Web Apollo: a web-based genomic annotation editing platform

PubMed Central

2013-01-01

Web Apollo is the first instantaneous, collaborative genomic annotation editor available on the web. One of the natural consequences following from current advances in sequencing technology is that there are more and more researchers sequencing new genomes. These researchers require tools to describe the functional features of their newly sequenced genomes. With Web Apollo researchers can use any of the common browsers (for example, Chrome or Firefox) to jointly analyze and precisely describe the features of a genome in real time, whether they are in the same room or working from opposite sides of the world. PMID:24000942

A web-based genomic sequence database for the Streptomycetaceae: a tool for systematics and genome mining

USDA-ARS?s Scientific Manuscript database

The ARS Microbial Genome Sequence Database (http://199.133.98.43), a web-based database server, was established utilizing the BIGSdb (Bacterial Isolate Genomics Sequence Database) software package, developed at Oxford University, as a tool to manage multi-locus sequence data for the family Streptomy...

The Comprehensive Phytopathogen Genomics Resource: a web-based resource for data-mining plant pathogen genomes.

PubMed

Hamilton, John P; Neeno-Eckwall, Eric C; Adhikari, Bishwo N; Perna, Nicole T; Tisserat, Ned; Leach, Jan E; Lévesque, C André; Buell, C Robin

2011-01-01

The Comprehensive Phytopathogen Genomics Resource (CPGR) provides a web-based portal for plant pathologists and diagnosticians to view the genome and trancriptome sequence status of 806 bacterial, fungal, oomycete, nematode, viral and viroid plant pathogens. Tools are available to search and analyze annotated genome sequences of 74 bacterial, fungal and oomycete pathogens. Oomycete and fungal genomes are obtained directly from GenBank, whereas bacterial genome sequences are downloaded from the A Systematic Annotation Package (ASAP) database that provides curation of genomes using comparative approaches. Curated lists of bacterial genes relevant to pathogenicity and avirulence are also provided. The Plant Pathogen Transcript Assemblies Database provides annotated assemblies of the transcribed regions of 82 eukaryotic genomes from publicly available single pass Expressed Sequence Tags. Data-mining tools are provided along with tools to create candidate diagnostic markers, an emerging use for genomic sequence data in plant pathology. The Plant Pathogen Ribosomal DNA (rDNA) database is a resource for pathogens that lack genome or transcriptome data sets and contains 131 755 rDNA sequences from GenBank for 17 613 species identified as plant pathogens and related genera. Database URL: http://cpgr.plantbiology.msu.edu.

Accessing the SEED genome databases via Web services API: tools for programmers.

PubMed

Disz, Terry; Akhter, Sajia; Cuevas, Daniel; Olson, Robert; Overbeek, Ross; Vonstein, Veronika; Stevens, Rick; Edwards, Robert A

2010-06-14

The SEED integrates many publicly available genome sequences into a single resource. The database contains accurate and up-to-date annotations based on the subsystems concept that leverages clustering between genomes and other clues to accurately and efficiently annotate microbial genomes. The backend is used as the foundation for many genome annotation tools, such as the Rapid Annotation using Subsystems Technology (RAST) server for whole genome annotation, the metagenomics RAST server for random community genome annotations, and the annotation clearinghouse for exchanging annotations from different resources. In addition to a web user interface, the SEED also provides Web services based API for programmatic access to the data in the SEED, allowing the development of third-party tools and mash-ups. The currently exposed Web services encompass over forty different methods for accessing data related to microbial genome annotations. The Web services provide comprehensive access to the database back end, allowing any programmer access to the most consistent and accurate genome annotations available. The Web services are deployed using a platform independent service-oriented approach that allows the user to choose the most suitable programming platform for their application. Example code demonstrate that Web services can be used to access the SEED using common bioinformatics programming languages such as Perl, Python, and Java. We present a novel approach to access the SEED database. Using Web services, a robust API for access to genomics data is provided, without requiring large volume downloads all at once. The API ensures timely access to the most current datasets available, including the new genomes as soon as they come online.

WheatGenome.info: an integrated database and portal for wheat genome information.

PubMed

Lai, Kaitao; Berkman, Paul J; Lorenc, Michal Tadeusz; Duran, Chris; Smits, Lars; Manoli, Sahana; Stiller, Jiri; Edwards, David

2012-02-01

Bread wheat (Triticum aestivum) is one of the most important crop plants, globally providing staple food for a large proportion of the human population. However, improvement of this crop has been limited due to its large and complex genome. Advances in genomics are supporting wheat crop improvement. We provide a variety of web-based systems hosting wheat genome and genomic data to support wheat research and crop improvement. WheatGenome.info is an integrated database resource which includes multiple web-based applications. These include a GBrowse2-based wheat genome viewer with BLAST search portal, TAGdb for searching wheat second-generation genome sequence data, wheat autoSNPdb, links to wheat genetic maps using CMap and CMap3D, and a wheat genome Wiki to allow interaction between diverse wheat genome sequencing activities. This system includes links to a variety of wheat genome resources hosted at other research organizations. This integrated database aims to accelerate wheat genome research and is freely accessible via the web interface at http://www.wheatgenome.info/.

Web-based visual analysis for high-throughput genomics

PubMed Central

2013-01-01

Background Visualization plays an essential role in genomics research by making it possible to observe correlations and trends in large datasets as well as communicate findings to others. Visual analysis, which combines visualization with analysis tools to enable seamless use of both approaches for scientific investigation, offers a powerful method for performing complex genomic analyses. However, there are numerous challenges that arise when creating rich, interactive Web-based visualizations/visual analysis applications for high-throughput genomics. These challenges include managing data flow from Web server to Web browser, integrating analysis tools and visualizations, and sharing visualizations with colleagues. Results We have created a platform simplifies the creation of Web-based visualization/visual analysis applications for high-throughput genomics. This platform provides components that make it simple to efficiently query very large datasets, draw common representations of genomic data, integrate with analysis tools, and share or publish fully interactive visualizations. Using this platform, we have created a Circos-style genome-wide viewer, a generic scatter plot for correlation analysis, an interactive phylogenetic tree, a scalable genome browser for next-generation sequencing data, and an application for systematically exploring tool parameter spaces to find good parameter values. All visualizations are interactive and fully customizable. The platform is integrated with the Galaxy (http://galaxyproject.org) genomics workbench, making it easy to integrate new visual applications into Galaxy. Conclusions Visualization and visual analysis play an important role in high-throughput genomics experiments, and approaches are needed to make it easier to create applications for these activities. Our framework provides a foundation for creating Web-based visualizations and integrating them into Galaxy. Finally, the visualizations we have created using the framework are useful tools for high-throughput genomics experiments. PMID:23758618

The Biofuel Feedstock Genomics Resource: a web-based portal and database to enable functional genomics of plant biofuel feedstock species.

PubMed

Childs, Kevin L; Konganti, Kranti; Buell, C Robin

2012-01-01

Major feedstock sources for future biofuel production are likely to be high biomass producing plant species such as poplar, pine, switchgrass, sorghum and maize. One active area of research in these species is genome-enabled improvement of lignocellulosic biofuel feedstock quality and yield. To facilitate genomic-based investigations in these species, we developed the Biofuel Feedstock Genomic Resource (BFGR), a database and web-portal that provides high-quality, uniform and integrated functional annotation of gene and transcript assembly sequences from species of interest to lignocellulosic biofuel feedstock researchers. The BFGR includes sequence data from 54 species and permits researchers to view, analyze and obtain annotation at the gene, transcript, protein and genome level. Annotation of biochemical pathways permits the identification of key genes and transcripts central to the improvement of lignocellulosic properties in these species. The integrated nature of the BFGR in terms of annotation methods, orthologous/paralogous relationships and linkage to seven species with complete genome sequences allows comparative analyses for biofuel feedstock species with limited sequence resources. Database URL: http://bfgr.plantbiology.msu.edu.

GSP: a web-based platform for designing genome-specific primers in polyploids

USDA-ARS?s Scientific Manuscript database

The primary goal of this research was to develop a web-based platform named GSP for designing genome-specific primers to distinguish subgenome sequences in the polyploid genome background. GSP uses BLAST to extract homeologous sequences of the subgenomes in the existing databases, performed a multip...

WebMeV | Informatics Technology for Cancer Research (ITCR)

Cancer.gov

Web MeV (Multiple-experiment Viewer) is a web/cloud-based tool for genomic data analysis. Web MeV is being built to meet the challenge of exploring large public genomic data set with intuitive graphical interface providing access to state-of-the-art analytical tools.

NIH tools facilitate matching cancer drugs with gene targets

Cancer.gov

A new study details how a suite of web-based tools provides the research community with greatly improved capacity to compare data derived from large collections of genomic information against thousands of drugs. By comparing drugs and genetic targets, re

CBS Genome Atlas Database: a dynamic storage for bioinformatic results and sequence data.

PubMed

Hallin, Peter F; Ussery, David W

2004-12-12

Currently, new bacterial genomes are being published on a monthly basis. With the growing amount of genome sequence data, there is a demand for a flexible and easy-to-maintain structure for storing sequence data and results from bioinformatic analysis. More than 150 sequenced bacterial genomes are now available, and comparisons of properties for taxonomically similar organisms are not readily available to many biologists. In addition to the most basic information, such as AT content, chromosome length, tRNA count and rRNA count, a large number of more complex calculations are needed to perform detailed comparative genomics. DNA structural calculations like curvature and stacking energy, DNA compositions like base skews, oligo skews and repeats at the local and global level are just a few of the analysis that are presented on the CBS Genome Atlas Web page. Complex analysis, changing methods and frequent addition of new models are factors that require a dynamic database layout. Using basic tools like the GNU Make system, csh, Perl and MySQL, we have created a flexible database environment for storing and maintaining such results for a collection of complete microbial genomes. Currently, these results counts to more than 220 pieces of information. The backbone of this solution consists of a program package written in Perl, which enables administrators to synchronize and update the database content. The MySQL database has been connected to the CBS web-server via PHP4, to present a dynamic web content for users outside the center. This solution is tightly fitted to existing server infrastructure and the solutions proposed here can perhaps serve as a template for other research groups to solve database issues. A web based user interface which is dynamically linked to the Genome Atlas Database can be accessed via www.cbs.dtu.dk/services/GenomeAtlas/. This paper has a supplemental information page which links to the examples presented: www.cbs.dtu.dk/services/GenomeAtlas/suppl/bioinfdatabase.

The integrated web service and genome database for agricultural plants with biotechnology information.

PubMed

Kim, Changkug; Park, Dongsuk; Seol, Youngjoo; Hahn, Jangho

2011-01-01

The National Agricultural Biotechnology Information Center (NABIC) constructed an agricultural biology-based infrastructure and developed a Web based relational database for agricultural plants with biotechnology information. The NABIC has concentrated on functional genomics of major agricultural plants, building an integrated biotechnology database for agro-biotech information that focuses on genomics of major agricultural resources. This genome database provides annotated genome information from 1,039,823 records mapped to rice, Arabidopsis, and Chinese cabbage.

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.

RSAT 2018: regulatory sequence analysis tools 20th anniversary.

PubMed

Nguyen, Nga Thi Thuy; Contreras-Moreira, Bruno; Castro-Mondragon, Jaime A; Santana-Garcia, Walter; Ossio, Raul; Robles-Espinoza, Carla Daniela; Bahin, Mathieu; Collombet, Samuel; Vincens, Pierre; Thieffry, Denis; van Helden, Jacques; Medina-Rivera, Alejandra; Thomas-Chollier, Morgane

2018-05-02

RSAT (Regulatory Sequence Analysis Tools) is a suite of modular tools for the detection and the analysis of cis-regulatory elements in genome sequences. Its main applications are (i) motif discovery, including from genome-wide datasets like ChIP-seq/ATAC-seq, (ii) motif scanning, (iii) motif analysis (quality assessment, comparisons and clustering), (iv) analysis of regulatory variations, (v) comparative genomics. Six public servers jointly support 10 000 genomes from all kingdoms. Six novel or refactored programs have been added since the 2015 NAR Web Software Issue, including updated programs to analyse regulatory variants (retrieve-variation-seq, variation-scan, convert-variations), along with tools to extract sequences from a list of coordinates (retrieve-seq-bed), to select motifs from motif collections (retrieve-matrix), and to extract orthologs based on Ensembl Compara (get-orthologs-compara). Three use cases illustrate the integration of new and refactored tools to the suite. This Anniversary update gives a 20-year perspective on the software suite. RSAT is well-documented and available through Web sites, SOAP/WSDL (Simple Object Access Protocol/Web Services Description Language) web services, virtual machines and stand-alone programs at http://www.rsat.eu/.

The integrated web service and genome database for agricultural plants with biotechnology information

PubMed Central

Kim, ChangKug; Park, DongSuk; Seol, YoungJoo; Hahn, JangHo

2011-01-01

The National Agricultural Biotechnology Information Center (NABIC) constructed an agricultural biology-based infrastructure and developed a Web based relational database for agricultural plants with biotechnology information. The NABIC has concentrated on functional genomics of major agricultural plants, building an integrated biotechnology database for agro-biotech information that focuses on genomics of major agricultural resources. This genome database provides annotated genome information from 1,039,823 records mapped to rice, Arabidopsis, and Chinese cabbage. PMID:21887015

OrthoVenn: a web server for genome wide comparison and annotation of orthologous clusters across multiple species

USDA-ARS?s Scientific Manuscript database

Genome wide analysis of orthologous clusters is an important component of comparative genomics studies. Identifying the overlap among orthologous clusters can enable us to elucidate the function and evolution of proteins across multiple species. Here, we report a web platform named OrthoVenn that i...

arrayCGHbase: an analysis platform for comparative genomic hybridization microarrays

PubMed Central

Menten, Björn; Pattyn, Filip; De Preter, Katleen; Robbrecht, Piet; Michels, Evi; Buysse, Karen; Mortier, Geert; De Paepe, Anne; van Vooren, Steven; Vermeesch, Joris; Moreau, Yves; De Moor, Bart; Vermeulen, Stefan; Speleman, Frank; Vandesompele, Jo

2005-01-01

Background The availability of the human genome sequence as well as the large number of physically accessible oligonucleotides, cDNA, and BAC clones across the entire genome has triggered and accelerated the use of several platforms for analysis of DNA copy number changes, amongst others microarray comparative genomic hybridization (arrayCGH). One of the challenges inherent to this new technology is the management and analysis of large numbers of data points generated in each individual experiment. Results We have developed arrayCGHbase, a comprehensive analysis platform for arrayCGH experiments consisting of a MIAME (Minimal Information About a Microarray Experiment) supportive database using MySQL underlying a data mining web tool, to store, analyze, interpret, compare, and visualize arrayCGH results in a uniform and user-friendly format. Following its flexible design, arrayCGHbase is compatible with all existing and forthcoming arrayCGH platforms. Data can be exported in a multitude of formats, including BED files to map copy number information on the genome using the Ensembl or UCSC genome browser. Conclusion ArrayCGHbase is a web based and platform independent arrayCGH data analysis tool, that allows users to access the analysis suite through the internet or a local intranet after installation on a private server. ArrayCGHbase is available at . PMID:15910681

Construction of an ortholog database using the semantic web technology for integrative analysis of genomic data.

PubMed

Chiba, Hirokazu; Nishide, Hiroyo; Uchiyama, Ikuo

2015-01-01

Recently, various types of biological data, including genomic sequences, have been rapidly accumulating. To discover biological knowledge from such growing heterogeneous data, a flexible framework for data integration is necessary. Ortholog information is a central resource for interlinking corresponding genes among different organisms, and the Semantic Web provides a key technology for the flexible integration of heterogeneous data. We have constructed an ortholog database using the Semantic Web technology, aiming at the integration of numerous genomic data and various types of biological information. To formalize the structure of the ortholog information in the Semantic Web, we have constructed the Ortholog Ontology (OrthO). While the OrthO is a compact ontology for general use, it is designed to be extended to the description of database-specific concepts. On the basis of OrthO, we described the ortholog information from our Microbial Genome Database for Comparative Analysis (MBGD) in the form of Resource Description Framework (RDF) and made it available through the SPARQL endpoint, which accepts arbitrary queries specified by users. In this framework based on the OrthO, the biological data of different organisms can be integrated using the ortholog information as a hub. Besides, the ortholog information from different data sources can be compared with each other using the OrthO as a shared ontology. Here we show some examples demonstrating that the ortholog information described in RDF can be used to link various biological data such as taxonomy information and Gene Ontology. Thus, the ortholog database using the Semantic Web technology can contribute to biological knowledge discovery through integrative data analysis.

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

The Comprehensive Microbial Resource.

PubMed

Peterson, J D; Umayam, L A; Dickinson, T; Hickey, E K; White, O

2001-01-01

One challenge presented by large-scale genome sequencing efforts is effective display of uniform information to the scientific community. The Comprehensive Microbial Resource (CMR) contains robust annotation of all complete microbial genomes and allows for a wide variety of data retrievals. The bacterial information has been placed on the Web at http://www.tigr.org/CMR for retrieval using standard web browsing technology. Retrievals can be based on protein properties such as molecular weight or hydrophobicity, GC-content, functional role assignments and taxonomy. The CMR also has special web-based tools to allow data mining using pre-run homology searches, whole genome dot-plots, batch downloading and traversal across genomes using a variety of datatypes.

GeNets: a unified web platform for network-based genomic analyses.

PubMed

Li, Taibo; Kim, April; Rosenbluh, Joseph; Horn, Heiko; Greenfeld, Liraz; An, David; Zimmer, Andrew; Liberzon, Arthur; Bistline, Jon; Natoli, Ted; Li, Yang; Tsherniak, Aviad; Narayan, Rajiv; Subramanian, Aravind; Liefeld, Ted; Wong, Bang; Thompson, Dawn; Calvo, Sarah; Carr, Steve; Boehm, Jesse; Jaffe, Jake; Mesirov, Jill; Hacohen, Nir; Regev, Aviv; Lage, Kasper

2018-06-18

Functional genomics networks are widely used to identify unexpected pathway relationships in large genomic datasets. However, it is challenging to compare the signal-to-noise ratios of different networks and to identify the optimal network with which to interpret a particular genetic dataset. We present GeNets, a platform in which users can train a machine-learning model (Quack) to carry out these comparisons and execute, store, and share analyses of genetic and RNA-sequencing datasets.

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

phiGENOME: an integrative navigation throughout bacteriophage genomes.

PubMed

Stano, Matej; Klucar, Lubos

2011-11-01

phiGENOME is a web-based genome browser generating dynamic and interactive graphical representation of phage genomes stored in the phiSITE, database of gene regulation in bacteriophages. phiGENOME is an integral part of the phiSITE web portal (http://www.phisite.org/phigenome) and it was optimised for visualisation of phage genomes with the emphasis on the gene regulatory elements. phiGENOME consists of three components: (i) genome map viewer built using Adobe Flash technology, providing dynamic and interactive graphical display of phage genomes; (ii) sequence browser based on precisely formatted HTML tags, providing detailed exploration of genome features on the sequence level and (iii) regulation illustrator, based on Scalable Vector Graphics (SVG) and designed for graphical representation of gene regulations. Bringing 542 complete genome sequences accompanied with their rich annotations and references, makes phiGENOME a unique information resource in the field of phage genomics. Copyright © 2011 Elsevier Inc. All rights reserved.

CloVR-Comparative: automated, cloud-enabled comparative microbial genome sequence analysis pipeline.

PubMed

Agrawal, Sonia; Arze, Cesar; Adkins, Ricky S; Crabtree, Jonathan; Riley, David; Vangala, Mahesh; Galens, Kevin; Fraser, Claire M; Tettelin, Hervé; White, Owen; Angiuoli, Samuel V; Mahurkar, Anup; Fricke, W Florian

2017-04-27

The benefit of increasing genomic sequence data to the scientific community depends on easy-to-use, scalable bioinformatics support. CloVR-Comparative combines commonly used bioinformatics tools into an intuitive, automated, and cloud-enabled analysis pipeline for comparative microbial genomics. CloVR-Comparative runs on annotated complete or draft genome sequences that are uploaded by the user or selected via a taxonomic tree-based user interface and downloaded from NCBI. CloVR-Comparative runs reference-free multiple whole-genome alignments to determine unique, shared and core coding sequences (CDSs) and single nucleotide polymorphisms (SNPs). Output includes short summary reports and detailed text-based results files, graphical visualizations (phylogenetic trees, circular figures), and a database file linked to the Sybil comparative genome browser. Data up- and download, pipeline configuration and monitoring, and access to Sybil are managed through CloVR-Comparative web interface. CloVR-Comparative and Sybil are distributed as part of the CloVR virtual appliance, which runs on local computers or the Amazon EC2 cloud. Representative datasets (e.g. 40 draft and complete Escherichia coli genomes) are processed in <36 h on a local desktop or at a cost of <$20 on EC2. CloVR-Comparative allows anybody with Internet access to run comparative genomics projects, while eliminating the need for on-site computational resources and expertise.

IonGAP: integrative bacterial genome analysis for Ion Torrent sequence data.

PubMed

Baez-Ortega, Adrian; Lorenzo-Diaz, Fabian; Hernandez, Mariano; Gonzalez-Vila, Carlos Ignacio; Roda-Garcia, Jose Luis; Colebrook, Marcos; Flores, Carlos

2015-09-01

We introduce IonGAP, a publicly available Web platform designed for the analysis of whole bacterial genomes using Ion Torrent sequence data. Besides assembly, it integrates a variety of comparative genomics, annotation and bacterial classification routines, based on the widely used FASTQ, BAM and SRA file formats. Benchmarking with different datasets evidenced that IonGAP is a fast, powerful and simple-to-use bioinformatics tool. By releasing this platform, we aim to translate low-cost bacterial genome analysis for microbiological prevention and control in healthcare, agroalimentary and pharmaceutical industry applications. IonGAP is hosted by the ITER's Teide-HPC supercomputer and is freely available on the Web for non-commercial use at http://iongap.hpc.iter.es. mcolesan@ull.edu.es or cflores@ull.edu.es Supplementary data are available at Bioinformatics online. © The Author 2015. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

The Comprehensive Microbial Resource

PubMed Central

Peterson, Jeremy D.; Umayam, Lowell A.; Dickinson, Tanja; Hickey, Erin K.; White, Owen

2001-01-01

One challenge presented by large-scale genome sequencing efforts is effective display of uniform information to the scientific community. The Comprehensive Microbial Resource (CMR) contains robust annotation of all complete microbial genomes and allows for a wide variety of data retrievals. The bacterial information has been placed on the Web at http://www.tigr.org/CMR for retrieval using standard web browsing technology. Retrievals can be based on protein properties such as molecular weight or hydrophobicity, GC-content, functional role assignments and taxonomy. The CMR also has special web-based tools to allow data mining using pre-run homology searches, whole genome dot-plots, batch downloading and traversal across genomes using a variety of datatypes. PMID:11125067

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.

Ensembl comparative genomics resources.

