The chocolate tree is an outcrossing species in the wild, due to self-incompatibility mechanisms at play. Thus a principled approach to understanding the inter-relationships between the different populations must take the shuffling of the genomic segments into account. The polymorphisms in the test data are short tandem repeats (STR) and are multi-allelic (sometimes as high as 30 distinct possible values at a locus). Each is at a genomic location that is bilaterally transmitted, hence the ARG is a natural model for this data. Another characteristic of this plant data set is that while it is genome-wide, across 10 linkage groups or chromosomes, it is very sparse, i.e., only 96 loci from a genome of approximately 400 megabases. The results are visualized both as MDS plots and as classification trees. To evaluate the accuracy of the ARG approach, we compare the results with those available in literature. Conclusions We have extended the ARG model to incorporate genome-wide (ensemble of multiple chromosomes) data in a natural way. We present a simple scheme to implement this in practice. Finally, this is the first time that a plant population data set is being studied by estimating its underlying ARG. We demonstrate an overall precision of 0.92 and an overall recall of 0.93 of the ARG-based classification, with respect to the gold standard. While we have corroborated the classification of the samples with that in literature, this opens the door to other potential studies that can be made on the ARG. PMID:23281769

Molecular biology of myopia.

PubMed

Schaeffel, Frank; Simon, Perikles; Feldkaemper, Marita; Ohngemach, Sibylle; Williams, Robert W

2003-09-01

Experiments in animal models of myopia have emphasised the importance of visual input in emmetropisation but it is also evident that the development of human myopia is influenced to some degree by genetic factors. Molecular genetic approaches can help to identify both the genes involved in the control of ocular development and the potential targets for pharmacological intervention. This review covers a variety of techniques that are being used to study the molecular biology of myopia. In the first part, we describe techniques used to analyse visually induced changes in gene expression: Northern Blot, polymerase chain reaction (PCR) and real-time PCR to obtain semi-quantitative and quantitative measures of changes in transcription level of a known gene, differential display reverse transcription PCR (DD-RT-PCR) to search for new genes that are controlled by visual input, rapid amplification of 5' cDNA (5'-RACE) to extend the 5' end of sequences that are regulated by visual input, in situ hybridisation to localise the expression of a given gene in a tissue and oligonucleotide microarray assays to simultaneously test visually induced changes in thousands of transcripts in single experiments. In the second part, we describe techniques that are used to localise regions in the genome that contain genes that are involved in the control of eye growth and refractive errors in mice and humans. These include quantitative trait loci (QTL) mapping, exploiting experimental test crosses of mice and transmission disequilibrium tests (TDT) in humans to find chromosomal intervals that harbour genes involved in myopia development. We review several successful applications of this battery of techniques in myopia research.

An integrated network visualization framework towards metabolic engineering applications.

PubMed

Noronha, Alberto; Vilaça, Paulo; Rocha, Miguel

2014-12-30

Over the last years, several methods for the phenotype simulation of microorganisms, under specified genetic and environmental conditions have been proposed, in the context of Metabolic Engineering (ME). These methods provided insight on the functioning of microbial metabolism and played a key role in the design of genetic modifications that can lead to strains of industrial interest. On the other hand, in the context of Systems Biology research, biological network visualization has reinforced its role as a core tool in understanding biological processes. However, it has been scarcely used to foster ME related methods, in spite of the acknowledged potential. In this work, an open-source software that aims to fill the gap between ME and metabolic network visualization is proposed, in the form of a plugin to the OptFlux ME platform. The framework is based on an abstract layer, where the network is represented as a bipartite graph containing minimal information about the underlying entities and their desired relative placement. The framework provides input/output support for networks specified in standard formats, such as XGMML, SBGN or SBML, providing a connection to genome-scale metabolic models. An user-interface makes it possible to edit, manipulate and query nodes in the network, providing tools to visualize diverse effects, including visual filters and aspect changing (e.g. colors, shapes and sizes). These tools are particularly interesting for ME, since they allow overlaying phenotype simulation results or elementary flux modes over the networks. The framework and its source code are freely available, together with documentation and other resources, being illustrated with well documented case studies.

CRF: detection of CRISPR arrays using random forest.

PubMed

Wang, Kai; Liang, Chun

2017-01-01

CRISPRs (clustered regularly interspaced short palindromic repeats) are particular repeat sequences found in wide range of bacteria and archaea genomes. Several tools are available for detecting CRISPR arrays in the genomes of both domains. Here we developed a new web-based CRISPR detection tool named CRF (CRISPR Finder by Random Forest). Different from other CRISPR detection tools, a random forest classifier was used in CRF to filter out invalid CRISPR arrays from all putative candidates and accordingly enhanced detection accuracy. In CRF, particularly, triplet elements that combine both sequence content and structure information were extracted from CRISPR repeats for classifier training. The classifier achieved high accuracy and sensitivity. Moreover, CRF offers a highly interactive web interface for robust data visualization that is not available among other CRISPR detection tools. After detection, the query sequence, CRISPR array architecture, and the sequences and secondary structures of CRISPR repeats and spacers can be visualized for visual examination and validation. CRF is freely available at http://bioinfolab.miamioh.edu/crf/home.php.

Exploring variation-aware contig graphs for (comparative) metagenomics using MaryGold

PubMed Central

Nijkamp, Jurgen F.; Pop, Mihai; Reinders, Marcel J. T.; de Ridder, Dick

2013-01-01

Motivation: Although many tools are available to study variation and its impact in single genomes, there is a lack of algorithms for finding such variation in metagenomes. This hampers the interpretation of metagenomics sequencing datasets, which are increasingly acquired in research on the (human) microbiome, in environmental studies and in the study of processes in the production of foods and beverages. Existing algorithms often depend on the use of reference genomes, which pose a problem when a metagenome of a priori unknown strain composition is studied. In this article, we develop a method to perform reference-free detection and visual exploration of genomic variation, both within a single metagenome and between metagenomes. Results: We present the MaryGold algorithm and its implementation, which efficiently detects bubble structures in contig graphs using graph decomposition. These bubbles represent variable genomic regions in closely related strains in metagenomic samples. The variation found is presented in a condensed Circos-based visualization, which allows for easy exploration and interpretation of the found variation. We validated the algorithm on two simulated datasets containing three respectively seven Escherichia coli genomes and showed that finding allelic variation in these genomes improves assemblies. Additionally, we applied MaryGold to publicly available real metagenomic datasets, enabling us to find within-sample genomic variation in the metagenomes of a kimchi fermentation process, the microbiome of a premature infant and in microbial communities living on acid mine drainage. Moreover, we used MaryGold for between-sample variation detection and exploration by comparing sequencing data sampled at different time points for both of these datasets. Availability: MaryGold has been written in C++ and Python and can be downloaded from http://bioinformatics.tudelft.nl/software Contact: d.deridder@tudelft.nl PMID:24058058

Genomicus update 2015: KaryoView and MatrixView provide a genome-wide perspective to multispecies comparative genomics

PubMed Central

Louis, Alexandra; Nguyen, Nga Thi Thuy; Muffato, Matthieu; Roest Crollius, Hugues

2015-01-01

The Genomicus web server (http://www.genomicus.biologie.ens.fr/genomicus) is a visualization tool allowing comparative genomics in four different phyla (Vertebrate, Fungi, Metazoan and Plants). It provides access to genomic information from extant species, as well as ancestral gene content and gene order for vertebrates and flowering plants. Here we present the new features available for vertebrate genome with a focus on new graphical tools. The interface to enter the database has been improved, two pairwise genome comparison tools are now available (KaryoView and MatrixView) and the multiple genome comparison tools (PhyloView and AlignView) propose three new kinds of representation and a more intuitive menu. These new developments have been implemented for Genomicus portal dedicated to vertebrates. This allows the analysis of 68 extant animal genomes, as well as 58 ancestral reconstructed genomes. The Genomicus server also provides access to ancestral gene orders, to facilitate evolutionary and comparative genomics studies, as well as computationally predicted regulatory interactions, thanks to the representation of conserved non-coding elements with their putative gene targets. PMID:25378326

Gene context analysis in the Integrated Microbial Genomes (IMG) data management system.

PubMed

Mavromatis, Konstantinos; Chu, Ken; Ivanova, Natalia; Hooper, Sean D; Markowitz, Victor M; Kyrpides, Nikos C

2009-11-24

Computational methods for determining the function of genes in newly sequenced genomes have been traditionally based on sequence similarity to genes whose function has been identified experimentally. Function prediction methods can be extended using gene context analysis approaches such as examining the conservation of chromosomal gene clusters, gene fusion events and co-occurrence profiles across genomes. Context analysis is based on the observation that functionally related genes are often having similar gene context and relies on the identification of such events across phylogenetically diverse collection of genomes. We have used the data management system of the Integrated Microbial Genomes (IMG) as the framework to implement and explore the power of gene context analysis methods because it provides one of the largest available genome integrations. Visualization and search tools to facilitate gene context analysis have been developed and applied across all publicly available archaeal and bacterial genomes in IMG. These computations are now maintained as part of IMG's regular genome content update cycle. IMG is available at: http://img.jgi.doe.gov.

Applications of Genome-based Science in Shaping Citrus Industries of the World (JGI Seventh Annual User Meeting, 2012: Genomics of Energy and Environment)

DOE Office of Scientific and Technical Information (OSTI.GOV)

Gmitter, Jr., Fred; Rokhsar, Dan

Fred Gmitter from the University of Florida on "Applications of Genome-based Science in Shaping the Future of the World's Citrus Industries" at the 7th Annual Genomics of Energy & Environment Meeting on March 21, 2012 in Walnut Creek, California.

Applications of Genome-based Science in Shaping Citrus Industries of the World (JGI Seventh Annual User Meeting, 2012: Genomics of Energy and Environment)

ScienceCinema

Gmitter, Jr., Fred; Rokhsar, Dan

2018-02-16

Fred Gmitter from the University of Florida on "Applications of Genome-based Science in Shaping the Future of the World's Citrus Industries" at the 7th Annual Genomics of Energy & Environment Meeting on March 21, 2012 in Walnut Creek, California.

How should the applications of genome editing be assessed and regulated?

PubMed

Fears, Robin; Ter Meulen, Volker

2017-04-04

An EASAC working group on genome editing recommends that regulators should focus on specific applications of these new techniques rather than attempting to regulate genome editing itself as a new technology.

How and why should we implement genomics into conservation?

PubMed Central

McMahon, Barry J; Teeling, Emma C; Höglund, Jacob

2014-01-01

Conservation genetics has provided important information into the dynamics of endangered populations. The rapid development of genomic methods has posed an important question, namely where do genetics and genomics sit in relation to their application in the conservation of species? Although genetics can answer a number of relevant questions related to conservation, the argument for the application of genomics is not yet fully exploited. Here, we explore the transition and rationale for the move from genetic to genomic research in conservation biology and the utility of such research. We explore the idea of a ‘conservation prior’ and how this can be determined by genomic data and used in the management of populations. We depict three different conservation scenarios and describe how genomic data can drive management action in each situation. We conclude that the most effective applications of genomics will be to inform stakeholders with the aim of avoiding ‘emergency room conservation’. PMID:25553063

Genomics in Public Health: Perspective from the Office of Public Health Genomics at the Centers for Disease Control and Prevention (CDC)

PubMed Central

Fisk Green, Ridgely; Dotson, W. David; Bowen, Scott; Kolor, Katherine; Khoury, Muin J.

2015-01-01

The national effort to use genomic knowledge to save lives is gaining momentum, as illustrated by the inclusion of genomics in key public health initiatives, including Healthy People 2020, and the recent launch of the precision medicine initiative. The Office of Public Health Genomics (OPHG) at the Centers for Disease Control and Prevention (CDC) partners with state public health departments and others to advance the translation of genome-based discoveries into disease prevention and population health. To do this, OPHG has adopted an “identify, inform, and integrate” model: identify evidence-based genomic applications ready for implementation, inform stakeholders about these applications, and integrate these applications into public health at the local, state, and national level. This paper addresses current and future work at OPHG for integrating genomics into public health programs. PMID:26636032

Genomics in Public Health: Perspective from the Office of Public Health Genomics at the Centers for Disease Control and Prevention (CDC).

PubMed

Green, Ridgely Fisk; Dotson, W David; Bowen, Scott; Kolor, Katherine; Khoury, Muin J

2015-01-01

The national effort to use genomic knowledge to save lives is gaining momentum, as illustrated by the inclusion of genomics in key public health initiatives, including Healthy People 2020, and the recent launch of the precision medicine initiative. The Office of Public Health Genomics (OPHG) at the Centers for Disease Control and Prevention (CDC) partners with state public health departments and others to advance the translation of genome-based discoveries into disease prevention and population health. To do this, OPHG has adopted an "identify, inform, and integrate" model: identify evidence-based genomic applications ready for implementation, inform stakeholders about these applications, and integrate these applications into public health at the local, state, and national level. This paper addresses current and future work at OPHG for integrating genomics into public health programs.

MEXPRESS: visualizing expression, DNA methylation and clinical TCGA data.