PubMed

Herrero, Javier; Muffato, Matthieu; Beal, Kathryn; Fitzgerald, Stephen; Gordon, Leo; Pignatelli, Miguel; Vilella, Albert J; Searle, Stephen M J; Amode, Ridwan; Brent, Simon; Spooner, William; Kulesha, Eugene; Yates, Andrew; Flicek, Paul

2016-01-01

Evolution provides the unifying framework with which to understand biology. The coherent investigation of genic and genomic data often requires comparative genomics analyses based on whole-genome alignments, sets of homologous genes and other relevant datasets in order to evaluate and answer evolutionary-related questions. However, the complexity and computational requirements of producing such data are substantial: this has led to only a small number of reference resources that are used for most comparative analyses. The Ensembl comparative genomics resources are one such reference set that facilitates comprehensive and reproducible analysis of chordate genome data. Ensembl computes pairwise and multiple whole-genome alignments from which large-scale synteny, per-base conservation scores and constrained elements are obtained. Gene alignments are used to define Ensembl Protein Families, GeneTrees and homologies for both protein-coding and non-coding RNA genes. These resources are updated frequently and have a consistent informatics infrastructure and data presentation across all supported species. Specialized web-based visualizations are also available including synteny displays, collapsible gene tree plots, a gene family locator and different alignment views. The Ensembl comparative genomics infrastructure is extensively reused for the analysis of non-vertebrate species by other projects including Ensembl Genomes and Gramene and much of the information here is relevant to these projects. The consistency of the annotation across species and the focus on vertebrates makes Ensembl an ideal system to perform and support vertebrate comparative genomic analyses. We use robust software and pipelines to produce reference comparative data and make it freely available. Database URL: http://www.ensembl.org. © The Author(s) 2016. Published by Oxford University Press.

Ensembl comparative genomics resources

PubMed Central

Muffato, Matthieu; Beal, Kathryn; Fitzgerald, Stephen; Gordon, Leo; Pignatelli, Miguel; Vilella, Albert J.; Searle, Stephen M. J.; Amode, Ridwan; Brent, Simon; Spooner, William; Kulesha, Eugene; Yates, Andrew; Flicek, Paul

2016-01-01

Evolution provides the unifying framework with which to understand biology. The coherent investigation of genic and genomic data often requires comparative genomics analyses based on whole-genome alignments, sets of homologous genes and other relevant datasets in order to evaluate and answer evolutionary-related questions. However, the complexity and computational requirements of producing such data are substantial: this has led to only a small number of reference resources that are used for most comparative analyses. The Ensembl comparative genomics resources are one such reference set that facilitates comprehensive and reproducible analysis of chordate genome data. Ensembl computes pairwise and multiple whole-genome alignments from which large-scale synteny, per-base conservation scores and constrained elements are obtained. Gene alignments are used to define Ensembl Protein Families, GeneTrees and homologies for both protein-coding and non-coding RNA genes. These resources are updated frequently and have a consistent informatics infrastructure and data presentation across all supported species. Specialized web-based visualizations are also available including synteny displays, collapsible gene tree plots, a gene family locator and different alignment views. The Ensembl comparative genomics infrastructure is extensively reused for the analysis of non-vertebrate species by other projects including Ensembl Genomes and Gramene and much of the information here is relevant to these projects. The consistency of the annotation across species and the focus on vertebrates makes Ensembl an ideal system to perform and support vertebrate comparative genomic analyses. We use robust software and pipelines to produce reference comparative data and make it freely available. Database URL: http://www.ensembl.org. PMID:26896847

BrucellaBase: Genome information resource.

PubMed

Sankarasubramanian, Jagadesan; Vishnu, Udayakumar S; Khader, L K M Abdul; Sridhar, Jayavel; Gunasekaran, Paramasamy; Rajendhran, Jeyaprakash

2016-09-01

Brucella sp. causes a major zoonotic disease, brucellosis. Brucella belongs to the family Brucellaceae under the order Rhizobiales of Alphaproteobacteria. We present BrucellaBase, a web-based platform, providing features of a genome database together with unique analysis tools. We have developed a web version of the multilocus sequence typing (MLST) (Whatmore et al., 2007) and phylogenetic analysis of Brucella spp. BrucellaBase currently contains genome data of 510 Brucella strains along with the user interfaces for BLAST, VFDB, CARD, pairwise genome alignment and MLST typing. Availability of these tools will enable the researchers interested in Brucella to get meaningful information from Brucella genome sequences. BrucellaBase will regularly be updated with new genome sequences, new features along with improvements in genome annotations. BrucellaBase is available online at http://www.dbtbrucellosis.in/brucellabase.html or http://59.99.226.203/brucellabase/homepage.html. Copyright © 2016 Elsevier B.V. All rights reserved.

GenomeD3Plot: a library for rich, interactive visualizations of genomic data in web applications.

PubMed

Laird, Matthew R; Langille, Morgan G I; Brinkman, Fiona S L

2015-10-15

A simple static image of genomes and associated metadata is very limiting, as researchers expect rich, interactive tools similar to the web applications found in the post-Web 2.0 world. GenomeD3Plot is a light weight visualization library written in javascript using the D3 library. GenomeD3Plot provides a rich API to allow the rapid visualization of complex genomic data using a convenient standards based JSON configuration file. When integrated into existing web services GenomeD3Plot allows researchers to interact with data, dynamically alter the view, or even resize or reposition the visualization in their browser window. In addition GenomeD3Plot has built in functionality to export any resulting genome visualization in PNG or SVG format for easy inclusion in manuscripts or presentations. GenomeD3Plot is being utilized in the recently released Islandviewer 3 (www.pathogenomics.sfu.ca/islandviewer/) to visualize predicted genomic islands with other genome annotation data. However, its features enable it to be more widely applicable for dynamic visualization of genomic data in general. GenomeD3Plot is licensed under the GNU-GPL v3 at https://github.com/brinkmanlab/GenomeD3Plot/. brinkman@sfu.ca. © The Author 2015. Published by Oxford University Press.

GrTEdb: the first web-based database of transposable elements in cotton (Gossypium raimondii).

PubMed

Xu, Zhenzhen; Liu, Jing; Ni, Wanchao; Peng, Zhen; Guo, Yue; Ye, Wuwei; Huang, Fang; Zhang, Xianggui; Xu, Peng; Guo, Qi; Shen, Xinlian; Du, Jianchang

2017-01-01

Although several diploid and tetroploid Gossypium species genomes have been sequenced, the well annotated web-based transposable elements (TEs) database is lacking. To better understand the roles of TEs in structural, functional and evolutionary dynamics of the cotton genome, a comprehensive, specific, and user-friendly web-based database, Gossypium raimondii transposable elements database (GrTEdb), was constructed. A total of 14 332 TEs were structurally annotated and clearly categorized in G. raimondii genome, and these elements have been classified into seven distinct superfamilies based on the order of protein-coding domains, structures and/or sequence similarity, including 2929 Copia-like elements, 10 368 Gypsy-like elements, 299 L1 , 12 Mutators , 435 PIF-Harbingers , 275 CACTAs and 14 Helitrons . Meanwhile, the web-based sequence browsing, searching, downloading and blast tool were implemented to help users easily and effectively to annotate the TEs or TE fragments in genomic sequences from G. raimondii and other closely related Gossypium species. GrTEdb provides resources and information related with TEs in G. raimondii , and will facilitate gene and genome analyses within or across Gossypium species, evaluating the impact of TEs on their host genomes, and investigating the potential interaction between TEs and protein-coding genes in Gossypium species. http://www.grtedb.org/. © The Author(s) 2017. Published by Oxford University Press.

GenomeVx: simple web-based creation of editable circular chromosome maps.

PubMed

Conant, Gavin C; Wolfe, Kenneth H

2008-03-15

We describe GenomeVx, a web-based tool for making editable, publication-quality, maps of mitochondrial and chloroplast genomes and of large plasmids. These maps show the location of genes and chromosomal features as well as a position scale. The program takes as input either raw feature positions or GenBank records. In the latter case, features are automatically extracted and colored, an example of which is given. Output is in the Adobe Portable Document Format (PDF) and can be edited by programs such as Adobe Illustrator. GenomeVx is available at http://wolfe.gen.tcd.ie/GenomeVx

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.

Base-By-Base: single nucleotide-level analysis of whole viral genome alignments.

PubMed

Brodie, Ryan; Smith, Alex J; Roper, Rachel L; Tcherepanov, Vasily; Upton, Chris

2004-07-14

With ever increasing numbers of closely related virus genomes being sequenced, it has become desirable to be able to compare two genomes at a level more detailed than gene content because two strains of an organism may share the same set of predicted genes but still differ in their pathogenicity profiles. For example, detailed comparison of multiple isolates of the smallpox virus genome (each approximately 200 kb, with 200 genes) is not feasible without new bioinformatics tools. A software package, Base-By-Base, has been developed that provides visualization tools to enable researchers to 1) rapidly identify and correct alignment errors in large, multiple genome alignments; and 2) generate tabular and graphical output of differences between the genomes at the nucleotide level. Base-By-Base uses detailed annotation information about the aligned genomes and can list each predicted gene with nucleotide differences, display whether variations occur within promoter regions or coding regions and whether these changes result in amino acid substitutions. Base-By-Base can connect to our mySQL database (Virus Orthologous Clusters; VOCs) to retrieve detailed annotation information about the aligned genomes or use information from text files. Base-By-Base enables users to quickly and easily compare large viral genomes; it highlights small differences that may be responsible for important phenotypic differences such as virulence. It is available via the Internet using Java Web Start and runs on Macintosh, PC and Linux operating systems with the Java 1.4 virtual machine.

Genomecmp: computer software to detect genomic rearrangements using markers

NASA Astrophysics Data System (ADS)

Kulawik, Maciej; Nowak, Robert M.

2017-08-01

Detection of genomics rearrangements is a tough task, because of the size of data to be processed. As genome sequences may consist of hundreds of millions symbols, it is not only practically impossible to compare them by hand, but it is also complex problem for computer software. The way to significantly accelerate the process is to use rearrangement detection algorithm based on unique short sequences called markers. The algorithm described in this paper develops markers using base genome and find the markers positions on other genome. The algorithm has been extended by support for ambiguity symbols. Web application with graphical user interface has been created using three-layer architecture, where users could run the task simultaneously. The accuracy and efficiency of proposed solution has been studied using generated and real data.

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.

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

CSTminer: a web tool for the identification of coding and noncoding conserved sequence tags through cross-species genome comparison

PubMed Central

Castrignanò, Tiziana; Canali, Alessandro; Grillo, Giorgio; Liuni, Sabino; Mignone, Flavio; Pesole, Graziano

2004-01-01

The identification and characterization of genome tracts that are highly conserved across species during evolution may contribute significantly to the functional annotation of whole-genome sequences. Indeed, such sequences are likely to correspond to known or unknown coding exons or regulatory motifs. Here, we present a web server implementing a previously developed algorithm that, by comparing user-submitted genome sequences, is able to identify statistically significant conserved blocks and assess their coding or noncoding nature through the measure of a coding potential score. The web tool, available at http://www.caspur.it/CSTminer/, is dynamically interconnected with the Ensembl genome resources and produces a graphical output showing a map of detected conserved sequences and annotated gene features. PMID:15215464

UFO: a web server for ultra-fast functional profiling of whole genome protein sequences.

PubMed

Meinicke, Peter

2009-09-02

Functional profiling is a key technique to characterize and compare the functional potential of entire genomes. The estimation of profiles according to an assignment of sequences to functional categories is a computationally expensive task because it requires the comparison of all protein sequences from a genome with a usually large database of annotated sequences or sequence families. Based on machine learning techniques for Pfam domain detection, the UFO web server for ultra-fast functional profiling allows researchers to process large protein sequence collections instantaneously. Besides the frequencies of Pfam and GO categories, the user also obtains the sequence specific assignments to Pfam domain families. In addition, a comparison with existing genomes provides dissimilarity scores with respect to 821 reference proteomes. Considering the underlying UFO domain detection, the results on 206 test genomes indicate a high sensitivity of the approach. In comparison with current state-of-the-art HMMs, the runtime measurements show a considerable speed up in the range of four orders of magnitude. For an average size prokaryotic genome, the computation of a functional profile together with its comparison typically requires about 10 seconds of processing time. For the first time the UFO web server makes it possible to get a quick overview on the functional inventory of newly sequenced organisms. The genome scale comparison with a large number of precomputed profiles allows a first guess about functionally related organisms. The service is freely available and does not require user registration or specification of a valid email address.

Standard operating procedure for calculating genome-to-genome distances based on high-scoring segment pairs.

PubMed

Auch, Alexander F; Klenk, Hans-Peter; Göker, Markus

2010-01-28

DNA-DNA hybridization (DDH) is a widely applied wet-lab technique to obtain an estimate of the overall similarity between the genomes of two organisms. To base the species concept for prokaryotes ultimately on DDH was chosen by microbiologists as a pragmatic approach for deciding about the recognition of novel species, but also allowed a relatively high degree of standardization compared to other areas of taxonomy. However, DDH is tedious and error-prone and first and foremost cannot be used to incrementally establish a comparative database. Recent studies have shown that in-silico methods for the comparison of genome sequences can be used to replace DDH. Considering the ongoing rapid technological progress of sequencing methods, genome-based prokaryote taxonomy is coming into reach. However, calculating distances between genomes is dependent on multiple choices for software and program settings. We here provide an overview over the modifications that can be applied to distance methods based in high-scoring segment pairs (HSPs) or maximally unique matches (MUMs) and that need to be documented. General recommendations on determining HSPs using BLAST or other algorithms are also provided. As a reference implementation, we introduce the GGDC web server (http://ggdc.gbdp.org).

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

Pfarao: a web application for protein family analysis customized for cytoskeletal and motor proteins (CyMoBase).

PubMed

Odronitz, Florian; Kollmar, Martin

2006-11-29

Annotation of protein sequences of eukaryotic organisms is crucial for the understanding of their function in the cell. Manual annotation is still by far the most accurate way to correctly predict genes. The classification of protein sequences, their phylogenetic relation and the assignment of function involves information from various sources. This often leads to a collection of heterogeneous data, which is hard to track. Cytoskeletal and motor proteins consist of large and diverse superfamilies comprising up to several dozen members per organism. Up to date there is no integrated tool available to assist in the manual large-scale comparative genomic analysis of protein families. Pfarao (Protein Family Application for Retrieval, Analysis and Organisation) is a database driven online working environment for the analysis of manually annotated protein sequences and their relationship. Currently, the system can store and interrelate a wide range of information about protein sequences, species, phylogenetic relations and sequencing projects as well as links to literature and domain predictions. Sequences can be imported from multiple sequence alignments that are generated during the annotation process. A web interface allows to conveniently browse the database and to compile tabular and graphical summaries of its content. We implemented a protein sequence-centric web application to store, organize, interrelate, and present heterogeneous data that is generated in manual genome annotation and comparative genomics. The application has been developed for the analysis of cytoskeletal and motor proteins (CyMoBase) but can easily be adapted for any protein.

Scribl: an HTML5 Canvas-based graphics library for visualizing genomic data over the web.

PubMed

Miller, Chase A; Anthony, Jon; Meyer, Michelle M; Marth, Gabor

2013-02-01

High-throughput biological research requires simultaneous visualization as well as analysis of genomic data, e.g. read alignments, variant calls and genomic annotations. Traditionally, such integrative analysis required desktop applications operating on locally stored data. Many current terabyte-size datasets generated by large public consortia projects, however, are already only feasibly stored at specialist genome analysis centers. As even small laboratories can afford very large datasets, local storage and analysis are becoming increasingly limiting, and it is likely that most such datasets will soon be stored remotely, e.g. in the cloud. These developments will require web-based tools that enable users to access, analyze and view vast remotely stored data with a level of sophistication and interactivity that approximates desktop applications. As rapidly dropping cost enables researchers to collect data intended to answer questions in very specialized contexts, developers must also provide software libraries that empower users to implement customized data analyses and data views for their particular application. Such specialized, yet lightweight, applications would empower scientists to better answer specific biological questions than possible with general-purpose genome browsers currently available. Using recent advances in core web technologies (HTML5), we developed Scribl, a flexible genomic visualization library specifically targeting coordinate-based data such as genomic features, DNA sequence and genetic variants. Scribl simplifies the development of sophisticated web-based graphical tools that approach the dynamism and interactivity of desktop applications. Software is freely available online at http://chmille4.github.com/Scribl/ and is implemented in JavaScript with all modern browsers supported.

G2S: a web-service for annotating genomic variants on 3D protein structures.

PubMed

Wang, Juexin; Sheridan, Robert; Sumer, S Onur; Schultz, Nikolaus; Xu, Dong; Gao, Jianjiong

2018-06-01

Accurately mapping and annotating genomic locations on 3D protein structures is a key step in structure-based analysis of genomic variants detected by recent large-scale sequencing efforts. There are several mapping resources currently available, but none of them provides a web API (Application Programming Interface) that supports programmatic access. We present G2S, a real-time web API that provides automated mapping of genomic variants on 3D protein structures. G2S can align genomic locations of variants, protein locations, or protein sequences to protein structures and retrieve the mapped residues from structures. G2S API uses REST-inspired design and it can be used by various clients such as web browsers, command terminals, programming languages and other bioinformatics tools for bringing 3D structures into genomic variant analysis. The webserver and source codes are freely available at https://g2s.genomenexus.org. g2s@genomenexus.org. Supplementary data are available at Bioinformatics online.

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.

TabPath: interactive tables for metabolic pathway analysis.

PubMed

Moraes, Lauro Ângelo Gonçalves de; Felestrino, Érica Barbosa; Assis, Renata de Almeida Barbosa; Matos, Diogo; Lima, Joubert de Castro; Lima, Leandro de Araújo; Almeida, Nalvo Franco; Setubal, João Carlos; Garcia, Camila Carrião Machado; Moreira, Leandro Marcio

2018-03-15

Information about metabolic pathways in a comparative context is one of the most powerful tool to help the understanding of genome-based differences in phenotypes among organisms. Although several platforms exist that provide a wealth of information on metabolic pathways of diverse organisms, the comparison among organisms using metabolic pathways is still a difficult task. We present TabPath (Tables for Metabolic Pathway), a web-based tool to facilitate comparison of metabolic pathways in genomes based on KEGG. From a selection of pathways and genomes of interest on the menu, TabPath generates user-friendly tables that facilitate analysis of variations in metabolism among the selected organisms. TabPath is available at http://200.239.132.160:8686. lmmorei@gmail.com.

TOPSAN: a dynamic web database for structural genomics.

PubMed

Ellrott, Kyle; Zmasek, Christian M; Weekes, Dana; Sri Krishna, S; Bakolitsa, Constantina; Godzik, Adam; Wooley, John

2011-01-01

The Open Protein Structure Annotation Network (TOPSAN) is a web-based collaboration platform for exploring and annotating structures determined by structural genomics efforts. Characterization of those structures presents a challenge since the majority of the proteins themselves have not yet been characterized. Responding to this challenge, the TOPSAN platform facilitates collaborative annotation and investigation via a user-friendly web-based interface pre-populated with automatically generated information. Semantic web technologies expand and enrich TOPSAN's content through links to larger sets of related databases, and thus, enable data integration from disparate sources and data mining via conventional query languages. TOPSAN can be found at http://www.topsan.org.

GWATCH: a web platform for automated gene association discovery analysis.

PubMed

Svitin, Anton; Malov, Sergey; Cherkasov, Nikolay; Geerts, Paul; Rotkevich, Mikhail; Dobrynin, Pavel; Shevchenko, Andrey; Guan, Li; Troyer, Jennifer; Hendrickson, Sher; Dilks, Holli Hutcheson; Oleksyk, Taras K; Donfield, Sharyne; Gomperts, Edward; Jabs, Douglas A; Sezgin, Efe; Van Natta, Mark; Harrigan, P Richard; Brumme, Zabrina L; O'Brien, Stephen J

2014-01-01

As genome-wide sequence analyses for complex human disease determinants are expanding, it is increasingly necessary to develop strategies to promote discovery and validation of potential disease-gene associations. Here we present a dynamic web-based platform - GWATCH - that automates and facilitates four steps in genetic epidemiological discovery: 1) Rapid gene association search and discovery analysis of large genome-wide datasets; 2) Expanded visual display of gene associations for genome-wide variants (SNPs, indels, CNVs), including Manhattan plots, 2D and 3D snapshots of any gene region, and a dynamic genome browser illustrating gene association chromosomal regions; 3) Real-time validation/replication of candidate or putative genes suggested from other sources, limiting Bonferroni genome-wide association study (GWAS) penalties; 4) Open data release and sharing by eliminating privacy constraints (The National Human Genome Research Institute (NHGRI) Institutional Review Board (IRB), informed consent, The Health Insurance Portability and Accountability Act (HIPAA) of 1996 etc.) on unabridged results, which allows for open access comparative and meta-analysis. GWATCH is suitable for both GWAS and whole genome sequence association datasets. We illustrate the utility of GWATCH with three large genome-wide association studies for HIV-AIDS resistance genes screened in large multicenter cohorts; however, association datasets from any study can be uploaded and analyzed by GWATCH.

Gene Ontology-Based Analysis of Zebrafish Omics Data Using the Web Tool Comparative Gene Ontology.

PubMed

Ebrahimie, Esmaeil; Fruzangohar, Mario; Moussavi Nik, Seyyed Hani; Newman, Morgan

2017-10-01

Gene Ontology (GO) analysis is a powerful tool in systems biology, which uses a defined nomenclature to annotate genes/proteins within three categories: "Molecular Function," "Biological Process," and "Cellular Component." GO analysis can assist in revealing functional mechanisms underlying observed patterns in transcriptomic, genomic, and proteomic data. The already extensive and increasing use of zebrafish for modeling genetic and other diseases highlights the need to develop a GO analytical tool for this organism. The web tool Comparative GO was originally developed for GO analysis of bacterial data in 2013 ( www.comparativego.com ). We have now upgraded and elaborated this web tool for analysis of zebrafish genetic data using GOs and annotations from the Gene Ontology Consortium.

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

A Secure Web Application Providing Public Access to High-Performance Data Intensive Scientific Resources - ScalaBLAST Web Application

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

Curtis, Darren S.; Peterson, Elena S.; Oehmen, Chris S.

2008-05-04

This work presents the ScalaBLAST Web Application (SWA), a web based application implemented using the PHP script language, MySQL DBMS, and Apache web server under a GNU/Linux platform. SWA is an application built as part of the Data Intensive Computer for Complex Biological Systems (DICCBS) project at the Pacific Northwest National Laboratory (PNNL). SWA delivers accelerated throughput of bioinformatics analysis via high-performance computing through a convenient, easy-to-use web interface. This approach greatly enhances emerging fields of study in biology such as ontology-based homology, and multiple whole genome comparisons which, in the absence of a tool like SWA, require a heroicmore » effort to overcome the computational bottleneck associated with genome analysis. The current version of SWA includes a user account management system, a web based user interface, and a backend process that generates the files necessary for the Internet scientific community to submit a ScalaBLAST parallel processing job on a dedicated cluster.« less

Cpf1-Database: web-based genome-wide guide RNA library design for gene knockout screens using CRISPR-Cpf1.

PubMed

Park, Jeongbin; Bae, Sangsu

2018-03-15

Following the type II CRISPR-Cas9 system, type V CRISPR-Cpf1 endonucleases have been found to be applicable for genome editing in various organisms in vivo. However, there are as yet no web-based tools capable of optimally selecting guide RNAs (gRNAs) among all possible genome-wide target sites. Here, we present Cpf1-Database, a genome-wide gRNA library design tool for LbCpf1 and AsCpf1, which have DNA recognition sequences of 5'-TTTN-3' at the 5' ends of target sites. Cpf1-Database provides a sophisticated but simple way to design gRNAs for AsCpf1 nucleases on the genome scale. One can easily access the data using a straightforward web interface, and using the powerful collections feature one can easily design gRNAs for thousands of genes in short time. Free access at http://www.rgenome.net/cpf1-database/. sangsubae@hanyang.ac.kr.

MobilomeFINDER: web-based tools for in silico and experimental discovery of bacterial genomic islands

PubMed Central

Ou, Hong-Yu; He, Xinyi; Harrison, Ewan M.; Kulasekara, Bridget R.; Thani, Ali Bin; Kadioglu, Aras; Lory, Stephen; Hinton, Jay C. D.; Barer, Michael R.; Rajakumar, Kumar

2007-01-01

MobilomeFINDER (http://mml.sjtu.edu.cn/MobilomeFINDER) is an interactive online tool that facilitates bacterial genomic island or ‘mobile genome’ (mobilome) discovery; it integrates the ArrayOme and tRNAcc software packages. ArrayOme utilizes a microarray-derived comparative genomic hybridization input data set to generate ‘inferred contigs’ produced by merging adjacent genes classified as ‘present’. Collectively these ‘fragments’ represent a hypothetical ‘microarray-visualized genome (MVG)’. ArrayOme permits recognition of discordances between physical genome and MVG sizes, thereby enabling identification of strains rich in microarray-elusive novel genes. Individual tRNAcc tools facilitate automated identification of genomic islands by comparative analysis of the contents and contexts of tRNA sites and other integration hotspots in closely related sequenced genomes. Accessory tools facilitate design of hotspot-flanking primers for in silico and/or wet-science-based interrogation of cognate loci in unsequenced strains and analysis of islands for features suggestive of foreign origins; island-specific and genome-contextual features are tabulated and represented in schematic and graphical forms. To date we have used MobilomeFINDER to analyse several Enterobacteriaceae, Pseudomonas aeruginosa and Streptococcus suis genomes. MobilomeFINDER enables high-throughput island identification and characterization through increased exploitation of emerging sequence data and PCR-based profiling of unsequenced test strains; subsequent targeted yeast recombination-based capture permits full-length sequencing and detailed functional studies of novel genomic islands. PMID:17537813

Scribl: an HTML5 Canvas-based graphics library for visualizing genomic data over the web

PubMed Central

Miller, Chase A.; Anthony, Jon; Meyer, Michelle M.; Marth, Gabor

2013-01-01

Motivation: High-throughput biological research requires simultaneous visualization as well as analysis of genomic data, e.g. read alignments, variant calls and genomic annotations. Traditionally, such integrative analysis required desktop applications operating on locally stored data. Many current terabyte-size datasets generated by large public consortia projects, however, are already only feasibly stored at specialist genome analysis centers. As even small laboratories can afford very large datasets, local storage and analysis are becoming increasingly limiting, and it is likely that most such datasets will soon be stored remotely, e.g. in the cloud. These developments will require web-based tools that enable users to access, analyze and view vast remotely stored data with a level of sophistication and interactivity that approximates desktop applications. As rapidly dropping cost enables researchers to collect data intended to answer questions in very specialized contexts, developers must also provide software libraries that empower users to implement customized data analyses and data views for their particular application. Such specialized, yet lightweight, applications would empower scientists to better answer specific biological questions than possible with general-purpose genome browsers currently available. Results: Using recent advances in core web technologies (HTML5), we developed Scribl, a flexible genomic visualization library specifically targeting coordinate-based data such as genomic features, DNA sequence and genetic variants. Scribl simplifies the development of sophisticated web-based graphical tools that approach the dynamism and interactivity of desktop applications. Availability and implementation: Software is freely available online at http://chmille4.github.com/Scribl/ and is implemented in JavaScript with all modern browsers supported. Contact: gabor.marth@bc.edu Supplementary information: Supplementary data are available at Bioinformatics online. PMID:23172864

ChloroMitoCU: Codon patterns across organelle genomes for functional genomics and evolutionary applications.

PubMed

Sablok, Gaurav; Chen, Ting-Wen; Lee, Chi-Ching; Yang, Chi; Gan, Ruei-Chi; Wegrzyn, Jill L; Porta, Nicola L; Nayak, Kinshuk C; Huang, Po-Jung; Varotto, Claudio; Tang, Petrus

2017-06-01

Organelle genomes are widely thought to have arisen from reduction events involving cyanobacterial and archaeal genomes, in the case of chloroplasts, or α-proteobacterial genomes, in the case of mitochondria. Heterogeneity in base composition and codon preference has long been the subject of investigation of topics ranging from phylogenetic distortion to the design of overexpression cassettes for transgenic expression. From the overexpression point of view, it is critical to systematically analyze the codon usage patterns of the organelle genomes. In light of the importance of codon usage patterns in the development of hyper-expression organelle transgenics, we present ChloroMitoCU, the first-ever curated, web-based reference catalog of the codon usage patterns in organelle genomes. ChloroMitoCU contains the pre-compiled codon usage patterns of 328 chloroplast genomes (29,960 CDS) and 3,502 mitochondrial genomes (49,066 CDS), enabling genome-wide exploration and comparative analysis of codon usage patterns across species. ChloroMitoCU allows the phylogenetic comparison of codon usage patterns across organelle genomes, the prediction of codon usage patterns based on user-submitted transcripts or assembled organelle genes, and comparative analysis with the pre-compiled patterns across species of interest. ChloroMitoCU can increase our understanding of the biased patterns of codon usage in organelle genomes across multiple clades. ChloroMitoCU can be accessed at: http://chloromitocu.cgu.edu.tw/. © The Author 2017. Published by Oxford University Press on behalf of Kazusa DNA Research Institute.

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.

GI-POP: a combinational annotation and genomic island prediction pipeline for ongoing microbial genome projects.

PubMed

Lee, Chi-Ching; Chen, Yi-Ping Phoebe; Yao, Tzu-Jung; Ma, Cheng-Yu; Lo, Wei-Cheng; Lyu, Ping-Chiang; Tang, Chuan Yi

2013-04-10

Sequencing of microbial genomes is important because of microbial-carrying antibiotic and pathogenetic activities. However, even with the help of new assembling software, finishing a whole genome is a time-consuming task. In most bacteria, pathogenetic or antibiotic genes are carried in genomic islands. Therefore, a quick genomic island (GI) prediction method is useful for ongoing sequencing genomes. In this work, we built a Web server called GI-POP (http://gipop.life.nthu.edu.tw) which integrates a sequence assembling tool, a functional annotation pipeline, and a high-performance GI predicting module, in a support vector machine (SVM)-based method called genomic island genomic profile scanning (GI-GPS). The draft genomes of the ongoing genome projects in contigs or scaffolds can be submitted to our Web server, and it provides the functional annotation and highly probable GI-predicting results. GI-POP is a comprehensive annotation Web server designed for ongoing genome project analysis. Researchers can perform annotation and obtain pre-analytic information include possible GIs, coding/non-coding sequences and functional analysis from their draft genomes. This pre-analytic system can provide useful information for finishing a genome sequencing project. Copyright © 2012 Elsevier B.V. All rights reserved.

MycoCosm, an Integrated Fungal Genomics Resource

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

Shabalov, Igor; Grigoriev, Igor

2012-03-16

MycoCosm is a web-based interactive fungal genomics resource, which was first released in March 2010, in response to an urgent call from the fungal community for integration of all fungal genomes and analytical tools in one place (Pan-fungal data resources meeting, Feb 21-22, 2010, Alexandria, VA). MycoCosm integrates genomics data and analysis tools to navigate through over 100 fungal genomes sequenced at JGI and elsewhere. This resource allows users to explore fungal genomes in the context of both genome-centric analysis and comparative genomics, and promotes user community participation in data submission, annotation and analysis. MycoCosm has over 4500 unique visitors/monthmore » or 35000+ visitors/year as well as hundreds of registered users contributing their data and expertise to this resource. Its scalable architecture allows significant expansion of the data expected from JGI Fungal Genomics Program, its users, and integration with external resources used by fungal community.« less

dbHiMo: a web-based epigenomics platform for histone-modifying enzymes

PubMed Central

Choi, Jaeyoung; Kim, Ki-Tae; Huh, Aram; Kwon, Seomun; Hong, Changyoung; Asiegbu, Fred O.; Jeon, Junhyun; Lee, Yong-Hwan

2015-01-01

Over the past two decades, epigenetics has evolved into a key concept for understanding regulation of gene expression. Among many epigenetic mechanisms, covalent modifications such as acetylation and methylation of lysine residues on core histones emerged as a major mechanism in epigenetic regulation. Here, we present the database for histone-modifying enzymes (dbHiMo; http://hme.riceblast.snu.ac.kr/) aimed at facilitating functional and comparative analysis of histone-modifying enzymes (HMEs). HMEs were identified by applying a search pipeline built upon profile hidden Markov model (HMM) to proteomes. The database incorporates 11 576 HMEs identified from 603 proteomes including 483 fungal, 32 plants and 51 metazoan species. The dbHiMo provides users with web-based personalized data browsing and analysis tools, supporting comparative and evolutionary genomics. With comprehensive data entries and associated web-based tools, our database will be a valuable resource for future epigenetics/epigenomics studies. Database URL: http://hme.riceblast.snu.ac.kr/ PMID:26055100

dbHiMo: a web-based epigenomics platform for histone-modifying enzymes.

PubMed

Choi, Jaeyoung; Kim, Ki-Tae; Huh, Aram; Kwon, Seomun; Hong, Changyoung; Asiegbu, Fred O; Jeon, Junhyun; Lee, Yong-Hwan

2015-01-01

Over the past two decades, epigenetics has evolved into a key concept for understanding regulation of gene expression. Among many epigenetic mechanisms, covalent modifications such as acetylation and methylation of lysine residues on core histones emerged as a major mechanism in epigenetic regulation. Here, we present the database for histone-modifying enzymes (dbHiMo; http://hme.riceblast.snu.ac.kr/) aimed at facilitating functional and comparative analysis of histone-modifying enzymes (HMEs). HMEs were identified by applying a search pipeline built upon profile hidden Markov model (HMM) to proteomes. The database incorporates 11,576 HMEs identified from 603 proteomes including 483 fungal, 32 plants and 51 metazoan species. The dbHiMo provides users with web-based personalized data browsing and analysis tools, supporting comparative and evolutionary genomics. With comprehensive data entries and associated web-based tools, our database will be a valuable resource for future epigenetics/epigenomics studies. © The Author(s) 2015. Published by Oxford University Press.

Pfarao: a web application for protein family analysis customized for cytoskeletal and motor proteins (CyMoBase)

PubMed Central

Odronitz, Florian; Kollmar, Martin

2006-01-01

Background Annotation of protein sequences of eukaryotic organisms is crucial for the understanding of their function in the cell. Manual annotation is still by far the most accurate way to correctly predict genes. The classification of protein sequences, their phylogenetic relation and the assignment of function involves information from various sources. This often leads to a collection of heterogeneous data, which is hard to track. Cytoskeletal and motor proteins consist of large and diverse superfamilies comprising up to several dozen members per organism. Up to date there is no integrated tool available to assist in the manual large-scale comparative genomic analysis of protein families. Description Pfarao (Protein Family Application for Retrieval, Analysis and Organisation) is a database driven online working environment for the analysis of manually annotated protein sequences and their relationship. Currently, the system can store and interrelate a wide range of information about protein sequences, species, phylogenetic relations and sequencing projects as well as links to literature and domain predictions. Sequences can be imported from multiple sequence alignments that are generated during the annotation process. A web interface allows to conveniently browse the database and to compile tabular and graphical summaries of its content. Conclusion We implemented a protein sequence-centric web application to store, organize, interrelate, and present heterogeneous data that is generated in manual genome annotation and comparative genomics. The application has been developed for the analysis of cytoskeletal and motor proteins (CyMoBase) but can easily be adapted for any protein. PMID:17134497

Cost-effective cloud computing: a case study using the comparative genomics tool, roundup.

PubMed

Kudtarkar, Parul; Deluca, Todd F; Fusaro, Vincent A; Tonellato, Peter J; Wall, Dennis P

2010-12-22

Comparative genomics resources, such as ortholog detection tools and repositories are rapidly increasing in scale and complexity. Cloud computing is an emerging technological paradigm that enables researchers to dynamically build a dedicated virtual cluster and may represent a valuable alternative for large computational tools in bioinformatics. In the present manuscript, we optimize the computation of a large-scale comparative genomics resource-Roundup-using cloud computing, describe the proper operating principles required to achieve computational efficiency on the cloud, and detail important procedures for improving cost-effectiveness to ensure maximal computation at minimal costs. Utilizing the comparative genomics tool, Roundup, as a case study, we computed orthologs among 902 fully sequenced genomes on Amazon's Elastic Compute Cloud. For managing the ortholog processes, we designed a strategy to deploy the web service, Elastic MapReduce, and maximize the use of the cloud while simultaneously minimizing costs. Specifically, we created a model to estimate cloud runtime based on the size and complexity of the genomes being compared that determines in advance the optimal order of the jobs to be submitted. We computed orthologous relationships for 245,323 genome-to-genome comparisons on Amazon's computing cloud, a computation that required just over 200 hours and cost $8,000 USD, at least 40% less than expected under a strategy in which genome comparisons were submitted to the cloud randomly with respect to runtime. Our cost savings projections were based on a model that not only demonstrates the optimal strategy for deploying RSD to the cloud, but also finds the optimal cluster size to minimize waste and maximize usage. Our cost-reduction model is readily adaptable for other comparative genomics tools and potentially of significant benefit to labs seeking to take advantage of the cloud as an alternative to local computing infrastructure.

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

StreptoBase: An Oral Streptococcus mitis Group Genomic Resource and Analysis Platform.

PubMed

Zheng, Wenning; Tan, Tze King; Paterson, Ian C; Mutha, Naresh V R; Siow, Cheuk Chuen; Tan, Shi Yang; Old, Lesley A; Jakubovics, Nicholas S; Choo, Siew Woh

2016-01-01

The oral streptococci are spherical Gram-positive bacteria categorized under the phylum Firmicutes which are among the most common causative agents of bacterial infective endocarditis (IE) and are also important agents in septicaemia in neutropenic patients. The Streptococcus mitis group is comprised of 13 species including some of the most common human oral colonizers such as S. mitis, S. oralis, S. sanguinis and S. gordonii as well as species such as S. tigurinus, S. oligofermentans and S. australis that have only recently been classified and are poorly understood at present. We present StreptoBase, which provides a specialized free resource focusing on the genomic analyses of oral species from the mitis group. It currently hosts 104 S. mitis group genomes including 27 novel mitis group strains that we sequenced using the high throughput Illumina HiSeq technology platform, and provides a comprehensive set of genome sequences for analyses, particularly comparative analyses and visualization of both cross-species and cross-strain characteristics of S. mitis group bacteria. StreptoBase incorporates sophisticated in-house designed bioinformatics web tools such as Pairwise Genome Comparison (PGC) tool and Pathogenomic Profiling Tool (PathoProT), which facilitate comparative pathogenomics analysis of Streptococcus strains. Examples are provided to demonstrate how StreptoBase can be employed to compare genome structure of different S. mitis group bacteria and putative virulence genes profile across multiple streptococcal strains. In conclusion, StreptoBase offers access to a range of streptococci genomic resources as well as analysis tools and will be an invaluable platform to accelerate research in streptococci. Database URL: http://streptococcus.um.edu.my.

CoNVaQ: a web tool for copy number variation-based association studies.

PubMed

Larsen, Simon Jonas; do Canto, Luisa Matos; Rogatto, Silvia Regina; Baumbach, Jan

2018-05-18

Copy number variations (CNVs) are large segments of the genome that are duplicated or deleted. Structural variations in the genome have been linked to many complex diseases. Similar to how genome-wide association studies (GWAS) have helped discover single-nucleotide polymorphisms linked to disease phenotypes, the extension of GWAS to CNVs has aided the discovery of structural variants associated with human traits and diseases. We present CoNVaQ, an easy-to-use web-based tool for CNV-based association studies. The web service allows users to upload two sets of CNV segments and search for genomic regions where the occurrence of CNVs is significantly associated with the phenotype. CoNVaQ provides two models: a simple statistical model using Fisher's exact test and a novel query-based model matching regions to user-defined queries. For each region, the method computes a global q-value statistic by repeated permutation of samples among the populations. We demonstrate our platform by using it to analyze a data set of HPV-positive and HPV-negative penile cancer patients. CoNVaQ provides a simple workflow for performing CNV-based association studies. It is made available as a web platform in order to provide a user-friendly workflow for biologists and clinicians to carry out CNV data analysis without installing any software. Through the web interface, users are also able to analyze their results to find overrepresented GO terms and pathways. In addition, our method is also available as a package for the R programming language. CoNVaQ is available at https://convaq.compbio.sdu.dk .

Ergatis: a web interface and scalable software system for bioinformatics workflows

PubMed Central

Orvis, Joshua; Crabtree, Jonathan; Galens, Kevin; Gussman, Aaron; Inman, Jason M.; Lee, Eduardo; Nampally, Sreenath; Riley, David; Sundaram, Jaideep P.; Felix, Victor; Whitty, Brett; Mahurkar, Anup; Wortman, Jennifer; White, Owen; Angiuoli, Samuel V.

2010-01-01

Motivation: The growth of sequence data has been accompanied by an increasing need to analyze data on distributed computer clusters. The use of these systems for routine analysis requires scalable and robust software for data management of large datasets. Software is also needed to simplify data management and make large-scale bioinformatics analysis accessible and reproducible to a wide class of target users. Results: We have developed a workflow management system named Ergatis that enables users to build, execute and monitor pipelines for computational analysis of genomics data. Ergatis contains preconfigured components and template pipelines for a number of common bioinformatics tasks such as prokaryotic genome annotation and genome comparisons. Outputs from many of these components can be loaded into a Chado relational database. Ergatis was designed to be accessible to a broad class of users and provides a user friendly, web-based interface. Ergatis supports high-throughput batch processing on distributed compute clusters and has been used for data management in a number of genome annotation and comparative genomics projects. Availability: Ergatis is an open-source project and is freely available at http://ergatis.sourceforge.net Contact: jorvis@users.sourceforge.net PMID:20413634

IMGD: an integrated platform supporting comparative genomics and phylogenetics of insect mitochondrial genomes

PubMed Central

Lee, Wonhoon; Park, Jongsun; Choi, Jaeyoung; Jung, Kyongyong; Park, Bongsoo; Kim, Donghan; Lee, Jaeyoung; Ahn, Kyohun; Song, Wonho; Kang, Seogchan; Lee, Yong-Hwan; Lee, Seunghwan

2009-01-01

Background Sequences and organization of the mitochondrial genome have been used as markers to investigate evolutionary history and relationships in many taxonomic groups. The rapidly increasing mitochondrial genome sequences from diverse insects provide ample opportunities to explore various global evolutionary questions in the superclass Hexapoda. To adequately support such questions, it is imperative to establish an informatics platform that facilitates the retrieval and utilization of available mitochondrial genome sequence data. Results The Insect Mitochondrial Genome Database (IMGD) is a new integrated platform that archives the mitochondrial genome sequences from 25,747 hexapod species, including 112 completely sequenced and 20 nearly completed genomes and 113,985 partially sequenced mitochondrial genomes. The Species-driven User Interface (SUI) of IMGD supports data retrieval and diverse analyses at multi-taxon levels. The Phyloviewer implemented in IMGD provides three methods for drawing phylogenetic trees and displays the resulting trees on the web. The SNP database incorporated to IMGD presents the distribution of SNPs and INDELs in the mitochondrial genomes of multiple isolates within eight species. A newly developed comparative SNU Genome Browser supports the graphical presentation and interactive interface for the identified SNPs/INDELs. Conclusion The IMGD provides a solid foundation for the comparative mitochondrial genomics and phylogenetics of insects. All data and functions described here are available at the web site . PMID:19351385

CVTree3 Web Server for Whole-genome-based and Alignment-free Prokaryotic Phylogeny and Taxonomy.

PubMed

Zuo, Guanghong; Hao, Bailin

2015-10-01

A faithful phylogeny and an objective taxonomy for prokaryotes should agree with each other and ultimately follow the genome data. With the number of sequenced genomes reaching tens of thousands, both tree inference and detailed comparison with taxonomy are great challenges. We now provide one solution in the latest Release 3.0 of the alignment-free and whole-genome-based web server CVTree3. The server resides in a cluster of 64 cores and is equipped with an interactive, collapsible, and expandable tree display. It is capable of comparing the tree branching order with prokaryotic classification at all taxonomic ranks from domains down to species and strains. CVTree3 allows for inquiry by taxon names and trial on lineage modifications. In addition, it reports a summary of monophyletic and non-monophyletic taxa at all ranks as well as produces print-quality subtree figures. After giving an overview of retrospective verification of the CVTree approach, the power of the new server is described for the mega-classification of prokaryotes and determination of taxonomic placement of some newly-sequenced genomes. A few discrepancies between CVTree and 16S rRNA analyses are also summarized with regard to possible taxonomic revisions. CVTree3 is freely accessible to all users at http://tlife.fudan.edu.cn/cvtree3/ without login requirements. Copyright © 2015 The Authors. Production and hosting by Elsevier Ltd.. All rights reserved.

CVTree3 Web Server for Whole-genome-based and Alignment-free Prokaryotic Phylogeny and Taxonomy

PubMed Central

Zuo, Guanghong; Hao, Bailin

2015-01-01

A faithful phylogeny and an objective taxonomy for prokaryotes should agree with each other and ultimately follow the genome data. With the number of sequenced genomes reaching tens of thousands, both tree inference and detailed comparison with taxonomy are great challenges. We now provide one solution in the latest Release 3.0 of the alignment-free and whole-genome-based web server CVTree3. The server resides in a cluster of 64 cores and is equipped with an interactive, collapsible, and expandable tree display. It is capable of comparing the tree branching order with prokaryotic classification at all taxonomic ranks from domains down to species and strains. CVTree3 allows for inquiry by taxon names and trial on lineage modifications. In addition, it reports a summary of monophyletic and non-monophyletic taxa at all ranks as well as produces print-quality subtree figures. After giving an overview of retrospective verification of the CVTree approach, the power of the new server is described for the mega-classification of prokaryotes and determination of taxonomic placement of some newly-sequenced genomes. A few discrepancies between CVTree and 16S rRNA analyses are also summarized with regard to possible taxonomic revisions. CVTree3 is freely accessible to all users at http://tlife.fudan.edu.cn/cvtree3/ without login requirements. PMID:26563468

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/.

Microbial Genome Analysis and Comparisons: Web-based Protocols and Resources

USDA-ARS?s Scientific Manuscript database

Fully annotated genome sequences of many microorganisms are publicly available as a resource. However, in-depth analysis of these genomes using specialized tools is required to derive meaningful information. We describe here the utility of three powerful publicly available genome databases and ana...

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.

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

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.

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

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

CAR: contig assembly of prokaryotic draft genomes using rearrangements.

PubMed

Lu, Chin Lung; Chen, Kun-Tze; Huang, Shih-Yuan; Chiu, Hsien-Tai

2014-11-28

Next generation sequencing technology has allowed efficient production of draft genomes for many organisms of interest. However, most draft genomes are just collections of independent contigs, whose relative positions and orientations along the genome being sequenced are unknown. Although several tools have been developed to order and orient the contigs of draft genomes, more accurate tools are still needed. In this study, we present a novel reference-based contig assembly (or scaffolding) tool, named as CAR, that can efficiently and more accurately order and orient the contigs of a prokaryotic draft genome based on a reference genome of a related organism. Given a set of contigs in multi-FASTA format and a reference genome in FASTA format, CAR can output a list of scaffolds, each of which is a set of ordered and oriented contigs. For validation, we have tested CAR on a real dataset composed of several prokaryotic genomes and also compared its performance with several other reference-based contig assembly tools. Consequently, our experimental results have shown that CAR indeed performs better than all these other reference-based contig assembly tools in terms of sensitivity, precision and genome coverage. CAR serves as an efficient tool that can more accurately order and orient the contigs of a prokaryotic draft genome based on a reference genome. The web server of CAR is freely available at http://genome.cs.nthu.edu.tw/CAR/ and its stand-alone program can also be downloaded from the same website.

PARRoT- a homology-based strategy to quantify and compare RNA-sequencing from non-model organisms.