PubMed

Koch, Alexander; De Meyer, Tim; Jeschke, Jana; Van Criekinge, Wim

2015-08-26

In recent years, increasing amounts of genomic and clinical cancer data have become publically available through large-scale collaborative projects such as The Cancer Genome Atlas (TCGA). However, as long as these datasets are difficult to access and interpret, they are essentially useless for a major part of the research community and their scientific potential will not be fully realized. To address these issues we developed MEXPRESS, a straightforward and easy-to-use web tool for the integration and visualization of the expression, DNA methylation and clinical TCGA data on a single-gene level ( http://mexpress.be ). In comparison to existing tools, MEXPRESS allows researchers to quickly visualize and interpret the different TCGA datasets and their relationships for a single gene, as demonstrated for GSTP1 in prostate adenocarcinoma. We also used MEXPRESS to reveal the differences in the DNA methylation status of the PAM50 marker gene MLPH between the breast cancer subtypes and how these differences were linked to the expression of MPLH. We have created a user-friendly tool for the visualization and interpretation of TCGA data, offering clinical researchers a simple way to evaluate the TCGA data for their genes or candidate biomarkers of interest.

CoCoNUT: an efficient system for the comparison and analysis of genomes

PubMed Central

2008-01-01

Background Comparative genomics is the analysis and comparison of genomes from different species. This area of research is driven by the large number of sequenced genomes and heavily relies on efficient algorithms and software to perform pairwise and multiple genome comparisons. Results Most of the software tools available are tailored for one specific task. In contrast, we have developed a novel system CoCoNUT (Computational Comparative geNomics Utility Toolkit) that allows solving several different tasks in a unified framework: (1) finding regions of high similarity among multiple genomic sequences and aligning them, (2) comparing two draft or multi-chromosomal genomes, (3) locating large segmental duplications in large genomic sequences, and (4) mapping cDNA/EST to genomic sequences. Conclusion CoCoNUT is competitive with other software tools w.r.t. the quality of the results. The use of state of the art algorithms and data structures allows CoCoNUT to solve comparative genomics tasks more efficiently than previous tools. With the improved user interface (including an interactive visualization component), CoCoNUT provides a unified, versatile, and easy-to-use software tool for large scale studies in comparative genomics. PMID:19014477

Graphical genotyping as a method to map Ny (o,n)sto and Gpa5 using a reference panel of tetraploid potato cultivars.

PubMed

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.

Genomic analyses provide insights into the history of tomato breeding.

PubMed

Lin, Tao; Zhu, Guangtao; Zhang, Junhong; Xu, Xiangyang; Yu, Qinghui; Zheng, Zheng; Zhang, Zhonghua; Lun, Yaoyao; Li, Shuai; Wang, Xiaoxuan; Huang, Zejun; Li, Junming; Zhang, Chunzhi; Wang, Taotao; Zhang, Yuyang; Wang, Aoxue; Zhang, Yancong; Lin, Kui; Li, Chuanyou; Xiong, Guosheng; Xue, Yongbiao; Mazzucato, Andrea; Causse, Mathilde; Fei, Zhangjun; Giovannoni, James J; Chetelat, Roger T; Zamir, Dani; Städler, Thomas; Li, Jingfu; Ye, Zhibiao; Du, Yongchen; Huang, Sanwen

2014-11-01

The histories of crop domestication and breeding are recorded in genomes. Although tomato is a model species for plant biology and breeding, the nature of human selection that altered its genome remains largely unknown. Here we report a comprehensive analysis of tomato evolution based on the genome sequences of 360 accessions. We provide evidence that domestication and improvement focused on two independent sets of quantitative trait loci (QTLs), resulting in modern tomato fruit ∼100 times larger than its ancestor. Furthermore, we discovered a major genomic signature for modern processing tomatoes, identified the causative variants that confer pink fruit color and precisely visualized the linkage drag associated with wild introgressions. This study outlines the accomplishments as well as the costs of historical selection and provides molecular insights toward further improvement.

Application of resequencing to rice genomics, functional genomics and evolutionary analysis

PubMed Central

2014-01-01

Rice is a model system used for crop genomics studies. The completion of the rice genome draft sequences in 2002 not only accelerated functional genome studies, but also initiated a new era of resequencing rice genomes. Based on the reference genome in rice, next-generation sequencing (NGS) using the high-throughput sequencing system can efficiently accomplish whole genome resequencing of various genetic populations and diverse germplasm resources. Resequencing technology has been effectively utilized in evolutionary analysis, rice genomics and functional genomics studies. This technique is beneficial for both bridging the knowledge gap between genotype and phenotype and facilitating molecular breeding via gene design in rice. Here, we also discuss the limitation, application and future prospects of rice resequencing. PMID:25006357

The Presence of Norovirus and Adenovirus on Environmental Surfaces in Relation to the Hygienic Level in Food Service Operations Associated with a Suspected Gastroenteritis Outbreak.

PubMed

Maunula, Leena; Rönnqvist, M; Åberg, R; Lunden, J; Nevas, M

2017-09-01

Norovirus (NoV) gastroenteritis outbreaks appear frequently in food service operations (FSOs), such as in restaurants and canteens. In this study the presence of NoV and adenovirus (AdV) genomes was investigated on the surfaces of premises, especially in kitchens, of 30 FSOs where foodborne gastroenteritis outbreaks were suspected. The objective was to establish a possible association between the presence of virus genomes on surfaces and a visual hygienic status of the FSOs. NoV genome was found in 11 and AdV genome in 8 out of 30 FSOs. In total, 291 swabs were taken, of which 8.9% contained NoV and 5.8% AdV genome. The presence of NoV genomes on the surfaces was not found to associate with lower hygiene level of the premises when based on visual inspection; most (7/9) of the FSOs with NoV contamination on surfaces and a completed evaluation form had a good hygiene level (the best category). Restaurants had a significantly lower proportion of NoV-positive swabs compared to other FSOs (canteens, cafeteria, schools etc.) taken together (p = 0.00014). The presence of a designated break room for the workers was found to be significantly more common in AdV-negative kitchens (p = 0.046). Our findings suggest that swabbing is necessary for revealing viral contamination of surfaces and emphasis of hygiene inspections should be on the food handling procedures, and the education of food workers on virus transmission.

Genome Writing: Current Progress and Related Applications.

PubMed

Wang, Yueqiang; Shen, Yue; Gu, Ying; Zhu, Shida; Yin, Ye

2018-02-01

The ultimate goal of synthetic biology is to build customized cells or organisms to meet specific industrial or medical needs. The most important part of the customized cell is a synthetic genome. Advanced genomic writing technologies are required to build such an artificial genome. Recently, the partially-completed synthetic yeast genome project represents a milestone in this field. In this mini review, we briefly introduce the techniques for de novo genome synthesis and genome editing. Furthermore, we summarize recent research progresses and highlight several applications in the synthetic genome field. Finally, we discuss current challenges and future prospects. Copyright © 2018. Production and hosting by Elsevier B.V.

Approaches to Fungal Genome Annotation

PubMed Central

Haas, Brian J.; Zeng, Qiandong; Pearson, Matthew D.; Cuomo, Christina A.; Wortman, Jennifer R.

2011-01-01

Fungal genome annotation is the starting point for analysis of genome content. This generally involves the application of diverse methods to identify features on a genome assembly such as protein-coding and non-coding genes, repeats and transposable elements, and pseudogenes. Here we describe tools and methods leveraged for eukaryotic genome annotation with a focus on the annotation of fungal nuclear and mitochondrial genomes. We highlight the application of the latest technologies and tools to improve the quality of predicted gene sets. The Broad Institute eukaryotic genome annotation pipeline is described as one example of how such methods and tools are integrated into a sequencing center’s production genome annotation environment. PMID:22059117

Featured Article: Genotation: Actionable knowledge for the scientific reader

PubMed Central

Willis, Ethan; Sakauye, Mark; Jose, Rony; Chen, Hao; Davis, Robert L

2016-01-01

We present an article viewer application that allows a scientific reader to easily discover and share knowledge by linking genomics-related concepts to knowledge of disparate biomedical databases. High-throughput data streams generated by technical advancements have contributed to scientific knowledge discovery at an unprecedented rate. Biomedical Informaticists have created a diverse set of databases to store and retrieve the discovered knowledge. The diversity and abundance of such resources present biomedical researchers a challenge with knowledge discovery. These challenges highlight a need for a better informatics solution. We use a text mining algorithm, Genomine, to identify gene symbols from the text of a journal article. The identified symbols are supplemented with information from the GenoDB knowledgebase. Self-updating GenoDB contains information from NCBI Gene, Clinvar, Medgen, dbSNP, KEGG, PharmGKB, Uniprot, and Hugo Gene databases. The journal viewer is a web application accessible via a web browser. The features described herein are accessible on www.genotation.org. The Genomine algorithm identifies gene symbols with an accuracy shown by .65 F-Score. GenoDB currently contains information regarding 59,905 gene symbols, 5633 drug–gene relationships, 5981 gene–disease relationships, and 713 pathways. This application provides scientific readers with actionable knowledge related to concepts of a manuscript. The reader will be able to save and share supplements to be visualized in a graphical manner. This provides convenient access to details of complex biological phenomena, enabling biomedical researchers to generate novel hypothesis to further our knowledge in human health. This manuscript presents a novel application that integrates genomic, proteomic, and pharmacogenomic information to supplement content of a biomedical manuscript and enable readers to automatically discover actionable knowledge. PMID:26900164

Featured Article: Genotation: Actionable knowledge for the scientific reader.

PubMed

Nagahawatte, Panduka; Willis, Ethan; Sakauye, Mark; Jose, Rony; Chen, Hao; Davis, Robert L

2016-06-01

We present an article viewer application that allows a scientific reader to easily discover and share knowledge by linking genomics-related concepts to knowledge of disparate biomedical databases. High-throughput data streams generated by technical advancements have contributed to scientific knowledge discovery at an unprecedented rate. Biomedical Informaticists have created a diverse set of databases to store and retrieve the discovered knowledge. The diversity and abundance of such resources present biomedical researchers a challenge with knowledge discovery. These challenges highlight a need for a better informatics solution. We use a text mining algorithm, Genomine, to identify gene symbols from the text of a journal article. The identified symbols are supplemented with information from the GenoDB knowledgebase. Self-updating GenoDB contains information from NCBI Gene, Clinvar, Medgen, dbSNP, KEGG, PharmGKB, Uniprot, and Hugo Gene databases. The journal viewer is a web application accessible via a web browser. The features described herein are accessible on www.genotation.org The Genomine algorithm identifies gene symbols with an accuracy shown by .65 F-Score. GenoDB currently contains information regarding 59,905 gene symbols, 5633 drug-gene relationships, 5981 gene-disease relationships, and 713 pathways. This application provides scientific readers with actionable knowledge related to concepts of a manuscript. The reader will be able to save and share supplements to be visualized in a graphical manner. This provides convenient access to details of complex biological phenomena, enabling biomedical researchers to generate novel hypothesis to further our knowledge in human health. This manuscript presents a novel application that integrates genomic, proteomic, and pharmacogenomic information to supplement content of a biomedical manuscript and enable readers to automatically discover actionable knowledge. © 2016 by the Society for Experimental Biology and Medicine.

Update on Genomic Databases and Resources at the National Center for Biotechnology Information.

PubMed

Tatusova, Tatiana

2016-01-01

The National Center for Biotechnology Information (NCBI), as a primary public repository of genomic sequence data, collects and maintains enormous amounts of heterogeneous data. Data for genomes, genes, gene expressions, gene variation, gene families, proteins, and protein domains are integrated with the analytical, search, and retrieval resources through the NCBI website, text-based search and retrieval system, provides a fast and easy way to navigate across diverse biological databases.Comparative genome analysis tools lead to further understanding of evolution processes quickening the pace of discovery. Recent technological innovations have ignited an explosion in genome sequencing that has fundamentally changed our understanding of the biology of living organisms. This huge increase in DNA sequence data presents new challenges for the information management system and the visualization tools. New strategies have been designed to bring an order to this genome sequence shockwave and improve the usability of associated data.

Viral Infection at High Magnification: 3D Electron Microscopy Methods to Analyze the Architecture of Infected Cells

PubMed Central

Romero-Brey, Inés; Bartenschlager, Ralf

2015-01-01

As obligate intracellular parasites, viruses need to hijack their cellular hosts and reprogram their machineries in order to replicate their genomes and produce new virions. For the direct visualization of the different steps of a viral life cycle (attachment, entry, replication, assembly and egress) electron microscopy (EM) methods are extremely helpful. While conventional EM has given important information about virus-host cell interactions, the development of three-dimensional EM (3D-EM) approaches provides unprecedented insights into how viruses remodel the intracellular architecture of the host cell. During the last years several 3D-EM methods have been developed. Here we will provide a description of the main approaches and examples of innovative applications. PMID:26633469

Viral Infection at High Magnification: 3D Electron Microscopy Methods to Analyze the Architecture of Infected Cells.