PubMed

Gan, Ruei-Chi; Chen, Ting-Wen; Wu, Timothy H; Huang, Po-Jung; Lee, Chi-Ching; Yeh, Yuan-Ming; Chiu, Cheng-Hsun; Huang, Hsien-Da; Tang, Petrus

2016-12-22

Next-generation sequencing promises the de novo genomic and transcriptomic analysis of samples of interests. However, there are only a few organisms having reference genomic sequences and even fewer having well-defined or curated annotations. For transcriptome studies focusing on organisms lacking proper reference genomes, the common strategy is de novo assembly followed by functional annotation. However, things become even more complicated when multiple transcriptomes are compared. Here, we propose a new analysis strategy and quantification methods for quantifying expression level which not only generate a virtual reference from sequencing data, but also provide comparisons between transcriptomes. First, all reads from the transcriptome datasets are pooled together for de novo assembly. The assembled contigs are searched against NCBI NR databases to find potential homolog sequences. Based on the searched result, a set of virtual transcripts are generated and served as a reference transcriptome. By using the same reference, normalized quantification values including RC (read counts), eRPKM (estimated RPKM) and eTPM (estimated TPM) can be obtained that are comparable across transcriptome datasets. In order to demonstrate the feasibility of our strategy, we implement it in the web service PARRoT. PARRoT stands for Pipeline for Analyzing RNA Reads of Transcriptomes. It analyzes gene expression profiles for two transcriptome sequencing datasets. For better understanding of the biological meaning from the comparison among transcriptomes, PARRoT further provides linkage between these virtual transcripts and their potential function through showing best hits in SwissProt, NR database, assigning GO terms. Our demo datasets showed that PARRoT can analyze two paired-end transcriptomic datasets of approximately 100 million reads within just three hours. In this study, we proposed and implemented a strategy to analyze transcriptomes from non-reference organisms which offers the opportunity to quantify and compare transcriptome profiles through a homolog based virtual transcriptome reference. By using the homolog based reference, our strategy effectively avoids the problems that may cause from inconsistencies among transcriptomes. This strategy will shed lights on the field of comparative genomics for non-model organism. We have implemented PARRoT as a web service which is freely available at http://parrot.cgu.edu.tw .

ADaCGH: A Parallelized Web-Based Application and R Package for the Analysis of aCGH Data

PubMed Central

Díaz-Uriarte, Ramón; Rueda, Oscar M.

2007-01-01

Background Copy number alterations (CNAs) in genomic DNA have been associated with complex human diseases, including cancer. One of the most common techniques to detect CNAs is array-based comparative genomic hybridization (aCGH). The availability of aCGH platforms and the need for identification of CNAs has resulted in a wealth of methodological studies. Methodology/Principal Findings ADaCGH is an R package and a web-based application for the analysis of aCGH data. It implements eight methods for detection of CNAs, gains and losses of genomic DNA, including all of the best performing ones from two recent reviews (CBS, GLAD, CGHseg, HMM). For improved speed, we use parallel computing (via MPI). Additional information (GO terms, PubMed citations, KEGG and Reactome pathways) is available for individual genes, and for sets of genes with altered copy numbers. Conclusions/Significance ADaCGH represents a qualitative increase in the standards of these types of applications: a) all of the best performing algorithms are included, not just one or two; b) we do not limit ourselves to providing a thin layer of CGI on top of existing BioConductor packages, but instead carefully use parallelization, examining different schemes, and are able to achieve significant decreases in user waiting time (factors up to 45×); c) we have added functionality not currently available in some methods, to adapt to recent recommendations (e.g., merging of segmentation results in wavelet-based and CGHseg algorithms); d) we incorporate redundancy, fault-tolerance and checkpointing, which are unique among web-based, parallelized applications; e) all of the code is available under open source licenses, allowing to build upon, copy, and adapt our code for other software projects. PMID:17710137

ADaCGH: A parallelized web-based application and R package for the analysis of aCGH data.

PubMed

Díaz-Uriarte, Ramón; Rueda, Oscar M

2007-08-15

Copy number alterations (CNAs) in genomic DNA have been associated with complex human diseases, including cancer. One of the most common techniques to detect CNAs is array-based comparative genomic hybridization (aCGH). The availability of aCGH platforms and the need for identification of CNAs has resulted in a wealth of methodological studies. ADaCGH is an R package and a web-based application for the analysis of aCGH data. It implements eight methods for detection of CNAs, gains and losses of genomic DNA, including all of the best performing ones from two recent reviews (CBS, GLAD, CGHseg, HMM). For improved speed, we use parallel computing (via MPI). Additional information (GO terms, PubMed citations, KEGG and Reactome pathways) is available for individual genes, and for sets of genes with altered copy numbers. ADACGH represents a qualitative increase in the standards of these types of applications: a) all of the best performing algorithms are included, not just one or two; b) we do not limit ourselves to providing a thin layer of CGI on top of existing BioConductor packages, but instead carefully use parallelization, examining different schemes, and are able to achieve significant decreases in user waiting time (factors up to 45x); c) we have added functionality not currently available in some methods, to adapt to recent recommendations (e.g., merging of segmentation results in wavelet-based and CGHseg algorithms); d) we incorporate redundancy, fault-tolerance and checkpointing, which are unique among web-based, parallelized applications; e) all of the code is available under open source licenses, allowing to build upon, copy, and adapt our code for other software projects.

GreenPhylDB v2.0: comparative and functional genomics in plants.

PubMed

Rouard, Mathieu; Guignon, Valentin; Aluome, Christelle; Laporte, Marie-Angélique; Droc, Gaëtan; Walde, Christian; Zmasek, Christian M; Périn, Christophe; Conte, Matthieu G

2011-01-01

GreenPhylDB is a database designed for comparative and functional genomics based on complete genomes. Version 2 now contains sixteen full genomes of members of the plantae kingdom, ranging from algae to angiosperms, automatically clustered into gene families. Gene families are manually annotated and then analyzed phylogenetically in order to elucidate orthologous and paralogous relationships. The database offers various lists of gene families including plant, phylum and species specific gene families. For each gene cluster or gene family, easy access to gene composition, protein domains, publications, external links and orthologous gene predictions is provided. Web interfaces have been further developed to improve the navigation through information related to gene families. New analysis tools are also available, such as a gene family ontology browser that facilitates exploration. GreenPhylDB is a component of the South Green Bioinformatics Platform (http://southgreen.cirad.fr/) and is accessible at http://greenphyl.cirad.fr. It enables comparative genomics in a broad taxonomy context to enhance the understanding of evolutionary processes and thus tends to speed up gene discovery.

MEGANTE: A Web-Based System for Integrated Plant Genome Annotation

PubMed Central

Numa, Hisataka; Itoh, Takeshi

2014-01-01

The recent advancement of high-throughput genome sequencing technologies has resulted in a considerable increase in demands for large-scale genome annotation. While annotation is a crucial step for downstream data analyses and experimental studies, this process requires substantial expertise and knowledge of bioinformatics. Here we present MEGANTE, a web-based annotation system that makes plant genome annotation easy for researchers unfamiliar with bioinformatics. Without any complicated configuration, users can perform genomic sequence annotations simply by uploading a sequence and selecting the species to query. MEGANTE automatically runs several analysis programs and integrates the results to select the appropriate consensus exon–intron structures and to predict open reading frames (ORFs) at each locus. Functional annotation, including a similarity search against known proteins and a functional domain search, are also performed for the predicted ORFs. The resultant annotation information is visualized with a widely used genome browser, GBrowse. For ease of analysis, the results can be downloaded in Microsoft Excel format. All of the query sequences and annotation results are stored on the server side so that users can access their own data from virtually anywhere on the web. The current release of MEGANTE targets 24 plant species from the Brassicaceae, Fabaceae, Musaceae, Poaceae, Salicaceae, Solanaceae, Rosaceae and Vitaceae families, and it allows users to submit a sequence up to 10 Mb in length and to save up to 100 sequences with the annotation information on the server. The MEGANTE web service is available at https://megante.dna.affrc.go.jp/. PMID:24253915

Cytoscape: the network visualization tool for GenomeSpace workflows.

PubMed

Demchak, Barry; Hull, Tim; Reich, Michael; Liefeld, Ted; Smoot, Michael; Ideker, Trey; Mesirov, Jill P

2014-01-01

Modern genomic analysis often requires workflows incorporating multiple best-of-breed tools. GenomeSpace is a web-based visual workbench that combines a selection of these tools with mechanisms that create data flows between them. One such tool is Cytoscape 3, a popular application that enables analysis and visualization of graph-oriented genomic networks. As Cytoscape runs on the desktop, and not in a web browser, integrating it into GenomeSpace required special care in creating a seamless user experience and enabling appropriate data flows. In this paper, we present the design and operation of the Cytoscape GenomeSpace app, which accomplishes this integration, thereby providing critical analysis and visualization functionality for GenomeSpace users. It has been downloaded over 850 times since the release of its first version in September, 2013.

Cytoscape: the network visualization tool for GenomeSpace workflows

PubMed Central

Demchak, Barry; Hull, Tim; Reich, Michael; Liefeld, Ted; Smoot, Michael; Ideker, Trey; Mesirov, Jill P.

2014-01-01

Modern genomic analysis often requires workflows incorporating multiple best-of-breed tools. GenomeSpace is a web-based visual workbench that combines a selection of these tools with mechanisms that create data flows between them. One such tool is Cytoscape 3, a popular application that enables analysis and visualization of graph-oriented genomic networks. As Cytoscape runs on the desktop, and not in a web browser, integrating it into GenomeSpace required special care in creating a seamless user experience and enabling appropriate data flows. In this paper, we present the design and operation of the Cytoscape GenomeSpace app, which accomplishes this integration, thereby providing critical analysis and visualization functionality for GenomeSpace users. It has been downloaded over 850 times since the release of its first version in September, 2013. PMID:25165537

webMGR: an online tool for the multiple genome rearrangement problem.

PubMed

Lin, Chi Ho; Zhao, Hao; Lowcay, Sean Harry; Shahab, Atif; Bourque, Guillaume

2010-02-01

The algorithm MGR enables the reconstruction of rearrangement phylogenies based on gene or synteny block order in multiple genomes. Although MGR has been successfully applied to study the evolution of different sets of species, its utilization has been hampered by the prohibitive running time for some applications. In the current work, we have designed new heuristics that significantly speed up the tool without compromising its accuracy. Moreover, we have developed a web server (webMGR) that includes elaborate web output to facilitate navigation through the results. webMGR can be accessed via http://www.gis.a-star.edu.sg/~bourque. The source code of the improved standalone version of MGR is also freely available from the web site. Supplementary data are available at Bioinformatics online.

Design and Implementation of a Randomized Controlled Trial of Genomic Counseling for Patients with Chronic Disease

PubMed Central

Sweet, Kevin; Gordon, Erynn S.; Sturm, Amy C.; Schmidlen, Tara J.; Manickam, Kandamurugu; Toland, Amanda Ewart; Keller, Margaret A.; Stack, Catharine B.; García-España, J. Felipe; Bellafante, Mark; Tayal, Neeraj; Embi, Peter; Binkley, Philip; Hershberger, Ray E.; Sadee, Wolfgang; Christman, Michael; Marsh, Clay

2014-01-01

We describe the development and implementation of a randomized controlled trial to investigate the impact of genomic counseling on a cohort of patients with heart failure (HF) or hypertension (HTN), managed at a large academic medical center, the Ohio State University Wexner Medical Center (OSUWMC). Our study is built upon the existing Coriell Personalized Medicine Collaborative (CPMC®). OSUWMC patient participants with chronic disease (CD) receive eight actionable complex disease and one pharmacogenomic test report through the CPMC® web portal. Participants are randomized to either the in-person post-test genomic counseling—active arm, versus web-based only return of results—control arm. Study-specific surveys measure: (1) change in risk perception; (2) knowledge retention; (3) perceived personal control; (4) health behavior change; and, for the active arm (5), overall satisfaction with genomic counseling. This ongoing partnership has spurred creation of both infrastructure and procedures necessary for the implementation of genomics and genomic counseling in clinical care and clinical research. This included creation of a comprehensive informed consent document and processes for prospective return of actionable results for multiple complex diseases and pharmacogenomics (PGx) through a web portal, and integration of genomic data files and clinical decision support into an EPIC-based electronic medical record. We present this partnership, the infrastructure, genomic counseling approach, and the challenges that arose in the design and conduct of this ongoing trial to inform subsequent collaborative efforts and best genomic counseling practices. PMID:24926413

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

WEbcoli: an interactive and asynchronous web application for in silico design and analysis of genome-scale E.coli model.

PubMed

Jung, Tae-Sung; Yeo, Hock Chuan; Reddy, Satty G; Cho, Wan-Sup; Lee, Dong-Yup

2009-11-01

WEbcoli is a WEb application for in silico designing, analyzing and engineering Escherichia coli metabolism. It is devised and implemented using advanced web technologies, thereby leading to enhanced usability and dynamic web accessibility. As a main feature, the WEbcoli system provides a user-friendly rich web interface, allowing users to virtually design and synthesize mutant strains derived from the genome-scale wild-type E.coli model and to customize pathways of interest through a graph editor. In addition, constraints-based flux analysis can be conducted for quantifying metabolic fluxes and charactering the physiological and metabolic states under various genetic and/or environmental conditions. WEbcoli is freely accessible at http://webcoli.org. cheld@nus.edu.sg.

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.

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/ .

Reads2Type: a web application for rapid microbial taxonomy identification.

PubMed

Saputra, Dhany; Rasmussen, Simon; Larsen, Mette V; Haddad, Nizar; Sperotto, Maria Maddalena; Aarestrup, Frank M; Lund, Ole; Sicheritz-Pontén, Thomas

2015-11-25

Identification of bacteria may be based on sequencing and molecular analysis of a specific locus such as 16S rRNA, or a set of loci such as in multilocus sequence typing. In the near future, healthcare institutions and routine diagnostic microbiology laboratories may need to sequence the entire genome of microbial isolates. Therefore we have developed Reads2Type, a web-based tool for taxonomy identification based on whole bacterial genome sequence data. Raw sequencing data provided by the user are mapped against a set of marker probes that are derived from currently available bacteria complete genomes. Using a dataset of 1003 whole genome sequenced bacteria from various sequencing platforms, Reads2Type was able to identify the species with 99.5 % accuracy and on the minutes time scale. In comparison with other tools, Reads2Type offers the advantage of not needing to transfer sequencing files, as the entire computational analysis is done on the computer of whom utilizes the web application. This also prevents data privacy issues to arise. The Reads2Type tool is available at http://www.cbs.dtu.dk/~dhany/reads2type.html.

Essie: A Concept-based Search Engine for Structured Biomedical Text

PubMed Central

Ide, Nicholas C.; Loane, Russell F.; Demner-Fushman, Dina

2007-01-01

This article describes the algorithms implemented in the Essie search engine that is currently serving several Web sites at the National Library of Medicine. Essie is a phrase-based search engine with term and concept query expansion and probabilistic relevancy ranking. Essie’s design is motivated by an observation that query terms are often conceptually related to terms in a document, without actually occurring in the document text. Essie’s performance was evaluated using data and standard evaluation methods from the 2003 and 2006 Text REtrieval Conference (TREC) Genomics track. Essie was the best-performing search engine in the 2003 TREC Genomics track and achieved results comparable to those of the highest-ranking systems on the 2006 TREC Genomics track task. Essie shows that a judicious combination of exploiting document structure, phrase searching, and concept based query expansion is a useful approach for information retrieval in the biomedical domain. PMID:17329729

Sinbase: an integrated database to study genomics, genetics and comparative genomics in Sesamum indicum.

PubMed

Wang, Linhai; Yu, Jingyin; Li, Donghua; Zhang, Xiurong

2015-01-01

Sesame (Sesamum indicum L.) is an ancient and important oilseed crop grown widely in tropical and subtropical areas. It belongs to the gigantic order Lamiales, which includes many well-known or economically important species, such as olive (Olea europaea), leonurus (Leonurus japonicus) and lavender (Lavandula spica), many of which have important pharmacological properties. Despite their importance, genetic and genomic analyses on these species have been insufficient due to a lack of reference genome information. The now available S. indicum genome will provide an unprecedented opportunity for studying both S. indicum genetic traits and comparative genomics. To deliver S. indicum genomic information to the worldwide research community, we designed Sinbase, a web-based database with comprehensive sesame genomic, genetic and comparative genomic information. Sinbase includes sequences of assembled sesame pseudomolecular chromosomes, protein-coding genes (27,148), transposable elements (372,167) and non-coding RNAs (1,748). In particular, Sinbase provides unique and valuable information on colinear regions with various plant genomes, including Arabidopsis thaliana, Glycine max, Vitis vinifera and Solanum lycopersicum. Sinbase also provides a useful search function and data mining tools, including a keyword search and local BLAST service. Sinbase will be updated regularly with new features, improvements to genome annotation and new genomic sequences, and is freely accessible at http://ocri-genomics.org/Sinbase/. © The Author 2014. Published by Oxford University Press on behalf of Japanese Society of Plant Physiologists. All rights reserved. For permissions, please email: journals.permissions@oup.com.

Cost-Effective Cloud Computing: A Case Study Using the Comparative Genomics Tool, Roundup

PubMed Central

Kudtarkar, Parul; DeLuca, Todd F.; Fusaro, Vincent A.; Tonellato, Peter J.; Wall, Dennis P.

2010-01-01

Background Comparative genomics resources, such as ortholog detection tools and repositories are rapidly increasing in scale and complexity. Cloud computing is an emerging technological paradigm that enables researchers to dynamically build a dedicated virtual cluster and may represent a valuable alternative for large computational tools in bioinformatics. In the present manuscript, we optimize the computation of a large-scale comparative genomics resource—Roundup—using cloud computing, describe the proper operating principles required to achieve computational efficiency on the cloud, and detail important procedures for improving cost-effectiveness to ensure maximal computation at minimal costs. Methods Utilizing the comparative genomics tool, Roundup, as a case study, we computed orthologs among 902 fully sequenced genomes on Amazon’s Elastic Compute Cloud. For managing the ortholog processes, we designed a strategy to deploy the web service, Elastic MapReduce, and maximize the use of the cloud while simultaneously minimizing costs. Specifically, we created a model to estimate cloud runtime based on the size and complexity of the genomes being compared that determines in advance the optimal order of the jobs to be submitted. Results We computed orthologous relationships for 245,323 genome-to-genome comparisons on Amazon’s computing cloud, a computation that required just over 200 hours and cost $8,000 USD, at least 40% less than expected under a strategy in which genome comparisons were submitted to the cloud randomly with respect to runtime. Our cost savings projections were based on a model that not only demonstrates the optimal strategy for deploying RSD to the cloud, but also finds the optimal cluster size to minimize waste and maximize usage. Our cost-reduction model is readily adaptable for other comparative genomics tools and potentially of significant benefit to labs seeking to take advantage of the cloud as an alternative to local computing infrastructure. PMID:21258651

A physical map of Brassica oleracea shows complexity of chromosomal changes following recursive paleopolyploidizations

PubMed Central

2011-01-01

Background Evolution of the Brassica species has been recursively affected by polyploidy events, and comparison to their relative, Arabidopsis thaliana, provides means to explore their genomic complexity. Results A genome-wide physical map of a rapid-cycling strain of B. oleracea was constructed by integrating high-information-content fingerprinting (HICF) of Bacterial Artificial Chromosome (BAC) clones with hybridization to sequence-tagged probes. Using 2907 contigs of two or more BACs, we performed several lines of comparative genomic analysis. Interspecific DNA synteny is much better preserved in euchromatin than heterochromatin, showing the qualitative difference in evolution of these respective genomic domains. About 67% of contigs can be aligned to the Arabidopsis genome, with 96.5% corresponding to euchromatic regions, and 3.5% (shown to contain repetitive sequences) to pericentromeric regions. Overgo probe hybridization data showed that contigs aligned to Arabidopsis euchromatin contain ~80% of low-copy-number genes, while genes with high copy number are much more frequently associated with pericentromeric regions. We identified 39 interchromosomal breakpoints during the diversification of B. oleracea and Arabidopsis thaliana, a relatively high level of genomic change since their divergence. Comparison of the B. oleracea physical map with Arabidopsis and other available eudicot genomes showed appreciable 'shadowing' produced by more ancient polyploidies, resulting in a web of relatedness among contigs which increased genomic complexity. Conclusions A high-resolution genetically-anchored physical map sheds light on Brassica genome organization and advances positional cloning of specific genes, and may help to validate genome sequence assembly and alignment to chromosomes. All the physical mapping data is freely shared at a WebFPC site (http://lulu.pgml.uga.edu/fpc/WebAGCoL/brassica/WebFPC/; Temporarily password-protected: account: pgml; password: 123qwe123. PMID:21955929

YouGenMap: a web platform for dynamic multi-comparative mapping and visualization of genetic maps

Treesearch

Keith Batesole; Kokulapalan Wimalanathan; Lin Liu; Fan Zhang; Craig S. Echt; Chun Liang

2014-01-01

Comparative genetic maps are used in examination of genome organization, detection of conserved gene order, and exploration of marker order variations. YouGenMap is an open-source web tool that offers dynamic comparative mapping capability of users' own genetic mapping between 2 or more map sets. Users' genetic map data and optional gene annotations are...

Enabling the democratization of the genomics revolution with a fully integrated web-based bioinformatics platform, Version 1.5 and 1.x.

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

Chain, Patrick; Lo, Chien-Chi; Li, Po-E

EDGE bioinformatics was developed to help biologists process Next Generation Sequencing data (in the form of raw FASTQ files), even if they have little to no bioinformatics expertise. EDGE is a highly integrated and interactive web-based platform that is capable of running many of the standard analyses that biologists require for viral, bacterial/archaeal, and metagenomic samples. EDGE provides the following analytical workflows: quality trimming and host removal, assembly and annotation, comparisons against known references, taxonomy classification of reads and contigs, whole genome SNP-based phylogenetic analysis, and PCR analysis. EDGE provides an intuitive web-based interface for user input, allows users tomore » visualize and interact with selected results (e.g. JBrowse genome browser), and generates a final detailed PDF report. Results in the form of tables, text files, graphic files, and PDFs can be downloaded. A user management system allows tracking of an individual’s EDGE runs, along with the ability to share, post publicly, delete, or archive their results.« less

PigGIS: Pig Genomic Informatics System

PubMed Central

Ruan, Jue; Guo, Yiran; Li, Heng; Hu, Yafeng; Song, Fei; Huang, Xin; Kristiensen, Karsten; Bolund, Lars; Wang, Jun

2007-01-01

Pig Genomic Information System (PigGIS) is a web-based depository of pig (Sus scrofa) genomic learning mainly engineered for biomedical research to locate pig genes from their human homologs and position single nucleotide polymorphisms (SNPs) in different pig populations. It utilizes a variety of sequence data, including whole genome shotgun (WGS) reads and expressed sequence tags (ESTs), and achieves a successful mapping solution to the low-coverage genome problem. With the data presently available, we have identified a total of 15 700 pig consensus sequences covering 18.5 Mb of the homologous human exons. We have also recovered 18 700 SNPs and 20 800 unique 60mer oligonucleotide probes for future pig genome analyses. PigGIS can be freely accessed via the web at and . PMID:17090590

Soybean Knowledge Base (SoyKB): a Web Resource for Soybean Translational Genomics

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

Joshi, Trupti; Patil, Kapil; Fitzpatrick, Michael R.

2012-01-17

Background: Soybean Knowledge Base (SoyKB) is a comprehensive all-inclusive web resource for soybean translational genomics. SoyKB is designed to handle the management and integration of soybean genomics, transcriptomics, proteomics and metabolomics data along with annotation of gene function and biological pathway. It contains information on four entities, namely genes, microRNAs, metabolites and single nucleotide polymorphisms (SNPs). Methods: SoyKB has many useful tools such as Affymetrix probe ID search, gene family search, multiple gene/ metabolite search supporting co-expression analysis, and protein 3D structure viewer as well as download and upload capacity for experimental data and annotations. It has four tiers ofmore » registration, which control different levels of access to public and private data. It allows users of certain levels to share their expertise by adding comments to the data. It has a user-friendly web interface together with genome browser and pathway viewer, which display data in an intuitive manner to the soybean researchers, producers and consumers. Conclusions: SoyKB addresses the increasing need of the soybean research community to have a one-stop-shop functional and translational omics web resource for information retrieval and analysis in a user-friendly way. SoyKB can be publicly accessed at http://soykb.org/.« less

SeMPI: a genome-based secondary metabolite prediction and identification web server.

PubMed

Zierep, Paul F; Padilla, Natàlia; Yonchev, Dimitar G; Telukunta, Kiran K; Klementz, Dennis; Günther, Stefan

2017-07-03

The secondary metabolism of bacteria, fungi and plants yields a vast number of bioactive substances. The constantly increasing amount of published genomic data provides the opportunity for an efficient identification of gene clusters by genome mining. Conversely, for many natural products with resolved structures, the encoding gene clusters have not been identified yet. Even though genome mining tools have become significantly more efficient in the identification of biosynthetic gene clusters, structural elucidation of the actual secondary metabolite is still challenging, especially due to as yet unpredictable post-modifications. Here, we introduce SeMPI, a web server providing a prediction and identification pipeline for natural products synthesized by polyketide synthases of type I modular. In order to limit the possible structures of PKS products and to include putative tailoring reactions, a structural comparison with annotated natural products was introduced. Furthermore, a benchmark was designed based on 40 gene clusters with annotated PKS products. The web server of the pipeline (SeMPI) is freely available at: http://www.pharmaceutical-bioinformatics.de/sempi. © The Author(s) 2017. Published by Oxford University Press on behalf of Nucleic Acids Research.

MicroScope: a platform for microbial genome annotation and comparative genomics

PubMed Central

Vallenet, D.; Engelen, S.; Mornico, D.; Cruveiller, S.; Fleury, L.; Lajus, A.; Rouy, Z.; Roche, D.; Salvignol, G.; Scarpelli, C.; Médigue, C.

2009-01-01

The initial outcome of genome sequencing is the creation of long text strings written in a four letter alphabet. The role of in silico sequence analysis is to assist biologists in the act of associating biological knowledge with these sequences, allowing investigators to make inferences and predictions that can be tested experimentally. A wide variety of software is available to the scientific community, and can be used to identify genomic objects, before predicting their biological functions. However, only a limited number of biologically interesting features can be revealed from an isolated sequence. Comparative genomics tools, on the other hand, by bringing together the information contained in numerous genomes simultaneously, allow annotators to make inferences based on the idea that evolution and natural selection are central to the definition of all biological processes. We have developed the MicroScope platform in order to offer a web-based framework for the systematic and efficient revision of microbial genome annotation and comparative analysis (http://www.genoscope.cns.fr/agc/microscope). Starting with the description of the flow chart of the annotation processes implemented in the MicroScope pipeline, and the development of traditional and novel microbial annotation and comparative analysis tools, this article emphasizes the essential role of expert annotation as a complement of automatic annotation. Several examples illustrate the use of implemented tools for the review and curation of annotations of both new and publicly available microbial genomes within MicroScope’s rich integrated genome framework. The platform is used as a viewer in order to browse updated annotation information of available microbial genomes (more than 440 organisms to date), and in the context of new annotation projects (117 bacterial genomes). The human expertise gathered in the MicroScope database (about 280,000 independent annotations) contributes to improve the quality of microbial genome annotation, especially for genomes initially analyzed by automatic procedures alone. Database URLs: http://www.genoscope.cns.fr/agc/mage and http://www.genoscope.cns.fr/agc/microcyc PMID:20157493

MicroScope: a platform for microbial genome annotation and comparative genomics.

PubMed

Vallenet, D; Engelen, S; Mornico, D; Cruveiller, S; Fleury, L; Lajus, A; Rouy, Z; Roche, D; Salvignol, G; Scarpelli, C; Médigue, C

2009-01-01

The initial outcome of genome sequencing is the creation of long text strings written in a four letter alphabet. The role of in silico sequence analysis is to assist biologists in the act of associating biological knowledge with these sequences, allowing investigators to make inferences and predictions that can be tested experimentally. A wide variety of software is available to the scientific community, and can be used to identify genomic objects, before predicting their biological functions. However, only a limited number of biologically interesting features can be revealed from an isolated sequence. Comparative genomics tools, on the other hand, by bringing together the information contained in numerous genomes simultaneously, allow annotators to make inferences based on the idea that evolution and natural selection are central to the definition of all biological processes. We have developed the MicroScope platform in order to offer a web-based framework for the systematic and efficient revision of microbial genome annotation and comparative analysis (http://www.genoscope.cns.fr/agc/microscope). Starting with the description of the flow chart of the annotation processes implemented in the MicroScope pipeline, and the development of traditional and novel microbial annotation and comparative analysis tools, this article emphasizes the essential role of expert annotation as a complement of automatic annotation. Several examples illustrate the use of implemented tools for the review and curation of annotations of both new and publicly available microbial genomes within MicroScope's rich integrated genome framework. The platform is used as a viewer in order to browse updated annotation information of available microbial genomes (more than 440 organisms to date), and in the context of new annotation projects (117 bacterial genomes). The human expertise gathered in the MicroScope database (about 280,000 independent annotations) contributes to improve the quality of microbial genome annotation, especially for genomes initially analyzed by automatic procedures alone.Database URLs: http://www.genoscope.cns.fr/agc/mage and http://www.genoscope.cns.fr/agc/microcyc.

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.

The Aspergillus Genome Database: multispecies curation and incorporation of RNA-Seq data to improve structural gene annotations.

PubMed

Cerqueira, Gustavo C; Arnaud, Martha B; Inglis, Diane O; Skrzypek, Marek S; Binkley, Gail; Simison, Matt; Miyasato, Stuart R; Binkley, Jonathan; Orvis, Joshua; Shah, Prachi; Wymore, Farrell; Sherlock, Gavin; Wortman, Jennifer R

2014-01-01

The Aspergillus Genome Database (AspGD; http://www.aspgd.org) is a freely available web-based resource that was designed for Aspergillus researchers and is also a valuable source of information for the entire fungal research community. In addition to being a repository and central point of access to genome, transcriptome and polymorphism data, AspGD hosts a comprehensive comparative genomics toolbox that facilitates the exploration of precomputed orthologs among the 20 currently available Aspergillus genomes. AspGD curators perform gene product annotation based on review of the literature for four key Aspergillus species: Aspergillus nidulans, Aspergillus oryzae, Aspergillus fumigatus and Aspergillus niger. We have iteratively improved the structural annotation of Aspergillus genomes through the analysis of publicly available transcription data, mostly expressed sequenced tags, as described in a previous NAR Database article (Arnaud et al. 2012). In this update, we report substantive structural annotation improvements for A. nidulans, A. oryzae and A. fumigatus genomes based on recently available RNA-Seq data. Over 26 000 loci were updated across these species; although those primarily comprise the addition and extension of untranslated regions (UTRs), the new analysis also enabled over 1000 modifications affecting the coding sequence of genes in each target genome.

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

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

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

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

BμG@Sbase—a microbial gene expression and comparative genomic database

PubMed Central

Witney, Adam A.; Waldron, Denise E.; Brooks, Lucy A.; Tyler, Richard H.; Withers, Michael; Stoker, Neil G.; Wren, Brendan W.; Butcher, Philip D.; Hinds, Jason

2012-01-01

The reducing cost of high-throughput functional genomic technologies is creating a deluge of high volume, complex data, placing the burden on bioinformatics resources and tool development. The Bacterial Microarray Group at St George's (BμG@S) has been at the forefront of bacterial microarray design and analysis for over a decade and while serving as a hub of a global network of microbial research groups has developed BμG@Sbase, a microbial gene expression and comparative genomic database. BμG@Sbase (http://bugs.sgul.ac.uk/bugsbase/) is a web-browsable, expertly curated, MIAME-compliant database that stores comprehensive experimental annotation and multiple raw and analysed data formats. Consistent annotation is enabled through a structured set of web forms, which guide the user through the process following a set of best practices and controlled vocabulary. The database currently contains 86 expertly curated publicly available data sets (with a further 124 not yet published) and full annotation information for 59 bacterial microarray designs. The data can be browsed and queried using an explorer-like interface; integrating intuitive tree diagrams to present complex experimental details clearly and concisely. Furthermore the modular design of the database will provide a robust platform for integrating other data types beyond microarrays into a more Systems analysis based future. PMID:21948792

BμG@Sbase--a microbial gene expression and comparative genomic database.

PubMed

Witney, Adam A; Waldron, Denise E; Brooks, Lucy A; Tyler, Richard H; Withers, Michael; Stoker, Neil G; Wren, Brendan W; Butcher, Philip D; Hinds, Jason

2012-01-01

The reducing cost of high-throughput functional genomic technologies is creating a deluge of high volume, complex data, placing the burden on bioinformatics resources and tool development. The Bacterial Microarray Group at St George's (BμG@S) has been at the forefront of bacterial microarray design and analysis for over a decade and while serving as a hub of a global network of microbial research groups has developed BμG@Sbase, a microbial gene expression and comparative genomic database. BμG@Sbase (http://bugs.sgul.ac.uk/bugsbase/) is a web-browsable, expertly curated, MIAME-compliant database that stores comprehensive experimental annotation and multiple raw and analysed data formats. Consistent annotation is enabled through a structured set of web forms, which guide the user through the process following a set of best practices and controlled vocabulary. The database currently contains 86 expertly curated publicly available data sets (with a further 124 not yet published) and full annotation information for 59 bacterial microarray designs. The data can be browsed and queried using an explorer-like interface; integrating intuitive tree diagrams to present complex experimental details clearly and concisely. Furthermore the modular design of the database will provide a robust platform for integrating other data types beyond microarrays into a more Systems analysis based future.

Data partitioning enables the use of standard SOAP Web Services in genome-scale workflows.

PubMed

Sztromwasser, Pawel; Puntervoll, Pål; Petersen, Kjell

2011-07-26

Biological databases and computational biology tools are provided by research groups around the world, and made accessible on the Web. Combining these resources is a common practice in bioinformatics, but integration of heterogeneous and often distributed tools and datasets can be challenging. To date, this challenge has been commonly addressed in a pragmatic way, by tedious and error-prone scripting. Recently however a more reliable technique has been identified and proposed as the platform that would tie together bioinformatics resources, namely Web Services. In the last decade the Web Services have spread wide in bioinformatics, and earned the title of recommended technology. However, in the era of high-throughput experimentation, a major concern regarding Web Services is their ability to handle large-scale data traffic. We propose a stream-like communication pattern for standard SOAP Web Services, that enables efficient flow of large data traffic between a workflow orchestrator and Web Services. We evaluated the data-partitioning strategy by comparing it with typical communication patterns on an example pipeline for genomic sequence annotation. The results show that data-partitioning lowers resource demands of services and increases their throughput, which in consequence allows to execute in-silico experiments on genome-scale, using standard SOAP Web Services and workflows. As a proof-of-principle we annotated an RNA-seq dataset using a plain BPEL workflow engine.

DMINDA: an integrated web server for DNA motif identification and analyses

PubMed Central

Ma, Qin; Zhang, Hanyuan; Mao, Xizeng; Zhou, Chuan; Liu, Bingqiang; Chen, Xin; Xu, Ying

2014-01-01

DMINDA (DNA motif identification and analyses) is an integrated web server for DNA motif identification and analyses, which is accessible at http://csbl.bmb.uga.edu/DMINDA/. This web site is freely available to all users and there is no login requirement. This server provides a suite of cis-regulatory motif analysis functions on DNA sequences, which are important to elucidation of the mechanisms of transcriptional regulation: (i) de novo motif finding for a given set of promoter sequences along with statistical scores for the predicted motifs derived based on information extracted from a control set, (ii) scanning motif instances of a query motif in provided genomic sequences, (iii) motif comparison and clustering of identified motifs, and (iv) co-occurrence analyses of query motifs in given promoter sequences. The server is powered by a backend computer cluster with over 150 computing nodes, and is particularly useful for motif prediction and analyses in prokaryotic genomes. We believe that DMINDA, as a new and comprehensive web server for cis-regulatory motif finding and analyses, will benefit the genomic research community in general and prokaryotic genome researchers in particular. PMID:24753419

GEM System: automatic prototyping of cell-wide metabolic pathway models from genomes.

PubMed

Arakawa, Kazuharu; Yamada, Yohei; Shinoda, Kosaku; Nakayama, Yoichi; Tomita, Masaru

2006-03-23

Successful realization of a "systems biology" approach to analyzing cells is a grand challenge for our understanding of life. However, current modeling approaches to cell simulation are labor-intensive, manual affairs, and therefore constitute a major bottleneck in the evolution of computational cell biology. We developed the Genome-based Modeling (GEM) System for the purpose of automatically prototyping simulation models of cell-wide metabolic pathways from genome sequences and other public biological information. Models generated by the GEM System include an entire Escherichia coli metabolism model comprising 968 reactions of 1195 metabolites, achieving 100% coverage when compared with the KEGG database, 92.38% with the EcoCyc database, and 95.06% with iJR904 genome-scale model. The GEM System prototypes qualitative models to reduce the labor-intensive tasks required for systems biology research. Models of over 90 bacterial genomes are available at our web site.

PhytoCRISP-Ex: a web-based and stand-alone application to find specific target sequences for CRISPR/CAS editing.

PubMed

Rastogi, Achal; Murik, Omer; Bowler, Chris; Tirichine, Leila

2016-07-01

With the emerging interest in phytoplankton research, the need to establish genetic tools for the functional characterization of genes is indispensable. The CRISPR/Cas9 system is now well recognized as an efficient and accurate reverse genetic tool for genome editing. Several computational tools have been published allowing researchers to find candidate target sequences for the engineering of the CRISPR vectors, while searching possible off-targets for the predicted candidates. These tools provide built-in genome databases of common model organisms that are used for CRISPR target prediction. Although their predictions are highly sensitive, the applicability to non-model genomes, most notably protists, makes their design inadequate. This motivated us to design a new CRISPR target finding tool, PhytoCRISP-Ex. Our software offers CRIPSR target predictions using an extended list of phytoplankton genomes and also delivers a user-friendly standalone application that can be used for any genome. The software attempts to integrate, for the first time, most available phytoplankton genomes information and provide a web-based platform for Cas9 target prediction within them with high sensitivity. By offering a standalone version, PhytoCRISP-Ex maintains an independence to be used with any organism and widens its applicability in high throughput pipelines. PhytoCRISP-Ex out pars all the existing tools by computing the availability of restriction sites over the most probable Cas9 cleavage sites, which can be ideal for mutant screens. PhytoCRISP-Ex is a simple, fast and accurate web interface with 13 pre-indexed and presently updating phytoplankton genomes. The software was also designed as a UNIX-based standalone application that allows the user to search for target sequences in the genomes of a variety of other species.

Operon-mapper: A Web Server for Precise Operon Identification in Bacterial and Archaeal Genomes.

PubMed

Taboada, Blanca; Estrada, Karel; Ciria, Ricardo; Merino, Enrique

2018-06-19

Operon-mapper is a web server that accurately, easily, and directly predicts the operons of any bacterial or archaeal genome sequence. The operon predictions are based on the intergenic distance of neighboring genes as well as the functional relationships of their protein-coding products. To this end, Operon-mapper finds all the ORFs within a given nucleotide sequence, along with their genomic coordinates, orthology groups, and functional relationships. We believe that Operon-mapper, due to its accuracy, simplicity and speed, as well as the relevant information that it generates, will be a useful tool for annotating and characterizing genomic sequences. http://biocomputo.ibt.unam.mx/operon_mapper/.

Genomics for Everyone

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

Chain, Patrick

Genomics — the genetic mapping and DNA sequencing of sets of genes or the complete genomes of organisms, along with related genome analysis and database work — is emerging as one of the transformative sciences of the 21st century. But current bioinformatics tools are not accessible to most biological researchers. Now, a new computational and web-based tool called EDGE Bioinformatics is working to fulfill the promise of democratizing genomics.

A Teaching Model for Biotechnology and Genomics Education.

ERIC Educational Resources Information Center

Kirkpatrick, Gretchen; Orvis, Kathryn; Pittendrigh, Barry

2002-01-01

Presents the Genomic Analogy Model for Educators (GAME) strategy for making concepts in genomics easily understandable for both students and the general population by using familiar objects and concepts associated with daily life. Uses web-based tutorials accompanied by laboratory exercises that are intended to be used by students studying…

A Model for the Development of Web-Based, Student-Centered Science Education Resources.

ERIC Educational Resources Information Center

Murfin, Brian; Go, Vanessa

The purpose of this study was to evaluate The Student Genome Project, an experiment in web-based genetics education. Over a two-year period, a team from New York University worked with a biology teacher and 33 high school students (N=33), and a middle school science teacher and a class of students (N=21) to develop a World Wide Web site intended…

Genome Partitioner: A web tool for multi-level partitioning of large-scale DNA constructs for synthetic biology applications.

PubMed

Christen, Matthias; Del Medico, Luca; Christen, Heinz; Christen, Beat

2017-01-01

Recent advances in lower-cost DNA synthesis techniques have enabled new innovations in the field of synthetic biology. Still, efficient design and higher-order assembly of genome-scale DNA constructs remains a labor-intensive process. Given the complexity, computer assisted design tools that fragment large DNA sequences into fabricable DNA blocks are needed to pave the way towards streamlined assembly of biological systems. Here, we present the Genome Partitioner software implemented as a web-based interface that permits multi-level partitioning of genome-scale DNA designs. Without the need for specialized computing skills, biologists can submit their DNA designs to a fully automated pipeline that generates the optimal retrosynthetic route for higher-order DNA assembly. To test the algorithm, we partitioned a 783 kb Caulobacter crescentus genome design. We validated the partitioning strategy by assembling a 20 kb test segment encompassing a difficult to synthesize DNA sequence. Successful assembly from 1 kb subblocks into the 20 kb segment highlights the effectiveness of the Genome Partitioner for reducing synthesis costs and timelines for higher-order DNA assembly. The Genome Partitioner is broadly applicable to translate DNA designs into ready to order sequences that can be assembled with standardized protocols, thus offering new opportunities to harness the diversity of microbial genomes for synthetic biology applications. The Genome Partitioner web tool can be accessed at https://christenlab.ethz.ch/GenomePartitioner.

THGS: a web-based database of Transmembrane Helices in Genome Sequences

PubMed Central

Fernando, S. A.; Selvarani, P.; Das, Soma; Kumar, Ch. Kiran; Mondal, Sukanta; Ramakumar, S.; Sekar, K.

2004-01-01

Transmembrane Helices in Genome Sequences (THGS) is an interactive web-based database, developed to search the transmembrane helices in the user-interested gene sequences available in the Genome Database (GDB). The proposed database has provision to search sequence motifs in transmembrane and globular proteins. In addition, the motif can be searched in the other sequence databases (Swiss-Prot and PIR) or in the macromolecular structure database, Protein Data Bank (PDB). Further, the 3D structure of the corresponding queried motif, if it is available in the solved protein structures deposited in the Protein Data Bank, can also be visualized using the widely used graphics package RASMOL. All the sequence databases used in the present work are updated frequently and hence the results produced are up to date. The database THGS is freely available via the world wide web and can be accessed at http://pranag.physics.iisc.ernet.in/thgs/ or http://144.16.71.10/thgs/. PMID:14681375

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

SWPhylo - A Novel Tool for Phylogenomic Inferences by Comparison of Oligonucleotide Patterns and Integration of Genome-Based and Gene-Based Phylogenetic Trees.

PubMed

Yu, Xiaoyu; Reva, Oleg N

2018-01-01

Modern phylogenetic studies may benefit from the analysis of complete genome sequences of various microorganisms. Evolutionary inferences based on genome-scale analysis are believed to be more accurate than the gene-based alternative. However, the computational complexity of current phylogenomic procedures, inappropriateness of standard phylogenetic tools to process genome-wide data, and lack of reliable substitution models which correlates with alignment-free phylogenomic approaches deter microbiologists from using these opportunities. For example, the super-matrix and super-tree approaches of phylogenomics use multiple integrated genomic loci or individual gene-based trees to infer an overall consensus tree. However, these approaches potentially multiply errors of gene annotation and sequence alignment not mentioning the computational complexity and laboriousness of the methods. In this article, we demonstrate that the annotation- and alignment-free comparison of genome-wide tetranucleotide frequencies, termed oligonucleotide usage patterns (OUPs), allowed a fast and reliable inference of phylogenetic trees. These were congruent to the corresponding whole genome super-matrix trees in terms of tree topology when compared with other known approaches including 16S ribosomal RNA and GyrA protein sequence comparison, complete genome-based MAUVE, and CVTree methods. A Web-based program to perform the alignment-free OUP-based phylogenomic inferences was implemented at http://swphylo.bi.up.ac.za/. Applicability of the tool was tested on different taxa from subspecies to intergeneric levels. Distinguishing between closely related taxonomic units may be enforced by providing the program with alignments of marker protein sequences, eg, GyrA.

SWPhylo – A Novel Tool for Phylogenomic Inferences by Comparison of Oligonucleotide Patterns and Integration of Genome-Based and Gene-Based Phylogenetic Trees

PubMed Central

Yu, Xiaoyu; Reva, Oleg N

2018-01-01

Modern phylogenetic studies may benefit from the analysis of complete genome sequences of various microorganisms. Evolutionary inferences based on genome-scale analysis are believed to be more accurate than the gene-based alternative. However, the computational complexity of current phylogenomic procedures, inappropriateness of standard phylogenetic tools to process genome-wide data, and lack of reliable substitution models which correlates with alignment-free phylogenomic approaches deter microbiologists from using these opportunities. For example, the super-matrix and super-tree approaches of phylogenomics use multiple integrated genomic loci or individual gene-based trees to infer an overall consensus tree. However, these approaches potentially multiply errors of gene annotation and sequence alignment not mentioning the computational complexity and laboriousness of the methods. In this article, we demonstrate that the annotation- and alignment-free comparison of genome-wide tetranucleotide frequencies, termed oligonucleotide usage patterns (OUPs), allowed a fast and reliable inference of phylogenetic trees. These were congruent to the corresponding whole genome super-matrix trees in terms of tree topology when compared with other known approaches including 16S ribosomal RNA and GyrA protein sequence comparison, complete genome-based MAUVE, and CVTree methods. A Web-based program to perform the alignment-free OUP-based phylogenomic inferences was implemented at http://swphylo.bi.up.ac.za/. Applicability of the tool was tested on different taxa from subspecies to intergeneric levels. Distinguishing between closely related taxonomic units may be enforced by providing the program with alignments of marker protein sequences, eg, GyrA. PMID:29511354

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

ODG: Omics database generator - a tool for generating, querying, and analyzing multi-omics comparative databases to facilitate biological understanding.