PubMed

Romero-Brey, Inés; Bartenschlager, Ralf

2015-12-03

As obligate intracellular parasites, viruses need to hijack their cellular hosts and reprogram their machineries in order to replicate their genomes and produce new virions. For the direct visualization of the different steps of a viral life cycle (attachment, entry, replication, assembly and egress) electron microscopy (EM) methods are extremely helpful. While conventional EM has given important information about virus-host cell interactions, the development of three-dimensional EM (3D-EM) approaches provides unprecedented insights into how viruses remodel the intracellular architecture of the host cell. During the last years several 3D-EM methods have been developed. Here we will provide a description of the main approaches and examples of innovative applications.

HYBRIDCHECK: software for the rapid detection, visualization and dating of recombinant regions in genome sequence data.

PubMed

Ward, Ben J; van Oosterhout, Cock

2016-03-01

HYBRIDCHECK is a software package to visualize the recombination signal in large DNA sequence data set, and it can be used to analyse recombination, genetic introgression, hybridization and horizontal gene transfer. It can scan large (multiple kb) contigs and whole-genome sequences of three or more individuals. HYBRIDCHECK is written in the r software for OS X, Linux and Windows operating systems, and it has a simple graphical user interface. In addition, the r code can be readily incorporated in scripts and analysis pipelines. HYBRIDCHECK implements several ABBA-BABA tests and visualizes the effects of hybridization and the resulting mosaic-like genome structure in high-density graphics. The package also reports the following: (i) the breakpoint positions, (ii) the number of mutations in each introgressed block, (iii) the probability that the identified region is not caused by recombination and (iv) the estimated age of each recombination event. The divergence times between the donor and recombinant sequence are calculated using a JC, K80, F81, HKY or GTR correction, and the dating algorithm is exceedingly fast. By estimating the coalescence time of introgressed blocks, it is possible to distinguish between hybridization and incomplete lineage sorting. HYBRIDCHECK is libré software and it and its manual are free to download from http://ward9250.github.io/HybridCheck/. © 2015 John Wiley & Sons Ltd.

Interactive visual exploration and refinement of cluster assignments.

PubMed

Kern, Michael; Lex, Alexander; Gehlenborg, Nils; Johnson, Chris R

2017-09-12

With ever-increasing amounts of data produced in biology research, scientists are in need of efficient data analysis methods. Cluster analysis, combined with visualization of the results, is one such method that can be used to make sense of large data volumes. At the same time, cluster analysis is known to be imperfect and depends on the choice of algorithms, parameters, and distance measures. Most clustering algorithms don't properly account for ambiguity in the source data, as records are often assigned to discrete clusters, even if an assignment is unclear. While there are metrics and visualization techniques that allow analysts to compare clusterings or to judge cluster quality, there is no comprehensive method that allows analysts to evaluate, compare, and refine cluster assignments based on the source data, derived scores, and contextual data. In this paper, we introduce a method that explicitly visualizes the quality of cluster assignments, allows comparisons of clustering results and enables analysts to manually curate and refine cluster assignments. Our methods are applicable to matrix data clustered with partitional, hierarchical, and fuzzy clustering algorithms. Furthermore, we enable analysts to explore clustering results in context of other data, for example, to observe whether a clustering of genomic data results in a meaningful differentiation in phenotypes. Our methods are integrated into Caleydo StratomeX, a popular, web-based, disease subtype analysis tool. We show in a usage scenario that our approach can reveal ambiguities in cluster assignments and produce improved clusterings that better differentiate genotypes and phenotypes.

The UCSC Genome Browser database: extensions and updates 2013.

PubMed

Meyer, Laurence R; Zweig, Ann S; Hinrichs, Angie S; Karolchik, Donna; Kuhn, Robert M; Wong, Matthew; Sloan, Cricket A; Rosenbloom, Kate R; Roe, Greg; Rhead, Brooke; Raney, Brian J; Pohl, Andy; Malladi, Venkat S; Li, Chin H; Lee, Brian T; Learned, Katrina; Kirkup, Vanessa; Hsu, Fan; Heitner, Steve; Harte, Rachel A; Haeussler, Maximilian; Guruvadoo, Luvina; Goldman, Mary; Giardine, Belinda M; Fujita, Pauline A; Dreszer, Timothy R; Diekhans, Mark; Cline, Melissa S; Clawson, Hiram; Barber, Galt P; Haussler, David; Kent, W James

2013-01-01

The University of California Santa Cruz (UCSC) Genome Browser (http://genome.ucsc.edu) offers online public access to a growing database of genomic sequence and annotations for a wide variety of organisms. The Browser is an integrated tool set for visualizing, comparing, analysing and sharing both publicly available and user-generated genomic datasets. As of September 2012, genomic sequence and a basic set of annotation 'tracks' are provided for 63 organisms, including 26 mammals, 13 non-mammal vertebrates, 3 invertebrate deuterostomes, 13 insects, 6 worms, yeast and sea hare. In the past year 19 new genome assemblies have been added, and we anticipate releasing another 28 in early 2013. Further, a large number of annotation tracks have been either added, updated by contributors or remapped to the latest human reference genome. Among these are an updated UCSC Genes track for human and mouse assemblies. We have also introduced several features to improve usability, including new navigation menus. This article provides an update to the UCSC Genome Browser database, which has been previously featured in the Database issue of this journal.

Visual Tracking of Plant Virus Infection and Movement Using a Reporter MYB Transcription Factor That Activates Anthocyanin Biosynthesis1[W

PubMed Central

Bedoya, Leonor C.; Martínez, Fernando; Orzáez, Diego; Daròs, José-Antonio

2012-01-01

Insertion of reporter genes into plant virus genomes is a common experimental strategy to research many aspects of the viral infection dynamics. Their numerous advantages make fluorescent proteins the markers of choice in most studies. However, the use of fluorescent proteins still has some limitations, such as the need of specialized material and facilities to detect the fluorescence. Here, we demonstrate a visual reporter marker system to track virus infection and movement through the plant. The reporter system is based on expression of Antirrhinum majus MYB-related Rosea1 (Ros1) transcription factor (220 amino acids; 25.7 kD) that activates a series of biosynthetic genes leading to accumulation of colored anthocyanins. Using two different tobacco etch potyvirus recombinant clones tagged with Ros1, we show that infected tobacco (Nicotiana tabacum) tissues turn bright red, demonstrating that in this context, the sole expression of Ros1 is sufficient to induce pigment accumulation to a level readily detectable to the naked eye. This marker system also reports viral load qualitatively and quantitatively by means of a very simple extraction process. The Ros1 marker remained stable within the potyvirus genome through successive infectious passages from plant to plant. The main limitation of this marker system is that color output will depend on each particular plant host-virus combination and must be previously tested. However, our experiments demonstrate accurate tracking of turnip mosaic potyvirus infecting Arabidopsis (Arabidopsis thaliana) and either tobacco mosaic virus or potato X virus infecting Nicotiana benthamiana, stressing the general applicability of the method. PMID:22238422

CisSERS: Customizable in silico sequence evaluation for restriction sites

DOE PAGES

Sharpe, Richard M.; Koepke, Tyson; Harper, Artemus; ...

2016-04-12

High-throughput sequencing continues to produce an immense volume of information that is processed and assembled into mature sequence data. Here, data analysis tools are urgently needed that leverage the embedded DNA sequence polymorphisms and consequent changes to restriction sites or sequence motifs in a high-throughput manner to enable biological experimentation. CisSERS was developed as a standalone open source tool to analyze sequence datasets and provide biologists with individual or comparative genome organization information in terms of presence and frequency of patterns or motifs such as restriction enzymes. Predicted agarose gel visualization of the custom analyses results was also integrated tomore » enhance the usefulness of the software. CisSERS offers several novel functionalities, such as handling of large and multiple datasets in parallel, multiple restriction enzyme site detection and custom motif detection features, which are seamlessly integrated with real time agarose gel visualization. Using a simple fasta-formatted file as input, CisSERS utilizes the REBASE enzyme database. Results from CisSERSenable the user to make decisions for designing genotyping by sequencing experiments, reduced representation sequencing, 3’UTR sequencing, and cleaved amplified polymorphic sequence (CAPS) molecular markers for large sample sets. CisSERS is a java based graphical user interface built around a perl backbone. Several of the applications of CisSERS including CAPS molecular marker development were successfully validated using wet-lab experimentation. Here, we present the tool CisSERSand results from in-silico and corresponding wet-lab analyses demonstrating that CisSERS is a technology platform solution that facilitates efficient data utilization in genomics and genetics studies.« less

CisSERS: Customizable in silico sequence evaluation for restriction sites

DOE Office of Scientific and Technical Information (OSTI.GOV)

Sharpe, Richard M.; Koepke, Tyson; Harper, Artemus

High-throughput sequencing continues to produce an immense volume of information that is processed and assembled into mature sequence data. Here, data analysis tools are urgently needed that leverage the embedded DNA sequence polymorphisms and consequent changes to restriction sites or sequence motifs in a high-throughput manner to enable biological experimentation. CisSERS was developed as a standalone open source tool to analyze sequence datasets and provide biologists with individual or comparative genome organization information in terms of presence and frequency of patterns or motifs such as restriction enzymes. Predicted agarose gel visualization of the custom analyses results was also integrated tomore » enhance the usefulness of the software. CisSERS offers several novel functionalities, such as handling of large and multiple datasets in parallel, multiple restriction enzyme site detection and custom motif detection features, which are seamlessly integrated with real time agarose gel visualization. Using a simple fasta-formatted file as input, CisSERS utilizes the REBASE enzyme database. Results from CisSERSenable the user to make decisions for designing genotyping by sequencing experiments, reduced representation sequencing, 3’UTR sequencing, and cleaved amplified polymorphic sequence (CAPS) molecular markers for large sample sets. CisSERS is a java based graphical user interface built around a perl backbone. Several of the applications of CisSERS including CAPS molecular marker development were successfully validated using wet-lab experimentation. Here, we present the tool CisSERSand results from in-silico and corresponding wet-lab analyses demonstrating that CisSERS is a technology platform solution that facilitates efficient data utilization in genomics and genetics studies.« less

Genome constraint through sexual reproduction: application of 4D-Genomics in reproductive biology.

PubMed

Horne, Steven D; Abdallah, Batoul Y; Stevens, Joshua B; Liu, Guo; Ye, Karen J; Bremer, Steven W; Heng, Henry H Q

2013-06-01

Assisted reproductive technologies have been used to achieve pregnancies since the first successful test tube baby was born in 1978. Infertile couples are at an increased risk for multiple miscarriages and the application of current protocols are associated with high first-trimester miscarriage rates. Among the contributing factors of these higher rates is a high incidence of fetal aneuploidy. Numerous studies support that protocols including ovulation-induction, sperm cryostorage, density-gradient centrifugation, and embryo culture can induce genome instability, but the general mechanism is less clear. Application of the genome theory and 4D-Genomics recently led to the establishment of a new paradigm for sexual reproduction; sex primarily constrains genome integrity that defines the biological system rather than just providing genetic diversity at the gene level. We therefore propose that application of assisted reproductive technologies can bypass this sexual reproduction filter as well as potentially induce additional system instability. We have previously demonstrated that a single-cell resolution genomic approach, such as spectral karyotyping to trace stochastic genome level alterations, is effective for pre- and post-natal analysis. We propose that monitoring overall genome alteration at the karyotype level alongside the application of assisted reproductive technologies will improve the efficacy of the techniques while limiting stress-induced genome instability. The development of more single-cell based cytogenomic technologies are needed in order to better understand the system dynamics associated with infertility and the potential impact that assisted reproductive technologies have on genome instability. Importantly, this approach will be useful in studying the potential for diseases to arise as a result of bypassing the filter of sexual reproduction.

Development of DNAzyme-based PCR signal cascade amplification for visual detection of Listeria monocytogenes in food.

PubMed

Liu, Zhanmin; Yao, Chenhui; Yang, Cuiyun; Wang, Yanming; Wan, Sibao; Huang, Junyi

2018-05-16

Listeria monocytogenes is an important foodborne pathogen, and it can cause severe diseases. Rapid detection of L. monocytogenes is crucial to control this pathogen. A simple and robust strategy based on the cascade of PCR and G-quadruplex DNAzyme catalyzed reaction was used to detect L. monocytogenes. In the presence of hemin and the aptamer formed during PCR, the catalytic horseradish peroxidase-mimicking G-quadruplex DNAzymes allow the colorimetric responses of target DNA from L. monocytogenes. This assay can detect genomic DNA of L. monocytogenes specifically with as low as 50 pg/reaction with the naked eye. Through 20 pork samples assay, visual detection assay had the same results as conventional detection methods, and had a good performance. This is a powerful demonstration of the ability of G-quadruplex DNAzyme to be used for PCR-based assay with significant advantages of high sensitivity, low cost and simple manipulation over existing approaches and offers the opportunity for application in pathogen detection. Copyright © 2018 Elsevier Inc. All rights reserved.

Groups: knowledge spreadsheets for symbolic biocomputing.