PubMed

Guhlin, Joseph; Silverstein, Kevin A T; Zhou, Peng; Tiffin, Peter; Young, Nevin D

2017-08-10

Rapid generation of omics data in recent years have resulted in vast amounts of disconnected datasets without systemic integration and knowledge building, while individual groups have made customized, annotated datasets available on the web with few ways to link them to in-lab datasets. With so many research groups generating their own data, the ability to relate it to the larger genomic and comparative genomic context is becoming increasingly crucial to make full use of the data. The Omics Database Generator (ODG) allows users to create customized databases that utilize published genomics data integrated with experimental data which can be queried using a flexible graph database. When provided with omics and experimental data, ODG will create a comparative, multi-dimensional graph database. ODG can import definitions and annotations from other sources such as InterProScan, the Gene Ontology, ENZYME, UniPathway, and others. This annotation data can be especially useful for studying new or understudied species for which transcripts have only been predicted, and rapidly give additional layers of annotation to predicted genes. In better studied species, ODG can perform syntenic annotation translations or rapidly identify characteristics of a set of genes or nucleotide locations, such as hits from an association study. ODG provides a web-based user-interface for configuring the data import and for querying the database. Queries can also be run from the command-line and the database can be queried directly through programming language hooks available for most languages. ODG supports most common genomic formats as well as generic, easy to use tab-separated value format for user-provided annotations. ODG is a user-friendly database generation and query tool that adapts to the supplied data to produce a comparative genomic database or multi-layered annotation database. ODG provides rapid comparative genomic annotation and is therefore particularly useful for non-model or understudied species. For species for which more data are available, ODG can be used to conduct complex multi-omics, pattern-matching queries.

CID-miRNA: A web server for prediction of novel miRNA precursors in human genome

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

Tyagi, Sonika; Vaz, Candida; Gupta, Vipin

2008-08-08

microRNAs (miRNA) are a class of non-protein coding functional RNAs that are thought to regulate expression of target genes by direct interaction with mRNAs. miRNAs have been identified through both experimental and computational methods in a variety of eukaryotic organisms. Though these approaches have been partially successful, there is a need to develop more tools for detection of these RNAs as they are also thought to be present in abundance in many genomes. In this report we describe a tool and a web server, named CID-miRNA, for identification of miRNA precursors in a given DNA sequence, utilising secondary structure-based filteringmore » systems and an algorithm based on stochastic context free grammar trained on human miRNAs. CID-miRNA analyses a given sequence using a web interface, for presence of putative miRNA precursors and the generated output lists all the potential regions that can form miRNA-like structures. It can also scan large genomic sequences for the presence of potential miRNA precursors in its stand-alone form. The web server can be accessed at (http://mirna.jnu.ac.in/cidmirna/)« less

Genomics for Everyone

ScienceCinema

Chain, Patrick

2018-05-31

Genomics — the genetic mapping and DNA sequencing of sets of genes or the complete genomes of organisms, along with related genome analysis and database work — is emerging as one of the transformative sciences of the 21st century. But current bioinformatics tools are not accessible to most biological researchers. Now, a new computational and web-based tool called EDGE Bioinformatics is working to fulfill the promise of democratizing genomics.

CRISPR/Cas9-Based Multiplex Genome Editing in Monocot and Dicot Plants.

PubMed

Ma, Xingliang; Liu, Yao-Guang

2016-07-01

The clustered regularly interspaced short palindromic repeats (CRISPR)/Cas9-mediated genome targeting system has been applied to a variety of organisms, including plants. Compared to other genome-targeting technologies such as zinc-finger nucleases (ZFNs) and transcription activator-like effector nucleases (TALENs), the CRISPR/Cas9 system is easier to use and has much higher editing efficiency. In addition, multiple "single guide RNAs" (sgRNAs) with different target sequences can be designed to direct the Cas9 protein to multiple genomic sites for simultaneous multiplex editing. Here, we present a procedure for highly efficient multiplex genome targeting in monocot and dicot plants using a versatile and robust CRISPR/Cas9 vector system, emphasizing the construction of binary constructs with multiple sgRNA expression cassettes in one round of cloning using Golden Gate ligation. We also describe the genotyping of targeted mutations in transgenic plants by direct Sanger sequencing followed by decoding of superimposed sequencing chromatograms containing biallelic or heterozygous mutations using the Web-based tool DSDecode. © 2016 by John Wiley & Sons, Inc. Copyright © 2016 John Wiley & Sons, Inc.

Learning about the Human Genome. Part 2: Resources for Science Educators. ERIC Digest.

ERIC Educational Resources Information Center

Haury, David L.

This ERIC Digest identifies how the human genome project fits into the "National Science Education Standards" and lists Human Genome Project Web sites found on the World Wide Web. It is a resource companion to "Learning about the Human Genome. Part 1: Challenge to Science Educators" (Haury 2001). The Web resources and…

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.

Ontology-oriented retrieval of putative microRNAs in Vitis vinifera via GrapeMiRNA: a web database of de novo predicted grape microRNAs.

PubMed

Lazzari, Barbara; Caprera, Andrea; Cestaro, Alessandro; Merelli, Ivan; Del Corvo, Marcello; Fontana, Paolo; Milanesi, Luciano; Velasco, Riccardo; Stella, Alessandra

2009-06-29

Two complete genome sequences are available for Vitis vinifera Pinot noir. Based on the sequence and gene predictions produced by the IASMA, we performed an in silico detection of putative microRNA genes and of their targets, and collected the most reliable microRNA predictions in a web database. The application is available at http://www.itb.cnr.it/ptp/grapemirna/. The program FindMiRNA was used to detect putative microRNA genes in the grape genome. A very high number of predictions was retrieved, calling for validation. Nine parameters were calculated and, based on the grape microRNAs dataset available at miRBase, thresholds were defined and applied to FindMiRNA predictions having targets in gene exons. In the resulting subset, predictions were ranked according to precursor positions and sequence similarity, and to target identity. To further validate FindMiRNA predictions, comparisons to the Arabidopsis genome, to the grape Genoscope genome, and to the grape EST collection were performed. Results were stored in a MySQL database and a web interface was prepared to query the database and retrieve predictions of interest. The GrapeMiRNA database encompasses 5,778 microRNA predictions spanning the whole grape genome. Predictions are integrated with information that can be of use in selection procedures. Tools added in the web interface also allow to inspect predictions according to gene ontology classes and metabolic pathways of targets. The GrapeMiRNA database can be of help in selecting candidate microRNA genes to be validated.

Inferring transposons activity chronology by TRANScendence - TEs database and de-novo mining tool.

PubMed

Startek, Michał Piotr; Nogły, Jakub; Gromadka, Agnieszka; Grzebelus, Dariusz; Gambin, Anna

2017-10-16

The constant progress in sequencing technology leads to ever increasing amounts of genomic data. In the light of current evidence transposable elements (TEs for short) are becoming useful tools for learning about the evolution of host genome. Therefore the software for genome-wide detection and analysis of TEs is of great interest. Here we describe the computational tool for mining, classifying and storing TEs from newly sequenced genomes. This is an online, web-based, user-friendly service, enabling users to upload their own genomic data, and perform de-novo searches for TEs. The detected TEs are automatically analyzed, compared to reference databases, annotated, clustered into families, and stored in TEs repository. Also, the genome-wide nesting structure of found elements are detected and analyzed by new method for inferring evolutionary history of TEs. We illustrate the functionality of our tool by performing a full-scale analyses of TE landscape in Medicago truncatula genome. TRANScendence is an effective tool for the de-novo annotation and classification of transposable elements in newly-acquired genomes. Its streamlined interface makes it well-suited for evolutionary studies.

DMINDA: an integrated web server for DNA motif identification and analyses.

PubMed

Ma, Qin; Zhang, Hanyuan; Mao, Xizeng; Zhou, Chuan; Liu, Bingqiang; Chen, Xin; Xu, Ying

2014-07-01

DMINDA (DNA motif identification and analyses) is an integrated web server for DNA motif identification and analyses, which is accessible at http://csbl.bmb.uga.edu/DMINDA/. This web site is freely available to all users and there is no login requirement. This server provides a suite of cis-regulatory motif analysis functions on DNA sequences, which are important to elucidation of the mechanisms of transcriptional regulation: (i) de novo motif finding for a given set of promoter sequences along with statistical scores for the predicted motifs derived based on information extracted from a control set, (ii) scanning motif instances of a query motif in provided genomic sequences, (iii) motif comparison and clustering of identified motifs, and (iv) co-occurrence analyses of query motifs in given promoter sequences. The server is powered by a backend computer cluster with over 150 computing nodes, and is particularly useful for motif prediction and analyses in prokaryotic genomes. We believe that DMINDA, as a new and comprehensive web server for cis-regulatory motif finding and analyses, will benefit the genomic research community in general and prokaryotic genome researchers in particular. © The Author(s) 2014. Published by Oxford University Press on behalf of Nucleic Acids Research.

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, ...

Cloud computing for comparative genomics with windows azure platform.

PubMed

Kim, Insik; Jung, Jae-Yoon; Deluca, Todd F; Nelson, Tristan H; Wall, Dennis P

2012-01-01

Cloud computing services have emerged as a cost-effective alternative for cluster systems as the number of genomes and required computation power to analyze them increased in recent years. Here we introduce the Microsoft Azure platform with detailed execution steps and a cost comparison with Amazon Web Services.

Cloud Computing for Comparative Genomics with Windows Azure Platform

PubMed Central

Kim, Insik; Jung, Jae-Yoon; DeLuca, Todd F.; Nelson, Tristan H.; Wall, Dennis P.

2012-01-01

Cloud computing services have emerged as a cost-effective alternative for cluster systems as the number of genomes and required computation power to analyze them increased in recent years. Here we introduce the Microsoft Azure platform with detailed execution steps and a cost comparison with Amazon Web Services. PMID:23032609

WEGO 2.0: a web tool for analyzing and plotting GO annotations, 2018 update.

PubMed

Ye, Jia; Zhang, Yong; Cui, Huihai; Liu, Jiawei; Wu, Yuqing; Cheng, Yun; Xu, Huixing; Huang, Xingxin; Li, Shengting; Zhou, An; Zhang, Xiuqing; Bolund, Lars; Chen, Qiang; Wang, Jian; Yang, Huanming; Fang, Lin; Shi, Chunmei

2018-05-18

WEGO (Web Gene Ontology Annotation Plot), created in 2006, is a simple but useful tool for visualizing, comparing and plotting GO (Gene Ontology) annotation results. Owing largely to the rapid development of high-throughput sequencing and the increasing acceptance of GO, WEGO has benefitted from outstanding performance regarding the number of users and citations in recent years, which motivated us to update to version 2.0. WEGO uses the GO annotation results as input. Based on GO's standardized DAG (Directed Acyclic Graph) structured vocabulary system, the number of genes corresponding to each GO ID is calculated and shown in a graphical format. WEGO 2.0 updates have targeted four aspects, aiming to provide a more efficient and up-to-date approach for comparative genomic analyses. First, the number of input files, previously limited to three, is now unlimited, allowing WEGO to analyze multiple datasets. Also added in this version are the reference datasets of nine model species that can be adopted as baselines in genomic comparative analyses. Furthermore, in the analyzing processes each Chi-square test is carried out for multiple datasets instead of every two samples. At last, WEGO 2.0 provides an additional output graph along with the traditional WEGO histogram, displaying the sorted P-values of GO terms and indicating their significant differences. At the same time, WEGO 2.0 features an entirely new user interface. WEGO is available for free at http://wego.genomics.org.cn.

Genome Partitioner: A web tool for multi-level partitioning of large-scale DNA constructs for synthetic biology applications

PubMed Central

Del Medico, Luca; Christen, Heinz; Christen, Beat

2017-01-01

Recent advances in lower-cost DNA synthesis techniques have enabled new innovations in the field of synthetic biology. Still, efficient design and higher-order assembly of genome-scale DNA constructs remains a labor-intensive process. Given the complexity, computer assisted design tools that fragment large DNA sequences into fabricable DNA blocks are needed to pave the way towards streamlined assembly of biological systems. Here, we present the Genome Partitioner software implemented as a web-based interface that permits multi-level partitioning of genome-scale DNA designs. Without the need for specialized computing skills, biologists can submit their DNA designs to a fully automated pipeline that generates the optimal retrosynthetic route for higher-order DNA assembly. To test the algorithm, we partitioned a 783 kb Caulobacter crescentus genome design. We validated the partitioning strategy by assembling a 20 kb test segment encompassing a difficult to synthesize DNA sequence. Successful assembly from 1 kb subblocks into the 20 kb segment highlights the effectiveness of the Genome Partitioner for reducing synthesis costs and timelines for higher-order DNA assembly. The Genome Partitioner is broadly applicable to translate DNA designs into ready to order sequences that can be assembled with standardized protocols, thus offering new opportunities to harness the diversity of microbial genomes for synthetic biology applications. The Genome Partitioner web tool can be accessed at https://christenlab.ethz.ch/GenomePartitioner. PMID:28531174

A Web-Based Genetic Polymorphism Learning Approach for High School Students and Science Teachers

ERIC Educational Resources Information Center

Amenkhienan, Ehichoya; Smith, Edward J.

2006-01-01

Variation and polymorphism are concepts that are central to genetics and genomics, primary biological disciplines in which high school students and undergraduates require a solid foundation. From 1998 through 2002, a web-based genetics education program was developed for high school teachers and students. The program included an exercise on using…

Merlin: Computer-Aided Oligonucleotide Design for Large Scale Genome Engineering with MAGE.

PubMed

Quintin, Michael; Ma, Natalie J; Ahmed, Samir; Bhatia, Swapnil; Lewis, Aaron; Isaacs, Farren J; Densmore, Douglas

2016-06-17

Genome engineering technologies now enable precise manipulation of organism genotype, but can be limited in scalability by their design requirements. Here we describe Merlin ( http://merlincad.org ), an open-source web-based tool to assist biologists in designing experiments using multiplex automated genome engineering (MAGE). Merlin provides methods to generate pools of single-stranded DNA oligonucleotides (oligos) for MAGE experiments by performing free energy calculation and BLAST scoring on a sliding window spanning the targeted site. These oligos are designed not only to improve recombination efficiency, but also to minimize off-target interactions. The application further assists experiment planning by reporting predicted allelic replacement rates after multiple MAGE cycles, and enables rapid result validation by generating primer sequences for multiplexed allele-specific colony PCR. Here we describe the Merlin oligo and primer design procedures and validate their functionality compared to OptMAGE by eliminating seven AvrII restriction sites from the Escherichia coli genome.

VectorBase: an updated bioinformatics resource for invertebrate vectors and other organisms related with human diseases

PubMed Central

Giraldo-Calderón, Gloria I.; Emrich, Scott J.; MacCallum, Robert M.; Maslen, Gareth; Dialynas, Emmanuel; Topalis, Pantelis; Ho, Nicholas; Gesing, Sandra; Madey, Gregory; Collins, Frank H.; Lawson, Daniel

2015-01-01

VectorBase is a National Institute of Allergy and Infectious Diseases supported Bioinformatics Resource Center (BRC) for invertebrate vectors of human pathogens. Now in its 11th year, VectorBase currently hosts the genomes of 35 organisms including a number of non-vectors for comparative analysis. Hosted data range from genome assemblies with annotated gene features, transcript and protein expression data to population genetics including variation and insecticide-resistance phenotypes. Here we describe improvements to our resource and the set of tools available for interrogating and accessing BRC data including the integration of Web Apollo to facilitate community annotation and providing Galaxy to support user-based workflows. VectorBase also actively supports our community through hands-on workshops and online tutorials. All information and data are freely available from our website at https://www.vectorbase.org/. PMID:25510499

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.

Hymenoptera Genome Database: integrating genome annotations in HymenopteraMine

PubMed Central

Elsik, Christine G.; Tayal, Aditi; Diesh, Colin M.; Unni, Deepak R.; Emery, Marianne L.; Nguyen, Hung N.; Hagen, Darren E.

2016-01-01

We report an update of the Hymenoptera Genome Database (HGD) (http://HymenopteraGenome.org), a model organism database for insect species of the order Hymenoptera (ants, bees and wasps). HGD maintains genomic data for 9 bee species, 10 ant species and 1 wasp, including the versions of genome and annotation data sets published by the genome sequencing consortiums and those provided by NCBI. A new data-mining warehouse, HymenopteraMine, based on the InterMine data warehousing system, integrates the genome data with data from external sources and facilitates cross-species analyses based on orthology. New genome browsers and annotation tools based on JBrowse/WebApollo provide easy genome navigation, and viewing of high throughput sequence data sets and can be used for collaborative genome annotation. All of the genomes and annotation data sets are combined into a single BLAST server that allows users to select and combine sequence data sets to search. PMID:26578564

MEMOSys: Bioinformatics platform for genome-scale metabolic models

PubMed Central

2011-01-01

Background Recent advances in genomic sequencing have enabled the use of genome sequencing in standard biological and biotechnological research projects. The challenge is how to integrate the large amount of data in order to gain novel biological insights. One way to leverage sequence data is to use genome-scale metabolic models. We have therefore designed and implemented a bioinformatics platform which supports the development of such metabolic models. Results MEMOSys (MEtabolic MOdel research and development System) is a versatile platform for the management, storage, and development of genome-scale metabolic models. It supports the development of new models by providing a built-in version control system which offers access to the complete developmental history. Moreover, the integrated web board, the authorization system, and the definition of user roles allow collaborations across departments and institutions. Research on existing models is facilitated by a search system, references to external databases, and a feature-rich comparison mechanism. MEMOSys provides customizable data exchange mechanisms using the SBML format to enable analysis in external tools. The web application is based on the Java EE framework and offers an intuitive user interface. It currently contains six annotated microbial metabolic models. Conclusions We have developed a web-based system designed to provide researchers a novel application facilitating the management and development of metabolic models. The system is freely available at http://www.icbi.at/MEMOSys. PMID:21276275

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.

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.

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.

TipMT: Identification of PCR-based taxon-specific markers.

PubMed

Rodrigues-Luiz, Gabriela F; Cardoso, Mariana S; Valdivia, Hugo O; Ayala, Edward V; Gontijo, Célia M F; Rodrigues, Thiago de S; Fujiwara, Ricardo T; Lopes, Robson S; Bartholomeu, Daniella C

2017-02-11

Molecular genetic markers are one of the most informative and widely used genome features in clinical and environmental diagnostic studies. A polymerase chain reaction (PCR)-based molecular marker is very attractive because it is suitable to high throughput automation and confers high specificity. However, the design of taxon-specific primers may be difficult and time consuming due to the need to identify appropriate genomic regions for annealing primers and to evaluate primer specificity. Here, we report the development of a Tool for Identification of Primers for Multiple Taxa (TipMT), which is a web application to search and design primers for genotyping based on genomic data. The tool identifies and targets single sequence repeats (SSR) or orthologous/taxa-specific genes for genotyping using Multiplex PCR. This pipeline was applied to the genomes of four species of Leishmania (L. amazonensis, L. braziliensis, L. infantum and L. major) and validated by PCR using artificial genomic DNA mixtures of the Leishmania species as templates. This experimental validation demonstrates the reliability of TipMT because amplification profiles showed discrimination of genomic DNA samples from Leishmania species. The TipMT web tool allows for large-scale identification and design of taxon-specific primers and is freely available to the scientific community at http://200.131.37.155/tipMT/ .

SG-ADVISER CNV: copy-number variant annotation and interpretation.

PubMed

Erikson, Galina A; Deshpande, Neha; Kesavan, Balachandar G; Torkamani, Ali

2015-09-01

Copy-number variants have been associated with a variety of diseases, especially cancer, autism, schizophrenia, and developmental delay. The majority of clinically relevant events occur de novo, necessitating the interpretation of novel events. In this light, we present the Scripps Genome ADVISER CNV annotation pipeline and Web server, which aims to fill the gap between copy number variant detection and interpretation by performing in-depth annotations and functional predictions for copy number variants. The Scripps Genome ADVISER CNV suite includes a Web server interface to a high-performance computing environment for calculations of annotations and a table-based user interface that allows for the execution of numerous annotation-based variant filtration strategies and statistics. The annotation results include details regarding location, impact on the coding portion of genes, allele frequency information (including allele frequencies from the Scripps Wellderly cohort), and overlap information with other reference data sets (including ClinVar, DGV, DECIPHER). A summary variant classification is produced (ADVISER score) based on the American College of Medical Genetics and Genomics scoring guidelines. We demonstrate >90% sensitivity/specificity for detection of pathogenic events. Scripps Genome ADVISER CNV is designed to allow users with no prior bioinformatics expertise to manipulate large volumes of copy-number variant data. Scripps Genome ADVISER CNV is available at http://genomics.scripps.edu/ADVISER/.

Genome-wide analysis of signatures of selection in populations of African honey bees (Apis mellifera) using new web-based tools.

PubMed

Fuller, Zachary L; Niño, Elina L; Patch, Harland M; Bedoya-Reina, Oscar C; Baumgarten, Tracey; Muli, Elliud; Mumoki, Fiona; Ratan, Aakrosh; McGraw, John; Frazier, Maryann; Masiga, Daniel; Schuster, Stephen; Grozinger, Christina M; Miller, Webb

2015-07-10

With the development of inexpensive, high-throughput sequencing technologies, it has become feasible to examine questions related to population genetics and molecular evolution of non-model species in their ecological contexts on a genome-wide scale. Here, we employed a newly developed suite of integrated, web-based programs to examine population dynamics and signatures of selection across the genome using several well-established tests, including F ST, pN/pS, and McDonald-Kreitman. We applied these techniques to study populations of honey bees (Apis mellifera) in East Africa. In Kenya, there are several described A. mellifera subspecies, which are thought to be localized to distinct ecological regions. We performed whole genome sequencing of 11 worker honey bees from apiaries distributed throughout Kenya and identified 3.6 million putative single-nucleotide polymorphisms. The dense coverage allowed us to apply several computational procedures to study population structure and the evolutionary relationships among the populations, and to detect signs of adaptive evolution across the genome. While there is considerable gene flow among the sampled populations, there are clear distinctions between populations from the northern desert region and those from the temperate, savannah region. We identified several genes showing population genetic patterns consistent with positive selection within African bee populations, and between these populations and European A. mellifera or Asian Apis florea. These results lay the groundwork for future studies of adaptive ecological evolution in honey bees, and demonstrate the use of new, freely available web-based tools and workflows ( http://usegalaxy.org/r/kenyanbee ) that can be applied to any model system with genomic information.

TGS-TB: Total Genotyping Solution for Mycobacterium tuberculosis Using Short-Read Whole-Genome Sequencing

PubMed Central

Sekizuka, Tsuyoshi; Yamashita, Akifumi; Murase, Yoshiro; Iwamoto, Tomotada; Mitarai, Satoshi; Kato, Seiya; Kuroda, Makoto

2015-01-01

Whole-genome sequencing (WGS) with next-generation DNA sequencing (NGS) is an increasingly accessible and affordable method for genotyping hundreds of Mycobacterium tuberculosis (Mtb) isolates, leading to more effective epidemiological studies involving single nucleotide variations (SNVs) in core genomic sequences based on molecular evolution. We developed an all-in-one web-based tool for genotyping Mtb, referred to as the Total Genotyping Solution for TB (TGS-TB), to facilitate multiple genotyping platforms using NGS for spoligotyping and the detection of phylogenies with core genomic SNVs, IS6110 insertion sites, and 43 customized loci for variable number tandem repeat (VNTR) through a user-friendly, simple click interface. This methodology is implemented with a KvarQ script to predict MTBC lineages/sublineages and potential antimicrobial resistance. Seven Mtb isolates (JP01 to JP07) in this study showing the same VNTR profile were accurately discriminated through median-joining network analysis using SNVs unique to those isolates. An additional IS6110 insertion was detected in one of those isolates as supportive genetic information in addition to core genomic SNVs. The results of in silico analyses using TGS-TB are consistent with those obtained using conventional molecular genotyping methods, suggesting that NGS short reads could provide multiple genotypes to discriminate multiple strains of Mtb, although longer NGS reads (≥300-mer) will be required for full genotyping on the TGS-TB web site. Most available short reads (~100-mer) can be utilized to discriminate the isolates based on the core genome phylogeny. TGS-TB provides a more accurate and discriminative strain typing for clinical and epidemiological investigations; NGS strain typing offers a total genotyping solution for Mtb outbreak and surveillance. TGS-TB web site: https://gph.niid.go.jp/tgs-tb/. PMID:26565975

Protein Sequence Annotation Tool (PSAT): A centralized web-based meta-server for high-throughput sequence annotations

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

Leung, Elo; Huang, Amy; Cadag, Eithon

In this study, we introduce the Protein Sequence Annotation Tool (PSAT), a web-based, sequence annotation meta-server for performing integrated, high-throughput, genome-wide sequence analyses. Our goals in building PSAT were to (1) create an extensible platform for integration of multiple sequence-based bioinformatics tools, (2) enable functional annotations and enzyme predictions over large input protein fasta data sets, and (3) provide a web interface for convenient execution of the tools. In this paper, we demonstrate the utility of PSAT by annotating the predicted peptide gene products of Herbaspirillum sp. strain RV1423, importing the results of PSAT into EC2KEGG, and using the resultingmore » functional comparisons to identify a putative catabolic pathway, thereby distinguishing RV1423 from a well annotated Herbaspirillum species. This analysis demonstrates that high-throughput enzyme predictions, provided by PSAT processing, can be used to identify metabolic potential in an otherwise poorly annotated genome. Lastly, PSAT is a meta server that combines the results from several sequence-based annotation and function prediction codes, and is available at http://psat.llnl.gov/psat/. PSAT stands apart from other sequencebased genome annotation systems in providing a high-throughput platform for rapid de novo enzyme predictions and sequence annotations over large input protein sequence data sets in FASTA. PSAT is most appropriately applied in annotation of large protein FASTA sets that may or may not be associated with a single genome.« less

Protein Sequence Annotation Tool (PSAT): A centralized web-based meta-server for high-throughput sequence annotations

DOE PAGES

Leung, Elo; Huang, Amy; Cadag, Eithon; ...