PubMed

Travers, Michael; Paley, Suzanne M; Shrager, Jeff; Holland, Timothy A; Karp, Peter D

2013-01-01

Knowledge spreadsheets (KSs) are a visual tool for interactive data analysis and exploration. They differ from traditional spreadsheets in that rather than being oriented toward numeric data, they work with symbolic knowledge representation structures and provide operations that take into account the semantics of the application domain. 'Groups' is an implementation of KSs within the Pathway Tools system. Groups allows Pathway Tools users to define a group of objects (e.g. groups of genes or metabolites) from a Pathway/Genome Database. Groups can be transformed (e.g. by transforming a metabolite group to the group of pathways in which those metabolites are substrates); combined through set operations; analysed (e.g. through enrichment analysis); and visualized (e.g. by painting onto a metabolic map diagram). Users of the Pathway Tools-based BioCyc.org website have made extensive use of Groups, and an informal survey of Groups users suggests that Groups has achieved the goal of allowing biologists themselves to perform some data manipulations that previously would have required the assistance of a programmer. Database URL: BioCyc.org.

High-throughput physical mapping of chromosomes using automated in situ hybridization.

PubMed

George, Phillip; Sharakhova, Maria V; Sharakhov, Igor V

2012-06-28

Projects to obtain whole-genome sequences for 10,000 vertebrate species and for 5,000 insect and related arthropod species are expected to take place over the next 5 years. For example, the sequencing of the genomes for 15 malaria mosquitospecies is currently being done using an Illumina platform. This Anopheles species cluster includes both vectors and non-vectors of malaria. When the genome assemblies become available, researchers will have the unique opportunity to perform comparative analysis for inferring evolutionary changes relevant to vector ability. However, it has proven difficult to use next-generation sequencing reads to generate high-quality de novo genome assemblies. Moreover, the existing genome assemblies for Anopheles gambiae, although obtained using the Sanger method, are gapped or fragmented. Success of comparative genomic analyses will be limited if researchers deal with numerous sequencing contigs, rather than with chromosome-based genome assemblies. Fragmented, unmapped sequences create problems for genomic analyses because: (i) unidentified gaps cause incorrect or incomplete annotation of genomic sequences; (ii) unmapped sequences lead to confusion between paralogous genes and genes from different haplotypes; and (iii) the lack of chromosome assignment and orientation of the sequencing contigs does not allow for reconstructing rearrangement phylogeny and studying chromosome evolution. Developing high-resolution physical maps for species with newly sequenced genomes is a timely and cost-effective investment that will facilitate genome annotation, evolutionary analysis, and re-sequencing of individual genomes from natural populations. Here, we present innovative approaches to chromosome preparation, fluorescent in situ hybridization (FISH), and imaging that facilitate rapid development of physical maps. Using An. gambiae as an example, we demonstrate that the development of physical chromosome maps can potentially improve genome assemblies and, thus, the quality of genomic analyses. First, we use a high-pressure method to prepare polytene chromosome spreads. This method, originally developed for Drosophila, allows the user to visualize more details on chromosomes than the regular squashing technique. Second, a fully automated, front-end system for FISH is used for high-throughput physical genome mapping. The automated slide staining system runs multiple assays simultaneously and dramatically reduces hands-on time. Third, an automatic fluorescent imaging system, which includes a motorized slide stage, automatically scans and photographs labeled chromosomes after FISH. This system is especially useful for identifying and visualizing multiple chromosomal plates on the same slide. In addition, the scanning process captures a more uniform FISH result. Overall, the automated high-throughput physical mapping protocol is more efficient than a standard manual protocol.

Enhancing knowledge discovery from cancer genomics data with Galaxy

PubMed Central

Albuquerque, Marco A.; Grande, Bruno M.; Ritch, Elie J.; Pararajalingam, Prasath; Jessa, Selin; Krzywinski, Martin; Grewal, Jasleen K.; Shah, Sohrab P.; Boutros, Paul C.

2017-01-01

Abstract The field of cancer genomics has demonstrated the power of massively parallel sequencing techniques to inform on the genes and specific alterations that drive tumor onset and progression. Although large comprehensive sequence data sets continue to be made increasingly available, data analysis remains an ongoing challenge, particularly for laboratories lacking dedicated resources and bioinformatics expertise. To address this, we have produced a collection of Galaxy tools that represent many popular algorithms for detecting somatic genetic alterations from cancer genome and exome data. We developed new methods for parallelization of these tools within Galaxy to accelerate runtime and have demonstrated their usability and summarized their runtimes on multiple cloud service providers. Some tools represent extensions or refinement of existing toolkits to yield visualizations suited to cohort-wide cancer genomic analysis. For example, we present Oncocircos and Oncoprintplus, which generate data-rich summaries of exome-derived somatic mutation. Workflows that integrate these to achieve data integration and visualizations are demonstrated on a cohort of 96 diffuse large B-cell lymphomas and enabled the discovery of multiple candidate lymphoma-related genes. Our toolkit is available from our GitHub repository as Galaxy tool and dependency definitions and has been deployed using virtualization on multiple platforms including Docker. PMID:28327945

Enhancing knowledge discovery from cancer genomics data with Galaxy.

PubMed

Albuquerque, Marco A; Grande, Bruno M; Ritch, Elie J; Pararajalingam, Prasath; Jessa, Selin; Krzywinski, Martin; Grewal, Jasleen K; Shah, Sohrab P; Boutros, Paul C; Morin, Ryan D

2017-05-01

The field of cancer genomics has demonstrated the power of massively parallel sequencing techniques to inform on the genes and specific alterations that drive tumor onset and progression. Although large comprehensive sequence data sets continue to be made increasingly available, data analysis remains an ongoing challenge, particularly for laboratories lacking dedicated resources and bioinformatics expertise. To address this, we have produced a collection of Galaxy tools that represent many popular algorithms for detecting somatic genetic alterations from cancer genome and exome data. We developed new methods for parallelization of these tools within Galaxy to accelerate runtime and have demonstrated their usability and summarized their runtimes on multiple cloud service providers. Some tools represent extensions or refinement of existing toolkits to yield visualizations suited to cohort-wide cancer genomic analysis. For example, we present Oncocircos and Oncoprintplus, which generate data-rich summaries of exome-derived somatic mutation. Workflows that integrate these to achieve data integration and visualizations are demonstrated on a cohort of 96 diffuse large B-cell lymphomas and enabled the discovery of multiple candidate lymphoma-related genes. Our toolkit is available from our GitHub repository as Galaxy tool and dependency definitions and has been deployed using virtualization on multiple platforms including Docker. © The Author 2017. Published by Oxford University Press.

Comparison of Burrows-Wheeler transform-based mapping algorithms used in high-throughput whole-genome sequencing: application to Illumina data for livestock genomes

USDA-ARS?s Scientific Manuscript database

Ongoing developments and cost decreases in next-generation sequencing (NGS) technologies have led to an increase in their application, which has greatly enhanced the fields of genetics and genomics. Mapping sequence reads onto a reference genome is a fundamental step in the analysis of NGS data. Eff...

The next generation of melanocyte data: Genetic, epigenetic, and transcriptional resource datasets and analysis tools.

PubMed

Loftus, Stacie K

2018-05-01

The number of melanocyte- and melanoma-derived next generation sequence genome-scale datasets have rapidly expanded over the past several years. This resource guide provides a summary of publicly available sources of melanocyte cell derived whole genome, exome, mRNA and miRNA transcriptome, chromatin accessibility and epigenetic datasets. Also highlighted are bioinformatic resources and tools for visualization and data queries which allow researchers a genome-scale view of the melanocyte. Published 2018. This article is a U.S. Government work and is in the public domain in the USA.

Genome dynamics of the human embryonic kidney 293 lineage in response to cell biology manipulations.

PubMed

Lin, Yao-Cheng; Boone, Morgane; Meuris, Leander; Lemmens, Irma; Van Roy, Nadine; Soete, Arne; Reumers, Joke; Moisse, Matthieu; Plaisance, Stéphane; Drmanac, Radoje; Chen, Jason; Speleman, Frank; Lambrechts, Diether; Van de Peer, Yves; Tavernier, Jan; Callewaert, Nico

2014-09-03

The HEK293 human cell lineage is widely used in cell biology and biotechnology. Here we use whole-genome resequencing of six 293 cell lines to study the dynamics of this aneuploid genome in response to the manipulations used to generate common 293 cell derivatives, such as transformation and stable clone generation (293T); suspension growth adaptation (293S); and cytotoxic lectin selection (293SG). Remarkably, we observe that copy number alteration detection could identify the genomic region that enabled cell survival under selective conditions (i.c. ricin selection). Furthermore, we present methods to detect human/vector genome breakpoints and a user-friendly visualization tool for the 293 genome data. We also establish that the genome structure composition is in steady state for most of these cell lines when standard cell culturing conditions are used. This resource enables novel and more informed studies with 293 cells, and we will distribute the sequenced cell lines to this effect.

The topography of mutational processes in breast cancer genomes

DOE PAGES

Morganella, Sandro; Alexandrov, Ludmil B.; Glodzik, Dominik; ...

2016-01-01

Somatic mutations in human cancers show unevenness in genomic distribution that correlate with aspects of genome structure and function. These mutations are, however, generated by multiple mutational processes operating through the cellular lineage between the fertilized egg and the cancer cell, each composed of specific DNA damage and repair components and leaving its own characteristic mutational signature on the genome. Using somatic mutation catalogues from 560 breast cancer whole-genome sequences, here we show that each of 12 base substitution, 2 insertion/deletion (indel) and 6 rearrangement mutational signatures present in breast tissue, exhibit distinct relationships with genomic features relating to transcription,more » DNA replication and chromatin organization. This signature-based approach permits visualization of the genomic distribution of mutational processes associated with APOBEC enzymes, mismatch repair deficiency and homologous recombinational repair deficiency, as well as mutational processes of unknown aetiology. Lastly, it highlights mechanistic insights including a putative replication-dependent mechanism of APOBEC-related mutagenesis.« less

UCSC genome browser: deep support for molecular biomedical research.

PubMed

Mangan, Mary E; Williams, Jennifer M; Lathe, Scott M; Karolchik, Donna; Lathe, Warren C

2008-01-01

The volume and complexity of genomic sequence data, and the additional experimental data required for annotation of the genomic context, pose a major challenge for display and access for biomedical researchers. Genome browsers organize this data and make it available in various ways to extract useful information to advance research projects. The UCSC Genome Browser is one of these resources. The official sequence data for a given species forms the framework to display many other types of data such as expression, variation, cross-species comparisons, and more. Visual representations of the data are available for exploration. Data can be queried with sequences. Complex database queries are also easily achieved with the Table Browser interface. Associated tools permit additional query types or access to additional data sources such as images of in situ localizations. Support for solving researcher's issues is provided with active discussion mailing lists and by providing updated training materials. The UCSC Genome Browser provides a source of deep support for a wide range of biomedical molecular research (http://genome.ucsc.edu).

A Simple Method for Visualization of Locus-Specific H4K20me1 Modifications in Living Caenorhabditis elegans Single Cells.

PubMed

Shinkai, Yoichi; Kuramochi, Masahiro; Doi, Motomichi

2018-05-03

Recently, advances in next-generation sequencing technologies have enabled genome-wide analyses of epigenetic modifications; however, it remains difficult to analyze the states of histone modifications at a single-cell resolution in living multicellular organisms because of the heterogeneity within cellular populations. Here we describe a simple method to visualize histone modifications on the specific sequence of target locus at a single-cell resolution in living Caenorhabditis elegans , by combining the LacO/LacI system and a genetically-encoded H4K20me1-specific probe, "mintbody". We demonstrate that Venus-labeled mintbody and mTurquoise2-labeled LacI can co-localize on an artificial chromosome carrying both the target locus and LacO sequences, where H4K20me1 marks the target locus. We demonstrate that our visualization method can precisely detect H4K20me1 depositions on the her-1 gene sequences on the artificial chromosome, to which the dosage compensation complex binds to regulate sex determination. The degree of H4K20me1 deposition on the her-1 sequences on the artificial chromosome correlated strongly with sex, suggesting that, using the artificial chromosome, this method can reflect context-dependent changes of H4K20me1 on endogenous genomes. Furthermore, we demonstrate live imaging of H4K20me1 depositions on the artificial chromosome. Combined with ChIP assays, this mintbody-LacO/LacI visualization method will enable analysis of developmental and context-dependent alterations of locus-specific histone modifications in specific cells and elucidation of the underlying molecular mechanisms. Copyright © 2018, G3: Genes, Genomes, Genetics.

A Drosophila Toolkit for the Visualization and Quantification of Viral Replication Launched from Transgenic Genomes

PubMed Central

Wernet, Mathias F.; Klovstad, Martha; Clandinin, Thomas R.

2014-01-01

Arthropod RNA viruses pose a serious threat to human health, yet many aspects of their replication cycle remain incompletely understood. Here we describe a versatile Drosophila toolkit of transgenic, self-replicating genomes (‘replicons’) from Sindbis virus that allow rapid visualization and quantification of viral replication in vivo. We generated replicons expressing Luciferase for the quantification of viral replication, serving as useful new tools for large-scale genetic screens for identifying cellular pathways that influence viral replication. We also present a new binary system in which replication-deficient viral genomes can be activated ‘in trans’, through co-expression of an intact replicon contributing an RNA-dependent RNA polymerase. The utility of this toolkit for studying virus biology is demonstrated by the observation of stochastic exclusion between replicons expressing different fluorescent proteins, when co-expressed under control of the same cellular promoter. This process is analogous to ‘superinfection exclusion’ between virus particles in cell culture, a process that is incompletely understood. We show that viral polymerases strongly prefer to replicate the genome that encoded them, and that almost invariably only a single virus genome is stochastically chosen for replication in each cell. Our in vivo system now makes this process amenable to detailed genetic dissection. Thus, this toolkit allows the cell-type specific, quantitative study of viral replication in a genetic model organism, opening new avenues for molecular, genetic and pharmacological dissection of virus biology and tool development. PMID:25386852

PGG.Population: a database for understanding the genomic diversity and genetic ancestry of human populations.

PubMed

Zhang, Chao; Gao, Yang; Liu, Jiaojiao; Xue, Zhe; Lu, Yan; Deng, Lian; Tian, Lei; Feng, Qidi; Xu, Shuhua

2018-01-04

There are a growing number of studies focusing on delineating genetic variations that are associated with complex human traits and diseases due to recent advances in next-generation sequencing technologies. However, identifying and prioritizing disease-associated causal variants relies on understanding the distribution of genetic variations within and among populations. The PGG.Population database documents 7122 genomes representing 356 global populations from 107 countries and provides essential information for researchers to understand human genomic diversity and genetic ancestry. These data and information can facilitate the design of research studies and the interpretation of results of both evolutionary and medical studies involving human populations. The database is carefully maintained and constantly updated when new data are available. We included miscellaneous functions and a user-friendly graphical interface for visualization of genomic diversity, population relationships (genetic affinity), ancestral makeup, footprints of natural selection, and population history etc. Moreover, PGG.Population provides a useful feature for users to analyze data and visualize results in a dynamic style via online illustration. The long-term ambition of the PGG.Population, together with the joint efforts from other researchers who contribute their data to our database, is to create a comprehensive depository of geographic and ethnic variation of human genome, as well as a platform bringing influence on future practitioners of medicine and clinical investigators. PGG.Population is available at https://www.pggpopulation.org. © The Author(s) 2017. Published by Oxford University Press on behalf of Nucleic Acids Research.

Apollo2Go: a web service adapter for the Apollo genome viewer to enable distributed genome annotation.

PubMed

Klee, Kathrin; Ernst, Rebecca; Spannagl, Manuel; Mayer, Klaus F X

2007-08-30

Apollo, a genome annotation viewer and editor, has become a widely used genome annotation and visualization tool for distributed genome annotation projects. When using Apollo for annotation, database updates are carried out by uploading intermediate annotation files into the respective database. This non-direct database upload is laborious and evokes problems of data synchronicity. To overcome these limitations we extended the Apollo data adapter with a generic, configurable web service client that is able to retrieve annotation data in a GAME-XML-formatted string and pass it on to Apollo's internal input routine. This Apollo web service adapter, Apollo2Go, simplifies the data exchange in distributed projects and aims to render the annotation process more comfortable. The Apollo2Go software is freely available from ftp://ftpmips.gsf.de/plants/apollo_webservice.

Apollo2Go: a web service adapter for the Apollo genome viewer to enable distributed genome annotation

PubMed Central

Klee, Kathrin; Ernst, Rebecca; Spannagl, Manuel; Mayer, Klaus FX

2007-01-01

Background Apollo, a genome annotation viewer and editor, has become a widely used genome annotation and visualization tool for distributed genome annotation projects. When using Apollo for annotation, database updates are carried out by uploading intermediate annotation files into the respective database. This non-direct database upload is laborious and evokes problems of data synchronicity. Results To overcome these limitations we extended the Apollo data adapter with a generic, configurable web service client that is able to retrieve annotation data in a GAME-XML-formatted string and pass it on to Apollo's internal input routine. Conclusion This Apollo web service adapter, Apollo2Go, simplifies the data exchange in distributed projects and aims to render the annotation process more comfortable. The Apollo2Go software is freely available from . PMID:17760972

The RAVEN Toolbox and Its Use for Generating a Genome-scale Metabolic Model for Penicillium chrysogenum

PubMed Central

Agren, Rasmus; Liu, Liming; Shoaie, Saeed; Vongsangnak, Wanwipa; Nookaew, Intawat; Nielsen, Jens

2013-01-01

We present the RAVEN (Reconstruction, Analysis and Visualization of Metabolic Networks) Toolbox: a software suite that allows for semi-automated reconstruction of genome-scale models. It makes use of published models and/or the KEGG database, coupled with extensive gap-filling and quality control features. The software suite also contains methods for visualizing simulation results and omics data, as well as a range of methods for performing simulations and analyzing the results. The software is a useful tool for system-wide data analysis in a metabolic context and for streamlined reconstruction of metabolic networks based on protein homology. The RAVEN Toolbox workflow was applied in order to reconstruct a genome-scale metabolic model for the important microbial cell factory Penicillium chrysogenum Wisconsin54-1255. The model was validated in a bibliomic study of in total 440 references, and it comprises 1471 unique biochemical reactions and 1006 ORFs. It was then used to study the roles of ATP and NADPH in the biosynthesis of penicillin, and to identify potential metabolic engineering targets for maximization of penicillin production. PMID:23555215

SEURAT: Visual analytics for the integrated analysis of microarray data

PubMed Central

2010-01-01

Background In translational cancer research, gene expression data is collected together with clinical data and genomic data arising from other chip based high throughput technologies. Software tools for the joint analysis of such high dimensional data sets together with clinical data are required. Results We have developed an open source software tool which provides interactive visualization capability for the integrated analysis of high-dimensional gene expression data together with associated clinical data, array CGH data and SNP array data. The different data types are organized by a comprehensive data manager. Interactive tools are provided for all graphics: heatmaps, dendrograms, barcharts, histograms, eventcharts and a chromosome browser, which displays genetic variations along the genome. All graphics are dynamic and fully linked so that any object selected in a graphic will be highlighted in all other graphics. For exploratory data analysis the software provides unsupervised data analytics like clustering, seriation algorithms and biclustering algorithms. Conclusions The SEURAT software meets the growing needs of researchers to perform joint analysis of gene expression, genomical and clinical data. PMID:20525257

An integrative model for in-silico clinical-genomics discovery science.

PubMed

Lussier, Yves A; Sarkar, Indra Nell; Cantor, Michael

2002-01-01

Human Genome discovery research has set the pace for Post-Genomic Discovery Research. While post-genomic fields focused at the molecular level are intensively pursued, little effort is being deployed in the later stages of molecular medicine discovery research, such as clinical-genomics. The objective of this study is to demonstrate the relevance and significance of integrating mainstream clinical informatics decision support systems to current bioinformatics genomic discovery science. This paper is a feasibility study of an original model enabling novel "in-silico" clinical-genomic discovery science and that demonstrates its feasibility. This model is designed to mediate queries among clinical and genomic knowledge bases with relevant bioinformatic analytic tools (e.g. gene clustering). Briefly, trait-disease-gene relationships were successfully illustrated using QMR, OMIM, SNOMED-RT, GeneCluster and TreeView. The analyses were visualized as two-dimensional dendrograms of clinical observations clustered around genes. To our knowledge, this is the first study using knowledge bases of clinical decision support systems for genomic discovery. Although this study is a proof of principle, it provides a framework for the development of clinical decision-support-system driven, high-throughput clinical-genomic technologies which could potentially unveil significant high-level functions of genes.

Coordinates and intervals in graph-based reference genomes.

PubMed

Rand, Knut D; Grytten, Ivar; Nederbragt, Alexander J; Storvik, Geir O; Glad, Ingrid K; Sandve, Geir K

2017-05-18

It has been proposed that future reference genomes should be graph structures in order to better represent the sequence diversity present in a species. However, there is currently no standard method to represent genomic intervals, such as the positions of genes or transcription factor binding sites, on graph-based reference genomes. We formalize offset-based coordinate systems on graph-based reference genomes and introduce methods for representing intervals on these reference structures. We show the advantage of our methods by representing genes on a graph-based representation of the newest assembly of the human genome (GRCh38) and its alternative loci for regions that are highly variable. More complex reference genomes, containing alternative loci, require methods to represent genomic data on these structures. Our proposed notation for genomic intervals makes it possible to fully utilize the alternative loci of the GRCh38 assembly and potential future graph-based reference genomes. We have made a Python package for representing such intervals on offset-based coordinate systems, available at https://github.com/uio-cels/offsetbasedgraph . An interactive web-tool using this Python package to visualize genes on a graph created from GRCh38 is available at https://github.com/uio-cels/genomicgraphcoords .

CSAR-web: a web server of contig scaffolding using algebraic rearrangements.

PubMed

Chen, Kun-Tze; Lu, Chin Lung

2018-05-04

CSAR-web is a web-based tool that allows the users to efficiently and accurately scaffold (i.e. order and orient) the contigs of a target draft genome based on a complete or incomplete reference genome from a related organism. It takes as input a target genome in multi-FASTA format and a reference genome in FASTA or multi-FASTA format, depending on whether the reference genome is complete or incomplete, respectively. In addition, it requires the users to choose either 'NUCmer on nucleotides' or 'PROmer on translated amino acids' for CSAR-web to identify conserved genomic markers (i.e. matched sequence regions) between the target and reference genomes, which are used by the rearrangement-based scaffolding algorithm in CSAR-web to order and orient the contigs of the target genome based on the reference genome. In the output page, CSAR-web displays its scaffolding result in a graphical mode (i.e. scalable dotplot) allowing the users to visually validate the correctness of scaffolded contigs and in a tabular mode allowing the users to view the details of scaffolds. CSAR-web is available online at http://genome.cs.nthu.edu.tw/CSAR-web.

Genomicus update 2015: KaryoView and MatrixView provide a genome-wide perspective to multispecies comparative genomics.

PubMed

Louis, Alexandra; Nguyen, Nga Thi Thuy; Muffato, Matthieu; Roest Crollius, Hugues

2015-01-01

The Genomicus web server (http://www.genomicus.biologie.ens.fr/genomicus) is a visualization tool allowing comparative genomics in four different phyla (Vertebrate, Fungi, Metazoan and Plants). It provides access to genomic information from extant species, as well as ancestral gene content and gene order for vertebrates and flowering plants. Here we present the new features available for vertebrate genome with a focus on new graphical tools. The interface to enter the database has been improved, two pairwise genome comparison tools are now available (KaryoView and MatrixView) and the multiple genome comparison tools (PhyloView and AlignView) propose three new kinds of representation and a more intuitive menu. These new developments have been implemented for Genomicus portal dedicated to vertebrates. This allows the analysis of 68 extant animal genomes, as well as 58 ancestral reconstructed genomes. The Genomicus server also provides access to ancestral gene orders, to facilitate evolutionary and comparative genomics studies, as well as computationally predicted regulatory interactions, thanks to the representation of conserved non-coding elements with their putative gene targets. © The Author(s) 2014. Published by Oxford University Press on behalf of Nucleic Acids Research.

Home - The Cancer Genome Atlas - Cancer Genome - TCGA

Cancer.gov

The Cancer Genome Atlas (TCGA) is a comprehensive and coordinated effort to accelerate our understanding of the molecular basis of cancer through the application of genome analysis technologies, including large-scale genome sequencing.

The Innate Immune Database (IIDB)

PubMed Central

Korb, Martin; Rust, Aistair G; Thorsson, Vesteinn; Battail, Christophe; Li, Bin; Hwang, Daehee; Kennedy, Kathleen A; Roach, Jared C; Rosenberger, Carrie M; Gilchrist, Mark; Zak, Daniel; Johnson, Carrie; Marzolf, Bruz; Aderem, Alan; Shmulevich, Ilya; Bolouri, Hamid

2008-01-01

Background As part of a National Institute of Allergy and Infectious Diseases funded collaborative project, we have performed over 150 microarray experiments measuring the response of C57/BL6 mouse bone marrow macrophages to toll-like receptor stimuli. These microarray expression profiles are available freely from our project web site . Here, we report the development of a database of computationally predicted transcription factor binding sites and related genomic features for a set of over 2000 murine immune genes of interest. Our database, which includes microarray co-expression clusters and a host of web-based query, analysis and visualization facilities, is available freely via the internet. It provides a broad resource to the research community, and a stepping stone towards the delineation of the network of transcriptional regulatory interactions underlying the integrated response of macrophages to pathogens. Description We constructed a database indexed on genes and annotations of the immediate surrounding genomic regions. To facilitate both gene-specific and systems biology oriented research, our database provides the means to analyze individual genes or an entire genomic locus. Although our focus to-date has been on mammalian toll-like receptor signaling pathways, our database structure is not limited to this subject, and is intended to be broadly applicable to immunology. By focusing on selected immune-active genes, we were able to perform computationally intensive expression and sequence analyses that would currently be prohibitive if applied to the entire genome. Using six complementary computational algorithms and methodologies, we identified transcription factor binding sites based on the Position Weight Matrices available in TRANSFAC. For one example transcription factor (ATF3) for which experimental data is available, over 50% of our predicted binding sites coincide with genome-wide chromatin immnuopreciptation (ChIP-chip) results. Our database can be interrogated via a web interface. Genomic annotations and binding site predictions can be automatically viewed with a customized version of the Argo genome browser. Conclusion We present the Innate Immune Database (IIDB) as a community resource for immunologists interested in gene regulatory systems underlying innate responses to pathogens. The database website can be freely accessed at . PMID:18321385

Sequence-Based Mapping and Genome Editing Reveal Mutations in Stickleback Hps5 Cause Oculocutaneous Albinism and the casper Phenotype.