2016-01-20

In this study, we introduce the Protein Sequence Annotation Tool (PSAT), a web-based, sequence annotation meta-server for performing integrated, high-throughput, genome-wide sequence analyses. Our goals in building PSAT were to (1) create an extensible platform for integration of multiple sequence-based bioinformatics tools, (2) enable functional annotations and enzyme predictions over large input protein fasta data sets, and (3) provide a web interface for convenient execution of the tools. In this paper, we demonstrate the utility of PSAT by annotating the predicted peptide gene products of Herbaspirillum sp. strain RV1423, importing the results of PSAT into EC2KEGG, and using the resultingmore » functional comparisons to identify a putative catabolic pathway, thereby distinguishing RV1423 from a well annotated Herbaspirillum species. This analysis demonstrates that high-throughput enzyme predictions, provided by PSAT processing, can be used to identify metabolic potential in an otherwise poorly annotated genome. Lastly, PSAT is a meta server that combines the results from several sequence-based annotation and function prediction codes, and is available at http://psat.llnl.gov/psat/. PSAT stands apart from other sequencebased genome annotation systems in providing a high-throughput platform for rapid de novo enzyme predictions and sequence annotations over large input protein sequence data sets in FASTA. PSAT is most appropriately applied in annotation of large protein FASTA sets that may or may not be associated with a single genome.« less

MALINA: a web service for visual analytics of human gut microbiota whole-genome metagenomic reads.

PubMed

Tyakht, Alexander V; Popenko, Anna S; Belenikin, Maxim S; Altukhov, Ilya A; Pavlenko, Alexander V; Kostryukova, Elena S; Selezneva, Oksana V; Larin, Andrei K; Karpova, Irina Y; Alexeev, Dmitry G

2012-12-07

MALINA is a web service for bioinformatic analysis of whole-genome metagenomic data obtained from human gut microbiota sequencing. As input data, it accepts metagenomic reads of various sequencing technologies, including long reads (such as Sanger and 454 sequencing) and next-generation (including SOLiD and Illumina). It is the first metagenomic web service that is capable of processing SOLiD color-space reads, to authors' knowledge. The web service allows phylogenetic and functional profiling of metagenomic samples using coverage depth resulting from the alignment of the reads to the catalogue of reference sequences which are built into the pipeline and contain prevalent microbial genomes and genes of human gut microbiota. The obtained metagenomic composition vectors are processed by the statistical analysis and visualization module containing methods for clustering, dimension reduction and group comparison. Additionally, the MALINA database includes vectors of bacterial and functional composition for human gut microbiota samples from a large number of existing studies allowing their comparative analysis together with user samples, namely datasets from Russian Metagenome project, MetaHIT and Human Microbiome Project (downloaded from http://hmpdacc.org). MALINA is made freely available on the web at http://malina.metagenome.ru. The website is implemented in JavaScript (using Ext JS), Microsoft .NET Framework, MS SQL, Python, with all major browsers supported.

VectorBase: a home for invertebrate vectors of human pathogens

PubMed Central

Lawson, Daniel; Arensburger, Peter; Atkinson, Peter; Besansky, Nora J.; Bruggner, Robert V.; Butler, Ryan; Campbell, Kathryn S.; Christophides, George K.; Christley, Scott; Dialynas, Emmanuel; Emmert, David; Hammond, Martin; Hill, Catherine A.; Kennedy, Ryan C.; Lobo, Neil F.; MacCallum, M. Robert; Madey, Greg; Megy, Karine; Redmond, Seth; Russo, Susan; Severson, David W.; Stinson, Eric O.; Topalis, Pantelis; Zdobnov, Evgeny M.; Birney, Ewan; Gelbart, William M.; Kafatos, Fotis C.; Louis, Christos; Collins, Frank H.

2007-01-01

VectorBase () is a web-accessible data repository for information about invertebrate vectors of human pathogens. VectorBase annotates and maintains vector genomes providing an integrated resource for the research community. Currently, VectorBase contains genome information for two organisms: Anopheles gambiae, a vector for the Plasmodium protozoan agent causing malaria, and Aedes aegypti, a vector for the flaviviral agents causing Yellow fever and Dengue fever. PMID:17145709

CRISPR-FOCUS: A web server for designing focused CRISPR screening experiments.

PubMed

Cao, Qingyi; Ma, Jian; Chen, Chen-Hao; Xu, Han; Chen, Zhi; Li, Wei; Liu, X Shirley

2017-01-01

The recently developed CRISPR screen technology, based on the CRISPR/Cas9 genome editing system, enables genome-wide interrogation of gene functions in an efficient and cost-effective manner. Although many computational algorithms and web servers have been developed to design single-guide RNAs (sgRNAs) with high specificity and efficiency, algorithms specifically designed for conducting CRISPR screens are still lacking. Here we present CRISPR-FOCUS, a web-based platform to search and prioritize sgRNAs for CRISPR screen experiments. With official gene symbols or RefSeq IDs as the only mandatory input, CRISPR-FOCUS filters and prioritizes sgRNAs based on multiple criteria, including efficiency, specificity, sequence conservation, isoform structure, as well as genomic variations including Single Nucleotide Polymorphisms and cancer somatic mutations. CRISPR-FOCUS also provides pre-defined positive and negative control sgRNAs, as well as other necessary sequences in the construct (e.g., U6 promoters to drive sgRNA transcription and RNA scaffolds of the CRISPR/Cas9). These features allow users to synthesize oligonucleotides directly based on the output of CRISPR-FOCUS. Overall, CRISPR-FOCUS provides a rational and high-throughput approach for sgRNA library design that enables users to efficiently conduct a focused screen experiment targeting up to thousands of genes. (CRISPR-FOCUS is freely available at http://cistrome.org/crispr-focus/).

Unlimited Thirst for Genome Sequencing, Data Interpretation, and Database Usage in Genomic Era: The Road towards Fast-Track Crop Plant Improvement

PubMed Central

Govindaraj, Mahalingam

2015-01-01

The number of sequenced crop genomes and associated genomic resources is growing rapidly with the advent of inexpensive next generation sequencing methods. Databases have become an integral part of all aspects of science research, including basic and applied plant and animal sciences. The importance of databases keeps increasing as the volume of datasets from direct and indirect genomics, as well as other omics approaches, keeps expanding in recent years. The databases and associated web portals provide at a minimum a uniform set of tools and automated analysis across a wide range of crop plant genomes. This paper reviews some basic terms and considerations in dealing with crop plant databases utilization in advancing genomic era. The utilization of databases for variation analysis with other comparative genomics tools, and data interpretation platforms are well described. The major focus of this review is to provide knowledge on platforms and databases for genome-based investigations of agriculturally important crop plants. The utilization of these databases in applied crop improvement program is still being achieved widely; otherwise, the end for sequencing is not far away. PMID:25874133

Net Venn - An integrated network analysis web platform for gene lists

USDA-ARS?s Scientific Manuscript database

Many lists containing biological identifiers such as gene lists have been generated in various genomics projects. Identifying the overlap among gene lists can enable us to understand the similarities and differences between the datasets. Here, we present an interactome network-based web application...

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.

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.

GDA, a web-based tool for Genomics and Drugs integrated analysis.

PubMed

Caroli, Jimmy; Sorrentino, Giovanni; Forcato, Mattia; Del Sal, Giannino; Bicciato, Silvio

2018-05-25

Several major screenings of genetic profiling and drug testing in cancer cell lines proved that the integration of genomic portraits and compound activities is effective in discovering new genetic markers of drug sensitivity and clinically relevant anticancer compounds. Despite most genetic and drug response data are publicly available, the availability of user-friendly tools for their integrative analysis remains limited, thus hampering an effective exploitation of this information. Here, we present GDA, a web-based tool for Genomics and Drugs integrated Analysis that combines drug response data for >50 800 compounds with mutations and gene expression profiles across 73 cancer cell lines. Genomic and pharmacological data are integrated through a modular architecture that allows users to identify compounds active towards cancer cell lines bearing a specific genomic background and, conversely, the mutational or transcriptional status of cells responding or not-responding to a specific compound. Results are presented through intuitive graphical representations and supplemented with information obtained from public repositories. As both personalized targeted therapies and drug-repurposing are gaining increasing attention, GDA represents a resource to formulate hypotheses on the interplay between genomic traits and drug response in cancer. GDA is freely available at http://gda.unimore.it/.

The PEPR GeneChip data warehouse, and implementation of a dynamic time series query tool (SGQT) with graphical interface.

PubMed

Chen, Josephine; Zhao, Po; Massaro, Donald; Clerch, Linda B; Almon, Richard R; DuBois, Debra C; Jusko, William J; Hoffman, Eric P

2004-01-01

Publicly accessible DNA databases (genome browsers) are rapidly accelerating post-genomic research (see http://www.genome.ucsc.edu/), with integrated genomic DNA, gene structure, EST/ splicing and cross-species ortholog data. DNA databases have relatively low dimensionality; the genome is a linear code that anchors all associated data. In contrast, RNA expression and protein databases need to be able to handle very high dimensional data, with time, tissue, cell type and genes, as interrelated variables. The high dimensionality of microarray expression profile data, and the lack of a standard experimental platform have complicated the development of web-accessible databases and analytical tools. We have designed and implemented a public resource of expression profile data containing 1024 human, mouse and rat Affymetrix GeneChip expression profiles, generated in the same laboratory, and subject to the same quality and procedural controls (Public Expression Profiling Resource; PEPR). Our Oracle-based PEPR data warehouse includes a novel time series query analysis tool (SGQT), enabling dynamic generation of graphs and spreadsheets showing the action of any transcript of interest over time. In this report, we demonstrate the utility of this tool using a 27 time point, in vivo muscle regeneration series. This data warehouse and associated analysis tools provides access to multidimensional microarray data through web-based interfaces, both for download of all types of raw data for independent analysis, and also for straightforward gene-based queries. Planned implementations of PEPR will include web-based remote entry of projects adhering to quality control and standard operating procedure (QC/SOP) criteria, and automated output of alternative probe set algorithms for each project (see http://microarray.cnmcresearch.org/pgadatatable.asp).

eXframe: reusable framework for storage, analysis and visualization of genomics experiments

PubMed Central

2011-01-01

Background Genome-wide experiments are routinely conducted to measure gene expression, DNA-protein interactions and epigenetic status. Structured metadata for these experiments is imperative for a complete understanding of experimental conditions, to enable consistent data processing and to allow retrieval, comparison, and integration of experimental results. Even though several repositories have been developed for genomics data, only a few provide annotation of samples and assays using controlled vocabularies. Moreover, many of them are tailored for a single type of technology or measurement and do not support the integration of multiple data types. Results We have developed eXframe - a reusable web-based framework for genomics experiments that provides 1) the ability to publish structured data compliant with accepted standards 2) support for multiple data types including microarrays and next generation sequencing 3) query, analysis and visualization integration tools (enabled by consistent processing of the raw data and annotation of samples) and is available as open-source software. We present two case studies where this software is currently being used to build repositories of genomics experiments - one contains data from hematopoietic stem cells and another from Parkinson's disease patients. Conclusion The web-based framework eXframe offers structured annotation of experiments as well as uniform processing and storage of molecular data from microarray and next generation sequencing platforms. The framework allows users to query and integrate information across species, technologies, measurement types and experimental conditions. Our framework is reusable and freely modifiable - other groups or institutions can deploy their own custom web-based repositories based on this software. It is interoperable with the most important data formats in this domain. We hope that other groups will not only use eXframe, but also contribute their own useful modifications. PMID:22103807

The PEPR GeneChip data warehouse, and implementation of a dynamic time series query tool (SGQT) with graphical interface

PubMed Central

Chen, Josephine; Zhao, Po; Massaro, Donald; Clerch, Linda B.; Almon, Richard R.; DuBois, Debra C.; Jusko, William J.; Hoffman, Eric P.

2004-01-01

Publicly accessible DNA databases (genome browsers) are rapidly accelerating post-genomic research (see http://www.genome.ucsc.edu/), with integrated genomic DNA, gene structure, EST/ splicing and cross-species ortholog data. DNA databases have relatively low dimensionality; the genome is a linear code that anchors all associated data. In contrast, RNA expression and protein databases need to be able to handle very high dimensional data, with time, tissue, cell type and genes, as interrelated variables. The high dimensionality of microarray expression profile data, and the lack of a standard experimental platform have complicated the development of web-accessible databases and analytical tools. We have designed and implemented a public resource of expression profile data containing 1024 human, mouse and rat Affymetrix GeneChip expression profiles, generated in the same laboratory, and subject to the same quality and procedural controls (Public Expression Profiling Resource; PEPR). Our Oracle-based PEPR data warehouse includes a novel time series query analysis tool (SGQT), enabling dynamic generation of graphs and spreadsheets showing the action of any transcript of interest over time. In this report, we demonstrate the utility of this tool using a 27 time point, in vivo muscle regeneration series. This data warehouse and associated analysis tools provides access to multidimensional microarray data through web-based interfaces, both for download of all types of raw data for independent analysis, and also for straightforward gene-based queries. Planned implementations of PEPR will include web-based remote entry of projects adhering to quality control and standard operating procedure (QC/SOP) criteria, and automated output of alternative probe set algorithms for each project (see http://microarray.cnmcresearch.org/pgadatatable.asp). PMID:14681485

Building a semantic web-based metadata repository for facilitating detailed clinical modeling in cancer genome studies.

PubMed

Sharma, Deepak K; Solbrig, Harold R; Tao, Cui; Weng, Chunhua; Chute, Christopher G; Jiang, Guoqian

2017-06-05

Detailed Clinical Models (DCMs) have been regarded as the basis for retaining computable meaning when data are exchanged between heterogeneous computer systems. To better support clinical cancer data capturing and reporting, there is an emerging need to develop informatics solutions for standards-based clinical models in cancer study domains. The objective of the study is to develop and evaluate a cancer genome study metadata management system that serves as a key infrastructure in supporting clinical information modeling in cancer genome study domains. We leveraged a Semantic Web-based metadata repository enhanced with both ISO11179 metadata standard and Clinical Information Modeling Initiative (CIMI) Reference Model. We used the common data elements (CDEs) defined in The Cancer Genome Atlas (TCGA) data dictionary, and extracted the metadata of the CDEs using the NCI Cancer Data Standards Repository (caDSR) CDE dataset rendered in the Resource Description Framework (RDF). The ITEM/ITEM_GROUP pattern defined in the latest CIMI Reference Model is used to represent reusable model elements (mini-Archetypes). We produced a metadata repository with 38 clinical cancer genome study domains, comprising a rich collection of mini-Archetype pattern instances. We performed a case study of the domain "clinical pharmaceutical" in the TCGA data dictionary and demonstrated enriched data elements in the metadata repository are very useful in support of building detailed clinical models. Our informatics approach leveraging Semantic Web technologies provides an effective way to build a CIMI-compliant metadata repository that would facilitate the detailed clinical modeling to support use cases beyond TCGA in clinical cancer study domains.

WikiGenomes: an open web application for community consumption and curation of gene annotation data in Wikidata

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

Putman, Tim E.; Lelong, Sebastien; Burgstaller-Muehlbacher, Sebastian

With the advancement of genome-sequencing technologies, new genomes are being sequenced daily. Although these sequences are deposited in publicly available data warehouses, their functional and genomic annotations (beyond genes which are predicted automatically) mostly reside in the text of primary publications. Professional curators are hard at work extracting those annotations from the literature for the most studied organisms and depositing them in structured databases. However, the resources don’t exist to fund the comprehensive curation of the thousands of newly sequenced organisms in this manner. Here, we describe WikiGenomes (wikigenomes.org), a web application that facilitates the consumption and curation of genomicmore » data by the entire scientific community. WikiGenomes is based on Wikidata, an openly editable knowledge graph with the goal of aggregating published knowledge into a free and open database. WikiGenomes empowers the individual genomic researcher to contribute their expertise to the curation effort and integrates the knowledge into Wikidata, enabling it to be accessed by anyone without restriction.« less

WikiGenomes: an open web application for community consumption and curation of gene annotation data in Wikidata

DOE PAGES

Putman, Tim E.; Lelong, Sebastien; Burgstaller-Muehlbacher, Sebastian; ...

2017-03-06

With the advancement of genome-sequencing technologies, new genomes are being sequenced daily. Although these sequences are deposited in publicly available data warehouses, their functional and genomic annotations (beyond genes which are predicted automatically) mostly reside in the text of primary publications. Professional curators are hard at work extracting those annotations from the literature for the most studied organisms and depositing them in structured databases. However, the resources don’t exist to fund the comprehensive curation of the thousands of newly sequenced organisms in this manner. Here, we describe WikiGenomes (wikigenomes.org), a web application that facilitates the consumption and curation of genomicmore » data by the entire scientific community. WikiGenomes is based on Wikidata, an openly editable knowledge graph with the goal of aggregating published knowledge into a free and open database. WikiGenomes empowers the individual genomic researcher to contribute their expertise to the curation effort and integrates the knowledge into Wikidata, enabling it to be accessed by anyone without restriction.« less

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

GenColors: annotation and comparative genomics of prokaryotes made easy.

PubMed

Romualdi, Alessandro; Felder, Marius; Rose, Dominic; Gausmann, Ulrike; Schilhabel, Markus; Glöckner, Gernot; Platzer, Matthias; Sühnel, Jürgen

2007-01-01

GenColors (gencolors.fli-leibniz.de) is a new web-based software/database system aimed at an improved and accelerated annotation of prokaryotic genomes considering information on related genomes and making extensive use of genome comparison. It offers a seamless integration of data from ongoing sequencing projects and annotated genomic sequences obtained from GenBank. A variety of export/import filters manages an effective data flow from sequence assembly and manipulation programs (e.g., GAP4) to GenColors and back as well as to standard GenBank file(s). The genome comparison tools include best bidirectional hits, gene conservation, syntenies, and gene core sets. Precomputed UniProt matches allow annotation and analysis in an effective manner. In addition to these analysis options, base-specific quality data (coverage and confidence) can also be handled if available. The GenColors system can be used both for annotation purposes in ongoing genome projects and as an analysis tool for finished genomes. GenColors comes in two types, as dedicated genome browsers and as the Jena Prokaryotic Genome Viewer (JPGV). Dedicated genome browsers contain genomic information on a set of related genomes and offer a large number of options for genome comparison. The system has been efficiently used in the genomic sequencing of Borrelia garinii and is currently applied to various ongoing genome projects on Borrelia, Legionella, Escherichia, and Pseudomonas genomes. One of these dedicated browsers, the Spirochetes Genome Browser (sgb.fli-leibniz.de) with Borrelia, Leptospira, and Treponema genomes, is freely accessible. The others will be released after finalization of the corresponding genome projects. JPGV (jpgv.fli-leibniz.de) offers information on almost all finished bacterial genomes, as compared to the dedicated browsers with reduced genome comparison functionality, however. As of January 2006, this viewer includes 632 genomic elements (e.g., chromosomes and plasmids) of 293 species. The system provides versatile quick and advanced search options for all currently known prokaryotic genomes and generates circular and linear genome plots. Gene information sheets contain basic gene information, database search options, and links to external databases. GenColors is also available on request for local installation.

The Genomes OnLine Database (GOLD) v.5: a metadata management system based on a four level (meta)genome project classification

PubMed Central

Reddy, T.B.K.; Thomas, Alex D.; Stamatis, Dimitri; Bertsch, Jon; Isbandi, Michelle; Jansson, Jakob; Mallajosyula, Jyothi; Pagani, Ioanna; Lobos, Elizabeth A.; Kyrpides, Nikos C.

2015-01-01

The Genomes OnLine Database (GOLD; http://www.genomesonline.org) is a comprehensive online resource to catalog and monitor genetic studies worldwide. GOLD provides up-to-date status on complete and ongoing sequencing projects along with a broad array of curated metadata. Here we report version 5 (v.5) of the database. The newly designed database schema and web user interface supports several new features including the implementation of a four level (meta)genome project classification system and a simplified intuitive web interface to access reports and launch search tools. The database currently hosts information for about 19 200 studies, 56 000 Biosamples, 56 000 sequencing projects and 39 400 analysis projects. More than just a catalog of worldwide genome projects, GOLD is a manually curated, quality-controlled metadata warehouse. The problems encountered in integrating disparate and varying quality data into GOLD are briefly highlighted. GOLD fully supports and follows the Genomic Standards Consortium (GSC) Minimum Information standards. PMID:25348402

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.

PINTA: a web server for network-based gene prioritization from expression data

PubMed Central

Nitsch, Daniela; Tranchevent, Léon-Charles; Gonçalves, Joana P.; Vogt, Josef Korbinian; Madeira, Sara C.; Moreau, Yves

2011-01-01

PINTA (available at http://www.esat.kuleuven.be/pinta/; this web site is free and open to all users and there is no login requirement) is a web resource for the prioritization of candidate genes based on the differential expression of their neighborhood in a genome-wide protein–protein interaction network. Our strategy is meant for biological and medical researchers aiming at identifying novel disease genes using disease specific expression data. PINTA supports both candidate gene prioritization (starting from a user defined set of candidate genes) as well as genome-wide gene prioritization and is available for five species (human, mouse, rat, worm and yeast). As input data, PINTA only requires disease specific expression data, whereas various platforms (e.g. Affymetrix) are supported. As a result, PINTA computes a gene ranking and presents the results as a table that can easily be browsed and downloaded by the user. PMID:21602267

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.

OrthoVenn: a web server for genome wide comparison and annotation of orthologous clusters across multiple species.

PubMed

Wang, Yi; Coleman-Derr, Devin; Chen, Guoping; Gu, Yong Q

2015-07-01

Genome wide analysis of orthologous clusters is an important component of comparative genomics studies. Identifying the overlap among orthologous clusters can enable us to elucidate the function and evolution of proteins across multiple species. Here, we report a web platform named OrthoVenn that is useful for genome wide comparisons and visualization of orthologous clusters. OrthoVenn provides coverage of vertebrates, metazoa, protists, fungi, plants and bacteria for the comparison of orthologous clusters and also supports uploading of customized protein sequences from user-defined species. An interactive Venn diagram, summary counts, and functional summaries of the disjunction and intersection of clusters shared between species are displayed as part of the OrthoVenn result. OrthoVenn also includes in-depth views of the clusters using various sequence analysis tools. Furthermore, OrthoVenn identifies orthologous clusters of single copy genes and allows for a customized search of clusters of specific genes through key words or BLAST. OrthoVenn is an efficient and user-friendly web server freely accessible at http://probes.pw.usda.gov/OrthoVenn or http://aegilops.wheat.ucdavis.edu/OrthoVenn. © The Author(s) 2015. Published by Oxford University Press on behalf of Nucleic Acids Research.