PubMed

Hart, James C; Miller, Craig T

2017-09-07

Here, we present and characterize the spontaneous X-linked recessive mutation casper , which causes oculocutaneous albinism in threespine sticklebacks ( Gasterosteus aculeatus ). In humans, Hermansky-Pudlak syndrome results in pigmentation defects due to disrupted formation of the melanin-containing lysosomal-related organelle (LRO), the melanosome. casper mutants display not only reduced pigmentation of melanosomes in melanophores, but also reductions in the iridescent silver color from iridophores, while the yellow pigmentation from xanthophores appears unaffected. We mapped casper using high-throughput sequencing of genomic DNA from bulked casper mutants to a region of the stickleback X chromosome (chromosome 19) near the stickleback ortholog of Hermansky-Pudlak syndrome 5 ( Hps5 ). casper mutants have an insertion of a single nucleotide in the sixth exon of Hps5 , predicted to generate an early frameshift. Genome editing using CRISPR/Cas9 induced lesions in Hps5 and phenocopied the casper mutation. Injecting single or paired Hps5 guide RNAs revealed higher incidences of genomic deletions from paired guide RNAs compared to single gRNAs. Stickleback Hps5 provides a genetic system where a hemizygous locus in XY males and a diploid locus in XX females can be used to generate an easily scored visible phenotype, facilitating quantitative studies of different genome editing approaches. Lastly, we show the ability to better visualize patterns of fluorescent transgenic reporters in Hps5 mutant fish. Thus, Hps5 mutations present an opportunity to study pigmented LROs in the emerging stickleback model system, as well as a tool to aid in assaying genome editing and visualizing enhancer activity in transgenic fish. Copyright © 2017 Hart and Milller.

MEVA--An Interactive Visualization Application for Validation of Multifaceted Meteorological Data with Multiple 3D Devices.

PubMed

Helbig, Carolin; Bilke, Lars; Bauer, Hans-Stefan; Böttinger, Michael; Kolditz, Olaf

2015-01-01

To achieve more realistic simulations, meteorologists develop and use models with increasing spatial and temporal resolution. The analyzing, comparing, and visualizing of resulting simulations becomes more and more challenging due to the growing amounts and multifaceted character of the data. Various data sources, numerous variables and multiple simulations lead to a complex database. Although a variety of software exists suited for the visualization of meteorological data, none of them fulfills all of the typical domain-specific requirements: support for quasi-standard data formats and different grid types, standard visualization techniques for scalar and vector data, visualization of the context (e.g., topography) and other static data, support for multiple presentation devices used in modern sciences (e.g., virtual reality), a user-friendly interface, and suitability for cooperative work. Instead of attempting to develop yet another new visualization system to fulfill all possible needs in this application domain, our approach is to provide a flexible workflow that combines different existing state-of-the-art visualization software components in order to hide the complexity of 3D data visualization tools from the end user. To complete the workflow and to enable the domain scientists to interactively visualize their data without advanced skills in 3D visualization systems, we developed a lightweight custom visualization application (MEVA - multifaceted environmental data visualization application) that supports the most relevant visualization and interaction techniques and can be easily deployed. Specifically, our workflow combines a variety of different data abstraction methods provided by a state-of-the-art 3D visualization application with the interaction and presentation features of a computer-games engine. Our customized application includes solutions for the analysis of multirun data, specifically with respect to data uncertainty and differences between simulation runs. In an iterative development process, our easy-to-use application was developed in close cooperation with meteorologists and visualization experts. The usability of the application has been validated with user tests. We report on how this application supports the users to prove and disprove existing hypotheses and discover new insights. In addition, the application has been used at public events to communicate research results.

MEVA - An Interactive Visualization Application for Validation of Multifaceted Meteorological Data with Multiple 3D Devices

PubMed Central

Helbig, Carolin; Bilke, Lars; Bauer, Hans-Stefan; Böttinger, Michael; Kolditz, Olaf

2015-01-01

Background To achieve more realistic simulations, meteorologists develop and use models with increasing spatial and temporal resolution. The analyzing, comparing, and visualizing of resulting simulations becomes more and more challenging due to the growing amounts and multifaceted character of the data. Various data sources, numerous variables and multiple simulations lead to a complex database. Although a variety of software exists suited for the visualization of meteorological data, none of them fulfills all of the typical domain-specific requirements: support for quasi-standard data formats and different grid types, standard visualization techniques for scalar and vector data, visualization of the context (e.g., topography) and other static data, support for multiple presentation devices used in modern sciences (e.g., virtual reality), a user-friendly interface, and suitability for cooperative work. Methods and Results Instead of attempting to develop yet another new visualization system to fulfill all possible needs in this application domain, our approach is to provide a flexible workflow that combines different existing state-of-the-art visualization software components in order to hide the complexity of 3D data visualization tools from the end user. To complete the workflow and to enable the domain scientists to interactively visualize their data without advanced skills in 3D visualization systems, we developed a lightweight custom visualization application (MEVA - multifaceted environmental data visualization application) that supports the most relevant visualization and interaction techniques and can be easily deployed. Specifically, our workflow combines a variety of different data abstraction methods provided by a state-of-the-art 3D visualization application with the interaction and presentation features of a computer-games engine. Our customized application includes solutions for the analysis of multirun data, specifically with respect to data uncertainty and differences between simulation runs. In an iterative development process, our easy-to-use application was developed in close cooperation with meteorologists and visualization experts. The usability of the application has been validated with user tests. We report on how this application supports the users to prove and disprove existing hypotheses and discover new insights. In addition, the application has been used at public events to communicate research results. PMID:25915061

Comparative Microbial Modules Resource: Generation and Visualization of Multi-species Biclusters

PubMed Central

Bate, Ashley; Eichenberger, Patrick; Bonneau, Richard

2011-01-01

The increasing abundance of large-scale, high-throughput datasets for many closely related organisms provides opportunities for comparative analysis via the simultaneous biclustering of datasets from multiple species. These analyses require a reformulation of how to organize multi-species datasets and visualize comparative genomics data analyses results. Recently, we developed a method, multi-species cMonkey, which integrates heterogeneous high-throughput datatypes from multiple species to identify conserved regulatory modules. Here we present an integrated data visualization system, built upon the Gaggle, enabling exploration of our method's results (available at http://meatwad.bio.nyu.edu/cmmr.html). The system can also be used to explore other comparative genomics datasets and outputs from other data analysis procedures – results from other multiple-species clustering programs or from independent clustering of different single-species datasets. We provide an example use of our system for two bacteria, Escherichia coli and Salmonella Typhimurium. We illustrate the use of our system by exploring conserved biclusters involved in nitrogen metabolism, uncovering a putative function for yjjI, a currently uncharacterized gene that we predict to be involved in nitrogen assimilation. PMID:22144874

Comparative microbial modules resource: generation and visualization of multi-species biclusters.

PubMed

Kacmarczyk, Thadeous; Waltman, Peter; Bate, Ashley; Eichenberger, Patrick; Bonneau, Richard

2011-12-01

The increasing abundance of large-scale, high-throughput datasets for many closely related organisms provides opportunities for comparative analysis via the simultaneous biclustering of datasets from multiple species. These analyses require a reformulation of how to organize multi-species datasets and visualize comparative genomics data analyses results. Recently, we developed a method, multi-species cMonkey, which integrates heterogeneous high-throughput datatypes from multiple species to identify conserved regulatory modules. Here we present an integrated data visualization system, built upon the Gaggle, enabling exploration of our method's results (available at http://meatwad.bio.nyu.edu/cmmr.html). The system can also be used to explore other comparative genomics datasets and outputs from other data analysis procedures - results from other multiple-species clustering programs or from independent clustering of different single-species datasets. We provide an example use of our system for two bacteria, Escherichia coli and Salmonella Typhimurium. We illustrate the use of our system by exploring conserved biclusters involved in nitrogen metabolism, uncovering a putative function for yjjI, a currently uncharacterized gene that we predict to be involved in nitrogen assimilation. © 2011 Kacmarczyk et al.

Research on the framework and key technologies of panoramic visualization for smart distribution network

NASA Astrophysics Data System (ADS)

Du, Jian; Sheng, Wanxing; Lin, Tao; Lv, Guangxian

2018-05-01

Nowadays, the smart distribution network has made tremendous progress, and the business visualization becomes even more significant and indispensable. Based on the summarization of traditional visualization technologies and demands of smart distribution network, a panoramic visualization application is proposed in this paper. The overall architecture, integrated architecture and service architecture of panoramic visualization application is firstly presented. Then, the architecture design and main functions of panoramic visualization system are elaborated in depth. In addition, the key technologies related to the application is discussed briefly. At last, two typical visualization scenarios in smart distribution network, which are risk warning and fault self-healing, proves that the panoramic visualization application is valuable for the operation and maintenance of the distribution network.

The Open Microscopy Environment: open image informatics for the biological sciences

NASA Astrophysics Data System (ADS)

Blackburn, Colin; Allan, Chris; Besson, Sébastien; Burel, Jean-Marie; Carroll, Mark; Ferguson, Richard K.; Flynn, Helen; Gault, David; Gillen, Kenneth; Leigh, Roger; Leo, Simone; Li, Simon; Lindner, Dominik; Linkert, Melissa; Moore, Josh; Moore, William J.; Ramalingam, Balaji; Rozbicki, Emil; Rustici, Gabriella; Tarkowska, Aleksandra; Walczysko, Petr; Williams, Eleanor; Swedlow, Jason R.

2016-07-01

Despite significant advances in biological imaging and analysis, major informatics challenges remain unsolved: file formats are proprietary, storage and analysis facilities are lacking, as are standards for sharing image data and results. While the open FITS file format is ubiquitous in astronomy, astronomical imaging shares many challenges with biological imaging, including the need to share large image sets using secure, cross-platform APIs, and the need for scalable applications for processing and visualization. The Open Microscopy Environment (OME) is an open-source software framework developed to address these challenges. OME tools include: an open data model for multidimensional imaging (OME Data Model); an open file format (OME-TIFF) and library (Bio-Formats) enabling free access to images (5D+) written in more than 145 formats from many imaging domains, including FITS; and a data management server (OMERO). The Java-based OMERO client-server platform comprises an image metadata store, an image repository, visualization and analysis by remote access, allowing sharing and publishing of image data. OMERO provides a means to manage the data through a multi-platform API. OMERO's model-based architecture has enabled its extension into a range of imaging domains, including light and electron microscopy, high content screening, digital pathology and recently into applications using non-image data from clinical and genomic studies. This is made possible using the Bio-Formats library. The current release includes a single mechanism for accessing image data of all types, regardless of original file format, via Java, C/C++ and Python and a variety of applications and environments (e.g. ImageJ, Matlab and R).

Genome editing: progress and challenges for medical applications.

PubMed

Carroll, Dana

2016-11-15

The development of the CRISPR-Cas platform for genome editing has greatly simplified the process of making targeted genetic modifications. Applications of genome editing are expected to have a substantial impact on human therapies through the development of better animal models, new target discovery, and direct therapeutic intervention.

A novel genome signature based on inter-nucleotide distances profiles for visualization of metagenomic data

NASA Astrophysics Data System (ADS)

Xie, Xian-Hua; Yu, Zu-Guo; Ma, Yuan-Lin; Han, Guo-Sheng; Anh, Vo

2017-09-01

There has been a growing interest in visualization of metagenomic data. The present study focuses on the visualization of metagenomic data using inter-nucleotide distances profile. We first convert the fragment sequences into inter-nucleotide distances profiles. Then we analyze these profiles by principal component analysis. Finally the principal components are used to obtain the 2-D scattered plot according to their source of species. We name our method as inter-nucleotide distances profiles (INP) method. Our method is evaluated on three benchmark data sets used in previous published papers. Our results demonstrate that the INP method is good, alternative and efficient for visualization of metagenomic data.

Mobile device geo-localization and object visualization in sensor networks

NASA Astrophysics Data System (ADS)

Lemaire, Simon; Bodensteiner, Christoph; Arens, Michael

2014-10-01

In this paper we present a method to visualize geo-referenced objects on modern smartphones using a multi- functional application design. The application applies different localization and visualization methods including the smartphone camera image. The presented application copes well with different scenarios. A generic application work flow and augmented reality visualization techniques are described. The feasibility of the approach is experimentally validated using an online desktop selection application in a network with a modern of-the-shelf smartphone. Applications are widespread and include for instance crisis and disaster management or military applications.

Juicebox.js Provides a Cloud-Based Visualization System for Hi-C Data.

PubMed

Robinson, James T; Turner, Douglass; Durand, Neva C; Thorvaldsdóttir, Helga; Mesirov, Jill P; Aiden, Erez Lieberman

2018-02-28

Contact mapping experiments such as Hi-C explore how genomes fold in 3D. Here, we introduce Juicebox.js, a cloud-based web application for exploring the resulting datasets. Like the original Juicebox application, Juicebox.js allows users to zoom in and out of such datasets using an interface similar to Google Earth. Juicebox.js also has many features designed to facilitate data reproducibility and sharing. Furthermore, Juicebox.js encodes the exact state of the browser in a shareable URL. Creating a public browser for a new Hi-C dataset does not require coding and can be accomplished in under a minute. The web app also makes it possible to create interactive figures online that can complement or replace ordinary journal figures. When combined with Juicer, this makes the entire process of data analysis transparent, insofar as every step from raw reads to published figure is publicly available as open source code. Copyright © 2018 The Authors. Published by Elsevier Inc. All rights reserved.

Post-genomics nanotechnology is gaining momentum: nanoproteomics and applications in life sciences.

PubMed

Kobeissy, Firas H; Gulbakan, Basri; Alawieh, Ali; Karam, Pierre; Zhang, Zhiqun; Guingab-Cagmat, Joy D; Mondello, Stefania; Tan, Weihong; Anagli, John; Wang, Kevin

2014-02-01

The post-genomics era has brought about new Omics biotechnologies, such as proteomics and metabolomics, as well as their novel applications to personal genomics and the quantified self. These advances are now also catalyzing other and newer post-genomics innovations, leading to convergences between Omics and nanotechnology. In this work, we systematically contextualize and exemplify an emerging strand of post-genomics life sciences, namely, nanoproteomics and its applications in health and integrative biological systems. Nanotechnology has been utilized as a complementary component to revolutionize proteomics through different kinds of nanotechnology applications, including nanoporous structures, functionalized nanoparticles, quantum dots, and polymeric nanostructures. Those applications, though still in their infancy, have led to several highly sensitive diagnostics and new methods of drug delivery and targeted therapy for clinical use. The present article differs from previous analyses of nanoproteomics in that it offers an in-depth and comparative evaluation of the attendant biotechnology portfolio and their applications as seen through the lens of post-genomics life sciences and biomedicine. These include: (1) immunosensors for inflammatory, pathogenic, and autoimmune markers for infectious and autoimmune diseases, (2) amplified immunoassays for detection of cancer biomarkers, and (3) methods for targeted therapy and automatically adjusted drug delivery such as in experimental stroke and brain injury studies. As nanoproteomics becomes available both to the clinician at the bedside and the citizens who are increasingly interested in access to novel post-genomics diagnostics through initiatives such as the quantified self, we anticipate further breakthroughs in personalized and targeted medicine.

Company profile: Complete Genomics Inc.

PubMed

Reid, Clifford

2011-02-01

Complete Genomics Inc. is a life sciences company that focuses on complete human genome sequencing. It is taking a completely different approach to DNA sequencing than other companies in the industry. Rather than building a general-purpose platform for sequencing all organisms and all applications, it has focused on a single application - complete human genome sequencing. The company's Complete Genomics Analysis Platform (CGA™ Platform) comprises an integrated package of biochemistry, instrumentation and software that sequences human genomes at the highest quality, lowest cost and largest scale available. Complete Genomics offers a turnkey service that enables customers to outsource their human genome sequencing to the company's genome sequencing center in Mountain View, CA, USA. Customers send in their DNA samples, the company does all the library preparation, DNA sequencing, assembly and variant analysis, and customers receive research-ready data that they can use for biological discovery.

Non-isotopic Method for In Situ LncRNA Visualization and Quantitation.

PubMed

Maqsodi, Botoul; Nikoloff, Corina

2016-01-01

In mammals and other eukaryotes, most of the genome is transcribed in a developmentally regulated manner to produce large numbers of long noncoding RNAs (lncRNAs). Genome-wide studies have identified thousands of lncRNAs lacking protein-coding capacity. RNA in situ hybridization technique is especially beneficial for the visualization of RNA (mRNA and lncRNA) expression in a heterogeneous population of cells/tissues; however its utility has been hampered by complicated procedures typically developed and optimized for the detection of a specific gene and therefore not amenable to a wide variety of genes and tissues.Recently, bDNA has revolutionized RNA in situ detection with fully optimized, robust assays for the detection of any mRNA and lncRNA targets in formalin-fixed paraffin-embedded (FFPE) and fresh frozen tissue sections using manual processing.

Targeted activation of diverse CRISPR-Cas systems for mammalian genome editing via proximal CRISPR targeting.

PubMed

Chen, Fuqiang; Ding, Xiao; Feng, Yongmei; Seebeck, Timothy; Jiang, Yanfang; Davis, Gregory D

2017-04-07

Bacterial CRISPR-Cas systems comprise diverse effector endonucleases with different targeting ranges, specificities and enzymatic properties, but many of them are inactive in mammalian cells and are thus precluded from genome-editing applications. Here we show that the type II-B FnCas9 from Francisella novicida possesses novel properties, but its nuclease function is frequently inhibited at many genomic loci in living human cells. Moreover, we develop a proximal CRISPR (termed proxy-CRISPR) targeting method that restores FnCas9 nuclease activity in a target-specific manner. We further demonstrate that this proxy-CRISPR strategy is applicable to diverse CRISPR-Cas systems, including type II-C Cas9 and type V Cpf1 systems, and can facilitate precise gene editing even between identical genomic sites within the same genome. Our findings provide a novel strategy to enable use of diverse otherwise inactive CRISPR-Cas systems for genome-editing applications and a potential path to modulate the impact of chromatin microenvironments on genome modification.

Targeted activation of diverse CRISPR-Cas systems for mammalian genome editing via proximal CRISPR targeting

PubMed Central

Chen, Fuqiang; Ding, Xiao; Feng, Yongmei; Seebeck, Timothy; Jiang, Yanfang; Davis, Gregory D.

2017-01-01

Bacterial CRISPR–Cas systems comprise diverse effector endonucleases with different targeting ranges, specificities and enzymatic properties, but many of them are inactive in mammalian cells and are thus precluded from genome-editing applications. Here we show that the type II-B FnCas9 from Francisella novicida possesses novel properties, but its nuclease function is frequently inhibited at many genomic loci in living human cells. Moreover, we develop a proximal CRISPR (termed proxy-CRISPR) targeting method that restores FnCas9 nuclease activity in a target-specific manner. We further demonstrate that this proxy-CRISPR strategy is applicable to diverse CRISPR–Cas systems, including type II-C Cas9 and type V Cpf1 systems, and can facilitate precise gene editing even between identical genomic sites within the same genome. Our findings provide a novel strategy to enable use of diverse otherwise inactive CRISPR–Cas systems for genome-editing applications and a potential path to modulate the impact of chromatin microenvironments on genome modification. PMID:28387220

The spectrum of genomic signatures: from dinucleotides to chaos game representation.

PubMed

Wang, Yingwei; Hill, Kathleen; Singh, Shiva; Kari, Lila

2005-02-14

In the post genomic era, access to complete genome sequence data for numerous diverse species has opened multiple avenues for examining and comparing primary DNA sequence organization of entire genomes. Previously, the concept of a genomic signature was introduced with the observation of species-type specific Dinucleotide Relative Abundance Profiles (DRAPs); dinucleotides were identified as the subsequences with the greatest bias in representation in a majority of genomes. Herein, we demonstrate that DRAP is one particular genomic signature contained within a broader spectrum of signatures. Within this spectrum, an alternative genomic signature, Chaos Game Representation (CGR), provides a unique visualization of patterns in sequence organization. A genomic signature is associated with a particular integer order or subsequence length that represents a measure of the resolution or granularity in the analysis of primary DNA sequence organization. We quantitatively explore the organizational information provided by genomic signatures of different orders through different distance measures, including a novel Image Distance. The Image Distance and other existing distance measures are evaluated by comparing the phylogenetic trees they generate for 26 complete mitochondrial genomes from a diversity of species. The phylogenetic tree generated by the Image Distance is compatible with the known relatedness of species. Quantitative evaluation of the spectrum of genomic signatures may be used to ultimately gain insight into the determinants and biological relevance of the genome signatures.

OSLay: optimal syntenic layout of unfinished assemblies.

PubMed

Richter, Daniel C; Schuster, Stephan C; Huson, Daniel H

2007-07-01

The whole genome shotgun approach to genome sequencing results in a collection of contigs that must be ordered and oriented to facilitate efficient gap closure. We present a new tool OSLay that uses synteny between matching sequences in a target assembly and a reference assembly to layout the contigs (or scaffolds) in the target assembly. The underlying algorithm is based on maximum weight matching. The tool provides an interactive visualization of the computed layout and the result can be imported into the assembly editing tool Consed to support the design of primer pairs for gap closure. To enhance efficiency in the gap closure phase of a genome project it is crucial to know which contigs are adjacent in the target genome. Related genome sequences can be used to layout contigs in an assembly. OSLay is freely available from: http://www-ab.informatik.unituebingen.de/software/oslay.

ISRNA: an integrative online toolkit for short reads from high-throughput sequencing data.

PubMed

Luo, Guan-Zheng; Yang, Wei; Ma, Ying-Ke; Wang, Xiu-Jie

2014-02-01

Integrative Short Reads NAvigator (ISRNA) is an online toolkit for analyzing high-throughput small RNA sequencing data. Besides the high-speed genome mapping function, ISRNA provides statistics for genomic location, length distribution and nucleotide composition bias analysis of sequence reads. Number of reads mapped to known microRNAs and other classes of short non-coding RNAs, coverage of short reads on genes, expression abundance of sequence reads as well as some other analysis functions are also supported. The versatile search functions enable users to select sequence reads according to their sub-sequences, expression abundance, genomic location, relationship to genes, etc. A specialized genome browser is integrated to visualize the genomic distribution of short reads. ISRNA also supports management and comparison among multiple datasets. ISRNA is implemented in Java/C++/Perl/MySQL and can be freely accessed at http://omicslab.genetics.ac.cn/ISRNA/.

Public data and open source tools for multi-assay genomic investigation of disease.

PubMed

Kannan, Lavanya; Ramos, Marcel; Re, Angela; El-Hachem, Nehme; Safikhani, Zhaleh; Gendoo, Deena M A; Davis, Sean; Gomez-Cabrero, David; Castelo, Robert; Hansen, Kasper D; Carey, Vincent J; Morgan, Martin; Culhane, Aedín C; Haibe-Kains, Benjamin; Waldron, Levi

2016-07-01

Molecular interrogation of a biological sample through DNA sequencing, RNA and microRNA profiling, proteomics and other assays, has the potential to provide a systems level approach to predicting treatment response and disease progression, and to developing precision therapies. Large publicly funded projects have generated extensive and freely available multi-assay data resources; however, bioinformatic and statistical methods for the analysis of such experiments are still nascent. We review multi-assay genomic data resources in the areas of clinical oncology, pharmacogenomics and other perturbation experiments, population genomics and regulatory genomics and other areas, and tools for data acquisition. Finally, we review bioinformatic tools that are explicitly geared toward integrative genomic data visualization and analysis. This review provides starting points for accessing publicly available data and tools to support development of needed integrative methods. © The Author 2015. Published by Oxford University Press.

MIPS Arabidopsis thaliana Database (MAtDB): an integrated biological knowledge resource based on the first complete plant genome

PubMed Central

Schoof, Heiko; Zaccaria, Paolo; Gundlach, Heidrun; Lemcke, Kai; Rudd, Stephen; Kolesov, Grigory; Arnold, Roland; Mewes, H. W.; Mayer, Klaus F. X.

2002-01-01

Arabidopsis thaliana is the first plant for which the complete genome has been sequenced and published. Annotation of complex eukaryotic genomes requires more than the assignment of genetic elements to the sequence. Besides completing the list of genes, we need to discover their cellular roles, their regulation and their interactions in order to understand the workings of the whole plant. The MIPS Arabidopsis thaliana Database (MAtDB; http://mips.gsf.de/proj/thal/db) started out as a repository for genome sequence data in the European Scientists Sequencing Arabidopsis (ESSA) project and the Arabidopsis Genome Initiative. Our aim is to transform MAtDB into an integrated biological knowledge resource by integrating diverse data, tools, query and visualization capabilities and by creating a comprehensive resource for Arabidopsis as a reference model for other species, including crop plants. PMID:11752263

Streamlining genomes: toward the generation of simplified and stabilized microbial systems.

PubMed

Leprince, Audrey; van Passel, Mark W J; dos Santos, Vitor A P Martins

2012-10-01

At the junction between systems and synthetic biology, genome streamlining provides a solid foundation both for increased understanding of cellular circuitry, and for the tailoring of microbial chassis towards innovative biotechnological applications. Iterative genomic deletions (targeted and random) helps to generate simplified, stabilized and predictable genomes, whereas multiplexing genome engineering reveals a broad functional genetic diversity. The decrease in oligo and gene synthesis costs promises effective combinatorial tools for the generation of chassis based on streamlined and tractable genomes. Here we review recent progresses in streamlining genomes through recombineering techniques aiming to generate insights into cellular mechanisms and responses towards the design and assembly of streamlined genome chassis together with new cellular modules in diverse biotechnological applications. Copyright © 2012 Elsevier Ltd. All rights reserved.

Comparative map and trait viewer (CMTV): an integrated bioinformatic tool to construct consensus maps and compare QTL and functional genomics data across genomes and experiments.

PubMed

Sawkins, M C; Farmer, A D; Hoisington, D; Sullivan, J; Tolopko, A; Jiang, Z; Ribaut, J-M

2004-10-01

In the past few decades, a wealth of genomic data has been produced in a wide variety of species using a diverse array of functional and molecular marker approaches. In order to unlock the full potential of the information contained in these independent experiments, researchers need efficient and intuitive means to identify common genomic regions and genes involved in the expression of target phenotypic traits across diverse conditions. To address this need, we have developed a Comparative Map and Trait Viewer (CMTV) tool that can be used to construct dynamic aggregations of a variety of types of genomic datasets. By algorithmically determining correspondences between sets of objects on multiple genomic maps, the CMTV can display syntenic regions across taxa, combine maps from separate experiments into a consensus map, or project data from different maps into a common coordinate framework using dynamic coordinate translations between source and target maps. We present a case study that illustrates the utility of the tool for managing large and varied datasets by integrating data collected by CIMMYT in maize drought tolerance research with data from public sources. This example will focus on one of the visualization features for Quantitative Trait Locus (QTL) data, using likelihood ratio (LR) files produced by generic QTL analysis software and displaying the data in a unique visual manner across different combinations of traits, environments and crosses. Once a genomic region of interest has been identified, the CMTV can search and display additional QTLs meeting a particular threshold for that region, or other functional data such as sets of differentially expressed genes located in the region; it thus provides an easily used means for organizing and manipulating data sets that have been dynamically integrated under the focus of the researcher's specific hypothesis.

Nonverbal and Paraverbal Behavior in (Simulated) Medical Visits Related to Genomics and Weight: A Role for Emotion and Race

PubMed Central

Persky, Susan; Ferrer, Rebecca A.; Klein, William M. P.

2016-01-01

It is crucial to examine patient reactions to genomics-informed approaches to weight management within a clinical context, and understand the influence of patient characteristics (here, emotion and race). Examining nonverbal reactions offers a window into patients’ implicit cognitive, attitudinal and affective processes related to clinical encounters. We simulated a weight management clinical interaction with a virtual reality-based physician, and experimentally manipulated patient emotional state (anger/ fear) and whether the physician made genomic or personal behavior attributions for weight. Participants were 190 overweight females who racially identified as either Black or White. Participants made less visual contact when receiving genomic information in the anger condition, and Black participants exhibited lowered voice pitch when receiving genomic information. Black participants also increased their interpersonal distance when receiving genomic information in the anger condition. By studying non-conscious nonverbal behavior, we can better understand the nuances of these interactions. PMID:27146511

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

Enrichr: a comprehensive gene set enrichment analysis web server 2016 update

PubMed Central

Kuleshov, Maxim V.; Jones, Matthew R.; Rouillard, Andrew D.; Fernandez, Nicolas F.; Duan, Qiaonan; Wang, Zichen; Koplev, Simon; Jenkins, Sherry L.; Jagodnik, Kathleen M.; Lachmann, Alexander; McDermott, Michael G.; Monteiro, Caroline D.; Gundersen, Gregory W.; Ma'ayan, Avi

2016-01-01

Enrichment analysis is a popular method for analyzing gene sets generated by genome-wide experiments. Here we present a significant update to one of the tools in this domain called Enrichr. Enrichr currently contains a large collection of diverse gene set libraries available for analysis and download. In total, Enrichr currently contains 180 184 annotated gene sets from 102 gene set libraries. New features have been added to Enrichr including the ability to submit fuzzy sets, upload BED files, improved application programming interface and visualization of the results as clustergrams. Overall, Enrichr is a comprehensive resource for curated gene sets and a search engine that accumulates biological knowledge for further biological discoveries. Enrichr is freely available at: http://amp.pharm.mssm.edu/Enrichr. PMID:27141961

Curating and Integrating Data from Multiple Sources to Support Healthcare Analytics.

PubMed

Ng, Kenney; Kakkanatt, Chris; Benigno, Michael; Thompson, Clay; Jackson, Margaret; Cahan, Amos; Zhu, Xinxin; Zhang, Ping; Huang, Paul

2015-01-01

As the volume and variety of healthcare related data continues to grow, the analysis and use of this data will increasingly depend on the ability to appropriately collect, curate and integrate disparate data from many different sources. We describe our approach to and highlight our experiences with the development of a robust data collection, curation and integration infrastructure that supports healthcare analytics. This system has been successfully applied to the processing of a variety of data types including clinical data from electronic health records and observational studies, genomic data, microbiomic data, self-reported data from surveys and self-tracked data from wearable devices from over 600 subjects. The curated data is currently being used to support healthcare analytic applications such as data visualization, patient stratification and predictive modeling.

High-accuracy biodistribution analysis of adeno-associated virus variants by double barcode sequencing.

PubMed

Marsic, Damien; Méndez-Gómez, Héctor R; Zolotukhin, Sergei

2015-01-01

Biodistribution analysis is a key step in the evaluation of adeno-associated virus (AAV) capsid variants, whether natural isolates or produced by rational design or directed evolution. Indeed, when screening candidate vectors, accurate knowledge about which tissues are infected and how efficiently is essential. We describe the design, validation, and application of a new vector, pTR-UF50-BC, encoding a bioluminescent protein, a fluorescent protein and a DNA barcode, which can be used to visualize localization of transduction at the organism, organ, tissue, or cellular levels. In addition, by linking capsid variants to different barcoded versions of the vector and amplifying the barcode region from various tissue samples using barcoded primers, biodistribution of viral genomes can be analyzed with high accuracy and efficiency.

Organization and integration of biomedical knowledge with concept maps for key peroxisomal pathways.

PubMed

Willemsen, A M; Jansen, G A; Komen, J C; van Hooff, S; Waterham, H R; Brites, P M T; Wanders, R J A; van Kampen, A H C

2008-08-15

One important area of clinical genomics research involves the elucidation of molecular mechanisms underlying (complex) disorders which eventually may lead to new diagnostic or drug targets. To further advance this area of clinical genomics one of the main challenges is the acquisition and integration of data, information and expert knowledge for specific biomedical domains and diseases. Currently the required information is not very well organized but scattered over biological and biomedical databases, basic text books, scientific literature and experts' minds and may be highly specific, heterogeneous, complex and voluminous. We present a new framework to construct knowledge bases with concept maps for presentation of information and the web ontology language OWL for the representation of information. We demonstrate this framework through the construction of a peroxisomal knowledge base, which focuses on four key peroxisomal pathways and several related genetic disorders. All 155 concept maps in our knowledge base are linked to at least one other concept map, which allows the visualization of one big network of related pieces of information. The peroxisome knowledge base is available from www.bioinformaticslaboratory.nl (Support-->Web applications). Supplementary data is available from www.bioinformaticslaboratory.nl (Research-->Output--> Publications--> KB_SuppInfo)

Cancer Digital Slide Archive: an informatics resource to support integrated in silico analysis of TCGA pathology data

PubMed Central

Gutman, David A; Cobb, Jake; Somanna, Dhananjaya; Park, Yuna; Wang, Fusheng; Kurc, Tahsin; Saltz, Joel H; Brat, Daniel J; Cooper, Lee A D

2013-01-01

Background The integration and visualization of multimodal datasets is a common challenge in biomedical informatics. Several recent studies of The Cancer Genome Atlas (TCGA) data have illustrated important relationships between morphology observed in whole-slide images, outcome, and genetic events. The pairing of genomics and rich clinical descriptions with whole-slide imaging provided by TCGA presents a unique opportunity to perform these correlative studies. However, better tools are needed to integrate the vast and disparate data types. Objective To build an integrated web-based platform supporting whole-slide pathology image visualization and data integration. Materials and methods All images and genomic data were directly obtained from the TCGA and National Cancer Institute (NCI) websites. Results The Cancer Digital Slide Archive (CDSA) produced is accessible to the public (http://cancer.digitalslidearchive.net) and currently hosts more than 20 000 whole-slide images from 22 cancer types. Discussion The capabilities of CDSA are demonstrated using TCGA datasets to integrate pathology imaging with associated clinical, genomic and MRI measurements in glioblastomas and can be extended to other tumor types. CDSA also allows URL-based sharing of whole-slide images, and has preliminary support for directly sharing regions of interest and other annotations. Images can also be selected on the basis of other metadata, such as mutational profile, patient age, and other relevant characteristics. Conclusions With the increasing availability of whole-slide scanners, analysis of digitized pathology images will become increasingly important in linking morphologic observations with genomic and clinical endpoints. PMID:23893318

Two-Way Gene Interaction From Microarray Data Based on Correlation Methods.

PubMed

Alavi Majd, Hamid; Talebi, Atefeh; Gilany, Kambiz; Khayyer, Nasibeh

2016-06-01

Gene networks have generated a massive explosion in the development of high-throughput techniques for monitoring various aspects of gene activity. Networks offer a natural way to model interactions between genes, and extracting gene network information from high-throughput genomic data is an important and difficult task. The purpose of this study is to construct a two-way gene network based on parametric and nonparametric correlation coefficients. The first step in constructing a Gene Co-expression Network is to score all pairs of gene vectors. The second step is to select a score threshold and connect all gene pairs whose scores exceed this value. In the foundation-application study, we constructed two-way gene networks using nonparametric methods, such as Spearman's rank correlation coefficient and Blomqvist's measure, and compared them with Pearson's correlation coefficient. We surveyed six genes of venous thrombosis disease, made a matrix entry representing the score for the corresponding gene pair, and obtained two-way interactions using Pearson's correlation, Spearman's rank correlation, and Blomqvist's coefficient. Finally, these methods were compared with Cytoscape, based on BIND, and Gene Ontology, based on molecular function visual methods; R software version 3.2 and Bioconductor were used to perform these methods. Based on the Pearson and Spearman correlations, the results were the same and were confirmed by Cytoscape and GO visual methods; however, Blomqvist's coefficient was not confirmed by visual methods. Some results of the correlation coefficients are not the same with visualization. The reason may be due to the small number of data.

Ensembl Plants: Integrating Tools for Visualizing, Mining, and Analyzing Plant Genomics Data.

PubMed

Bolser, Dan; Staines, Daniel M; Pritchard, Emily; Kersey, Paul

2016-01-01

Ensembl Plants ( http://plants.ensembl.org ) is an integrative resource presenting genome-scale information for a growing number of sequenced plant species (currently 33). Data provided includes genome sequence, gene models, functional annotation, and polymorphic loci. Various additional information are provided for variation data, including population structure, individual genotypes, linkage, and phenotype data. In each release, comparative analyses are performed on whole genome and protein sequences, and genome alignments and gene trees are made available that show the implied evolutionary history of each gene family. Access to the data is provided through a genome browser incorporating many specialist interfaces for different data types, and through a variety of additional methods for programmatic access and data mining. These access routes are consistent with those offered through the Ensembl interface for the genomes of non-plant species, including those of plant pathogens, pests, and pollinators.Ensembl Plants is updated 4-5 times a year and is developed in collaboration with our international partners in the Gramene ( http://www.gramene.org ) and transPLANT projects ( http://www.transplantdb.org ).

Microbial genomic island discovery, visualization and analysis.

PubMed

Bertelli, Claire; Tilley, Keith E; Brinkman, Fiona S L

2018-06-03

Horizontal gene transfer (also called lateral gene transfer) is a major mechanism for microbial genome evolution, enabling rapid adaptation and survival in specific niches. Genomic islands (GIs), commonly defined as clusters of bacterial or archaeal genes of probable horizontal origin, are of particular medical, environmental and/or industrial interest, as they disproportionately encode virulence factors and some antimicrobial resistance genes and may harbor entire metabolic pathways that confer a specific adaptation (solvent resistance, symbiosis properties, etc). As large-scale analyses of microbial genomes increases, such as for genomic epidemiology investigations of infectious disease outbreaks in public health, there is increased appreciation of the need to accurately predict and track GIs. Over the past decade, numerous computational tools have been developed to tackle the challenges inherent in accurate GI prediction. We review here the main types of GI prediction methods and discuss their advantages and limitations for a routine analysis of microbial genomes in this era of rapid whole-genome sequencing. An assessment is provided of 20 GI prediction software methods that use sequence-composition bias to identify the GIs, using a reference GI data set from 104 genomes obtained using an independent comparative genomics approach. Finally, we present guidelines to assist researchers in effectively identifying these key genomic regions.