Secure web book to store structural genomics research data.

PubMed

Manjasetty, Babu A; Höppner, Klaus; Mueller, Uwe; Heinemann, Udo

2003-01-01

Recently established collaborative structural genomics programs aim at significantly accelerating the crystal structure analysis of proteins. These large-scale projects require efficient data management systems to ensure seamless collaboration between different groups of scientists working towards the same goal. Within the Berlin-based Protein Structure Factory, the synchrotron X-ray data collection and the subsequent crystal structure analysis tasks are located at BESSY, a third-generation synchrotron source. To organize file-based communication and data transfer at the BESSY site of the Protein Structure Factory, we have developed the web-based BCLIMS, the BESSY Crystallography Laboratory Information Management System. BCLIMS is a relational data management system which is powered by MySQL as the database engine and Apache HTTP as the web server. The database interface routines are written in Python programing language. The software is freely available to academic users. Here we describe the storage, retrieval and manipulation of laboratory information, mainly pertaining to the synchrotron X-ray diffraction experiments and the subsequent protein structure analysis, using BCLIMS.

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

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.

Hymenoptera Genome Database: integrating genome annotations in HymenopteraMine.

PubMed

Elsik, Christine G; Tayal, Aditi; Diesh, Colin M; Unni, Deepak R; Emery, Marianne L; Nguyen, Hung N; Hagen, Darren E

2016-01-04

We report an update of the Hymenoptera Genome Database (HGD) (http://HymenopteraGenome.org), a model organism database for insect species of the order Hymenoptera (ants, bees and wasps). HGD maintains genomic data for 9 bee species, 10 ant species and 1 wasp, including the versions of genome and annotation data sets published by the genome sequencing consortiums and those provided by NCBI. A new data-mining warehouse, HymenopteraMine, based on the InterMine data warehousing system, integrates the genome data with data from external sources and facilitates cross-species analyses based on orthology. New genome browsers and annotation tools based on JBrowse/WebApollo provide easy genome navigation, and viewing of high throughput sequence data sets and can be used for collaborative genome annotation. All of the genomes and annotation data sets are combined into a single BLAST server that allows users to select and combine sequence data sets to search. © The Author(s) 2015. Published by Oxford University Press on behalf of Nucleic Acids Research.

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

CottonGen: a genomics, genetics and breeding database for cotton research

USDA-ARS?s Scientific Manuscript database

CottonGen (http://www.cottongen.org) is a curated and integrated web-based relational database providing access to publicly available genomic, genetic and breeding data for cotton. CottonGen supercedes CottonDB and the Cotton Marker Database, with enhanced tools for easier data sharing, mining, vis...

A web-based genome browser for 'SNP-aware' assay design

USDA-ARS?s Scientific Manuscript database

Human and animal genomes contain an abundance of single nucleotide polymorphisms (SNPs) that are useful for genetic testing. However, the relatively large number of SNPs present in diverse populations can pose serious problems when designing assays. It is important to “mask” some SNP positions so ...

What tangled web: barriers to rampant horizontal gene transfer.

PubMed

Kurland, Charles G

2005-07-01

Dawkins in his The Selfish Gene(1) quite aptly applies the term "selfish" to parasitic repetitive DNA sequences endemic to eukaryotic genomes, especially vertebrates. Doolittle and Sapienza(2) as well as Orgel and Crick(3) enlivened this notion of selfish DNA with the identification of such repetitive sequences as remnants of mobile elements such as transposons. In addition, Orgel and Crick(3) associated parasitic DNA with a potential to outgrow their host genomes by propagating both vertically via conventional genome replication as well as infectiously by horizontal gene transfer (HGT) to other genomes. Still later, Doolittle(4) speculated that unchecked HGT between unrelated genomes so complicates phylogeny that the conventional representation of a tree of life would have to be replaced by a thicket or a web of life.(4) In contrast, considerable data now show that reconstructions based on whole genome sequences are consistent with the conventional "tree of life".(5-10) Here, we identify natural barriers that protect modern genome populations from the inroads of rampant HGT. Copyright (c) 2005 Wiley Periodicals, Inc.

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

CyanoClust: comparative genome resources of cyanobacteria and plastids.

PubMed

Sasaki, Naobumi V; Sato, Naoki

2010-01-01

Cyanobacteria, which perform oxygen-evolving photosynthesis as do chloroplasts of plants and algae, are one of the best-studied prokaryotic phyla and one from which many representative genomes have been sequenced. Lack of a suitable comparative genomic database has been a problem in cyanobacterial genomics because many proteins involved in physiological functions such as photosynthesis and nitrogen fixation are not catalogued in commonly used databases, such as Clusters of Orthologous Proteins (COG). CyanoClust is a database of homolog groups in cyanobacteria and plastids that are produced by the program Gclust. We have developed a web-server system for the protein homology database featuring cyanobacteria and plastids. Database URL: http://cyanoclust.c.u-tokyo.ac.jp/.

miRNAtools: Advanced Training Using the miRNA Web of Knowledge.

PubMed

Stępień, Ewa Ł; Costa, Marina C; Enguita, Francisco J

2018-02-16

Micro-RNAs (miRNAs) are small non-coding RNAs that act as negative regulators of the genomic output. Their intrinsic importance within cell biology and human disease is well known. Their mechanism of action based on the base pairing binding to their cognate targets have helped the development not only of many computer applications for the prediction of miRNA target recognition but also of specific applications for functional assessment and analysis. Learning about miRNA function requires practical training in the use of specific computer and web-based applications that are complementary to wet-lab studies. In order to guide the learning process about miRNAs, we have created miRNAtools (http://mirnatools.eu), a web repository of miRNA tools and tutorials. This article compiles tools with which miRNAs and their regulatory action can be analyzed and that function to collect and organize information dispersed on the web. The miRNAtools website contains a collection of tutorials that can be used by students and tutors engaged in advanced training courses. The tutorials engage in analyses of the functions of selected miRNAs, starting with their nomenclature and genomic localization and finishing with their involvement in specific cellular functions.

miRNAFold: a web server for fast miRNA precursor prediction in genomes.

PubMed

Tav, Christophe; Tempel, Sébastien; Poligny, Laurent; Tahi, Fariza

2016-07-08

Computational methods are required for prediction of non-coding RNAs (ncRNAs), which are involved in many biological processes, especially at post-transcriptional level. Among these ncRNAs, miRNAs have been largely studied and biologists need efficient and fast tools for their identification. In particular, ab initio methods are usually required when predicting novel miRNAs. Here we present a web server dedicated for miRNA precursors identification at a large scale in genomes. It is based on an algorithm called miRNAFold that allows predicting miRNA hairpin structures quickly with high sensitivity. miRNAFold is implemented as a web server with an intuitive and user-friendly interface, as well as a standalone version. The web server is freely available at: http://EvryRNA.ibisc.univ-evry.fr/miRNAFold. © The Author(s) 2016. Published by Oxford University Press on behalf of Nucleic Acids Research.

CROPPER: a metagene creator resource for cross-platform and cross-species compendium studies.

PubMed

Paananen, Jussi; Storvik, Markus; Wong, Garry

2006-09-22

Current genomic research methods provide researchers with enormous amounts of data. Combining data from different high-throughput research technologies commonly available in biological databases can lead to novel findings and increase research efficiency. However, combining data from different heterogeneous sources is often a very arduous task. These sources can be different microarray technology platforms, genomic databases, or experiments performed on various species. Our aim was to develop a software program that could facilitate the combining of data from heterogeneous sources, and thus allow researchers to perform genomic cross-platform/cross-species studies and to use existing experimental data for compendium studies. We have developed a web-based software resource, called CROPPER that uses the latest genomic information concerning different data identifiers and orthologous genes from the Ensembl database. CROPPER can be used to combine genomic data from different heterogeneous sources, allowing researchers to perform cross-platform/cross-species compendium studies without the need for complex computational tools or the requirement of setting up one's own in-house database. We also present an example of a simple cross-platform/cross-species compendium study based on publicly available Parkinson's disease data derived from different sources. CROPPER is a user-friendly and freely available web-based software resource that can be successfully used for cross-species/cross-platform compendium studies.

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

VectorBase: a data resource for invertebrate vector genomics

PubMed Central

Lawson, Daniel; Arensburger, Peter; Atkinson, Peter; Besansky, Nora J.; Bruggner, Robert V.; Butler, Ryan; Campbell, Kathryn S.; Christophides, George K.; Christley, Scott; Dialynas, Emmanuel; Hammond, Martin; Hill, Catherine A.; Konopinski, Nathan; Lobo, Neil F.; MacCallum, Robert M.; Madey, Greg; Megy, Karine; Meyer, Jason; Redmond, Seth; Severson, David W.; Stinson, Eric O.; Topalis, Pantelis; Birney, Ewan; Gelbart, William M.; Kafatos, Fotis C.; Louis, Christos; Collins, Frank H.

2009-01-01

VectorBase (http://www.vectorbase.org) is an NIAID-funded Bioinformatic Resource Center focused on invertebrate vectors of human pathogens. VectorBase annotates and curates vector genomes providing a web accessible integrated resource for the research community. Currently, VectorBase contains genome information for three mosquito species: Aedes aegypti, Anopheles gambiae and Culex quinquefasciatus, a body louse Pediculus humanus and a tick species Ixodes scapularis. Since our last report VectorBase has initiated a community annotation system, a microarray and gene expression repository and controlled vocabularies for anatomy and insecticide resistance. We have continued to develop both the software infrastructure and tools for interrogating the stored data. PMID:19028744

DiRE: identifying distant regulatory elements of co-expressed genes

PubMed Central

Gotea, Valer; Ovcharenko, Ivan

2008-01-01

Regulation of gene expression in eukaryotic genomes is established through a complex cooperative activity of proximal promoters and distant regulatory elements (REs) such as enhancers, repressors and silencers. We have developed a web server named DiRE, based on the Enhancer Identification (EI) method, for predicting distant regulatory elements in higher eukaryotic genomes, namely for determining their chromosomal location and functional characteristics. The server uses gene co-expression data, comparative genomics and profiles of transcription factor binding sites (TFBSs) to determine TFBS-association signatures that can be used for discriminating specific regulatory functions. DiRE's unique feature is its ability to detect REs outside of proximal promoter regions, as it takes advantage of the full gene locus to conduct the search. DiRE can predict common REs for any set of input genes for which the user has prior knowledge of co-expression, co-function or other biologically meaningful grouping. The server predicts function-specific REs consisting of clusters of specifically-associated TFBSs and it also scores the association of individual transcription factors (TFs) with the biological function shared by the group of input genes. Its integration with the Array2BIO server allows users to start their analysis with raw microarray expression data. The DiRE web server is freely available at http://dire.dcode.org. PMID:18487623

Ensembl 2002: accommodating comparative genomics.

PubMed

Clamp, M; Andrews, D; Barker, D; Bevan, P; Cameron, G; Chen, Y; Clark, L; Cox, T; Cuff, J; Curwen, V; Down, T; Durbin, R; Eyras, E; Gilbert, J; Hammond, M; Hubbard, T; Kasprzyk, A; Keefe, D; Lehvaslaiho, H; Iyer, V; Melsopp, C; Mongin, E; Pettett, R; Potter, S; Rust, A; Schmidt, E; Searle, S; Slater, G; Smith, J; Spooner, W; Stabenau, A; Stalker, J; Stupka, E; Ureta-Vidal, A; Vastrik, I; Birney, E

2003-01-01

The Ensembl (http://www.ensembl.org/) database project provides a bioinformatics framework to organise biology around the sequences of large genomes. It is a comprehensive source of stable automatic annotation of human, mouse and other genome sequences, available as either an interactive web site or as flat files. Ensembl also integrates manually annotated gene structures from external sources where available. 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. These range from sequence analysis to data storage and visualisation and installations exist around the world in both companies and at academic sites. With both human and mouse genome sequences available and more vertebrate sequences to follow, many of the recent developments in Ensembl have focusing on developing automatic comparative genome analysis and visualisation.

GREAT: a web portal for Genome Regulatory Architecture Tools

PubMed Central

Bouyioukos, Costas; Bucchini, François; Elati, Mohamed; Képès, François

2016-01-01

GREAT (Genome REgulatory Architecture Tools) is a novel web portal for tools designed to generate user-friendly and biologically useful analysis of genome architecture and regulation. The online tools of GREAT are freely accessible and compatible with essentially any operating system which runs a modern browser. GREAT is based on the analysis of genome layout -defined as the respective positioning of co-functional genes- and its relation with chromosome architecture and gene expression. GREAT tools allow users to systematically detect regular patterns along co-functional genomic features in an automatic way consisting of three individual steps and respective interactive visualizations. In addition to the complete analysis of regularities, GREAT tools enable the use of periodicity and position information for improving the prediction of transcription factor binding sites using a multi-view machine learning approach. The outcome of this integrative approach features a multivariate analysis of the interplay between the location of a gene and its regulatory sequence. GREAT results are plotted in web interactive graphs and are available for download either as individual plots, self-contained interactive pages or as machine readable tables for downstream analysis. The GREAT portal can be reached at the following URL https://absynth.issb.genopole.fr/GREAT and each individual GREAT tool is available for downloading. PMID:27151196

MendeLIMS: a web-based laboratory information management system for clinical genome sequencing.

PubMed

Grimes, Susan M; Ji, Hanlee P

2014-08-27

Large clinical genomics studies using next generation DNA sequencing require the ability to select and track samples from a large population of patients through many experimental steps. With the number of clinical genome sequencing studies increasing, it is critical to maintain adequate laboratory information management systems to manage the thousands of patient samples that are subject to this type of genetic analysis. To meet the needs of clinical population studies using genome sequencing, we developed a web-based laboratory information management system (LIMS) with a flexible configuration that is adaptable to continuously evolving experimental protocols of next generation DNA sequencing technologies. Our system is referred to as MendeLIMS, is easily implemented with open source tools and is also highly configurable and extensible. MendeLIMS has been invaluable in the management of our clinical genome sequencing studies. We maintain a publicly available demonstration version of the application for evaluation purposes at http://mendelims.stanford.edu. MendeLIMS is programmed in Ruby on Rails (RoR) and accesses data stored in SQL-compliant relational databases. Software is freely available for non-commercial use at http://dna-discovery.stanford.edu/software/mendelims/.

PWMScan: a fast tool for scanning entire genomes with a position-specific weight matrix.

PubMed

Ambrosini, Giovanna; Groux, Romain; Bucher, Philipp

2018-03-05

Transcription factors (TFs) regulate gene expression by binding to specific short DNA sequences of 5 to 20-bp to regulate the rate of transcription of genetic information from DNA to messenger RNA. We present PWMScan, a fast web-based tool to scan server-resident genomes for matches to a user-supplied PWM or TF binding site model from a public database. The web server and source code are available at http://ccg.vital-it.ch/pwmscan and https://sourceforge.net/projects/pwmscan, respectively. giovanna.ambrosini@epfl.ch. SUPPLEMENTARY DATA ARE AVAILABLE AT BIOINFORMATICS ONLINE.

Bluejay 1.0: genome browsing and comparison with rich customization provision and dynamic resource linking

PubMed Central

Soh, Jung; Gordon, Paul MK; Taschuk, Morgan L; Dong, Anguo; Ah-Seng, Andrew C; Turinsky, Andrei L; Sensen, Christoph W

2008-01-01

Background The Bluejay genome browser has been developed over several years to address the challenges posed by the ever increasing number of data types as well as the increasing volume of data in genome research. Beginning with a browser capable of rendering views of XML-based genomic information and providing scalable vector graphics output, we have now completed version 1.0 of the system with many additional features. Our development efforts were guided by our observation that biologists who use both gene expression profiling and comparative genomics gain functional insights above and beyond those provided by traditional per-gene analyses. Results Bluejay 1.0 is a genome viewer integrating genome annotation with: (i) gene expression information; and (ii) comparative analysis with an unlimited number of other genomes in the same view. This allows the biologist to see a gene not just in the context of its genome, but also its regulation and its evolution. Bluejay now has rich provision for personalization by users: (i) numerous display customization features; (ii) the availability of waypoints for marking multiple points of interest on a genome and subsequently utilizing them; and (iii) the ability to take user relevance feedback of annotated genes or textual items to offer personalized recommendations. Bluejay 1.0 also embeds the Seahawk browser for the Moby protocol, enabling users to seamlessly invoke hundreds of Web Services on genomic data of interest without any hard-coding. Conclusion Bluejay offers a unique set of customizable genome-browsing features, with the goal of allowing biologists to quickly focus on, analyze, compare, and retrieve related information on the parts of the genomic data they are most interested in. We expect these capabilities of Bluejay to benefit the many biologists who want to answer complex questions using the information available from completely sequenced genomes. PMID:18940007

SNiPlay: a web-based tool for detection, management and analysis of SNPs. Application to grapevine diversity projects.

PubMed

Dereeper, Alexis; Nicolas, Stéphane; Le Cunff, Loïc; Bacilieri, Roberto; Doligez, Agnès; Peros, Jean-Pierre; Ruiz, Manuel; This, Patrice

2011-05-05

High-throughput re-sequencing, new genotyping technologies and the availability of reference genomes allow the extensive characterization of Single Nucleotide Polymorphisms (SNPs) and insertion/deletion events (indels) in many plant species. The rapidly increasing amount of re-sequencing and genotyping data generated by large-scale genetic diversity projects requires the development of integrated bioinformatics tools able to efficiently manage, analyze, and combine these genetic data with genome structure and external data. In this context, we developed SNiPlay, a flexible, user-friendly and integrative web-based tool dedicated to polymorphism discovery and analysis. It integrates:1) a pipeline, freely accessible through the internet, combining existing softwares with new tools to detect SNPs and to compute different types of statistical indices and graphical layouts for SNP data. From standard sequence alignments, genotyping data or Sanger sequencing traces given as input, SNiPlay detects SNPs and indels events and outputs submission files for the design of Illumina's SNP chips. Subsequently, it sends sequences and genotyping data into a series of modules in charge of various processes: physical mapping to a reference genome, annotation (genomic position, intron/exon location, synonymous/non-synonymous substitutions), SNP frequency determination in user-defined groups, haplotype reconstruction and network, linkage disequilibrium evaluation, and diversity analysis (Pi, Watterson's Theta, Tajima's D).Furthermore, the pipeline allows the use of external data (such as phenotype, geographic origin, taxa, stratification) to define groups and compare statistical indices.2) a database storing polymorphisms, genotyping data and grapevine sequences released by public and private projects. It allows the user to retrieve SNPs using various filters (such as genomic position, missing data, polymorphism type, allele frequency), to compare SNP patterns between populations, and to export genotyping data or sequences in various formats. Our experiments on grapevine genetic projects showed that SNiPlay allows geneticists to rapidly obtain advanced results in several key research areas of plant genetic diversity. Both the management and treatment of large amounts of SNP data are rendered considerably easier for end-users through automation and integration. Current developments are taking into account new advances in high-throughput technologies.SNiPlay is available at: http://sniplay.cirad.fr/.

MODEST: a web-based design tool for oligonucleotide-mediated genome engineering and recombineering

PubMed Central

Bonde, Mads T.; Klausen, Michael S.; Anderson, Mads V.; Wallin, Annika I.N.; Wang, Harris H.; Sommer, Morten O.A.

2014-01-01

Recombineering and multiplex automated genome engineering (MAGE) offer the possibility to rapidly modify multiple genomic or plasmid sites at high efficiencies. This enables efficient creation of genetic variants including both single mutants with specifically targeted modifications as well as combinatorial cell libraries. Manual design of oligonucleotides for these approaches can be tedious, time-consuming, and may not be practical for larger projects targeting many genomic sites. At present, the change from a desired phenotype (e.g. altered expression of a specific protein) to a designed MAGE oligo, which confers the corresponding genetic change, is performed manually. To address these challenges, we have developed the MAGE Oligo Design Tool (MODEST). This web-based tool allows designing of MAGE oligos for (i) tuning translation rates by modifying the ribosomal binding site, (ii) generating translational gene knockouts and (iii) introducing other coding or non-coding mutations, including amino acid substitutions, insertions, deletions and point mutations. The tool automatically designs oligos based on desired genotypic or phenotypic changes defined by the user, which can be used for high efficiency recombineering and MAGE. MODEST is available for free and is open to all users at http://modest.biosustain.dtu.dk. PMID:24838561

RSAT: regulatory sequence analysis tools.

PubMed

Thomas-Chollier, Morgane; Sand, Olivier; Turatsinze, Jean-Valéry; Janky, Rekin's; Defrance, Matthieu; Vervisch, Eric; Brohée, Sylvain; van Helden, Jacques

2008-07-01

The regulatory sequence analysis tools (RSAT, http://rsat.ulb.ac.be/rsat/) is a software suite that integrates a wide collection of modular tools for the detection of cis-regulatory elements in genome sequences. The suite includes programs for sequence retrieval, pattern discovery, phylogenetic footprint detection, pattern matching, genome scanning and feature map drawing. Random controls can be performed with random gene selections or by generating random sequences according to a variety of background models (Bernoulli, Markov). Beyond the original word-based pattern-discovery tools (oligo-analysis and dyad-analysis), we recently added a battery of tools for matrix-based detection of cis-acting elements, with some original features (adaptive background models, Markov-chain estimation of P-values) that do not exist in other matrix-based scanning tools. The web server offers an intuitive interface, where each program can be accessed either separately or connected to the other tools. In addition, the tools are now available as web services, enabling their integration in programmatic workflows. Genomes are regularly updated from various genome repositories (NCBI and EnsEMBL) and 682 organisms are currently supported. Since 1998, the tools have been used by several hundreds of researchers from all over the world. Several predictions made with RSAT were validated experimentally and published.

Kaptive Web: User-Friendly Capsule and Lipopolysaccharide Serotype Prediction for Klebsiella Genomes.

PubMed

Wick, Ryan R; Heinz, Eva; Holt, Kathryn E; Wyres, Kelly L

2018-06-01

As whole-genome sequencing becomes an established component of the microbiologist's toolbox, it is imperative that researchers, clinical microbiologists, and public health professionals have access to genomic analysis tools for the rapid extraction of epidemiologically and clinically relevant information. For the Gram-negative hospital pathogens such as Klebsiella pneumoniae , initial efforts have focused on the detection and surveillance of antimicrobial resistance genes and clones. However, with the resurgence of interest in alternative infection control strategies targeting Klebsiella surface polysaccharides, the ability to extract information about these antigens is increasingly important. Here we present Kaptive Web, an online tool for the rapid typing of Klebsiella K and O loci, which encode the polysaccharide capsule and lipopolysaccharide O antigen, respectively. Kaptive Web enables users to upload and analyze genome assemblies in a web browser. The results can be downloaded in tabular format or explored in detail via the graphical interface, making it accessible for users at all levels of computational expertise. We demonstrate Kaptive Web's utility by analyzing >500 K. pneumoniae genomes. We identify extensive K and O locus diversity among 201 genomes belonging to the carbapenemase-associated clonal group 258 (25 K and 6 O loci). The characterization of a further 309 genomes indicated that such diversity is common among the multidrug-resistant clones and that these loci represent useful epidemiological markers for strain subtyping. These findings reinforce the need for rapid, reliable, and accessible typing methods such as Kaptive Web. Kaptive Web is available for use at http://kaptive.holtlab.net/, and the source code is available at https://github.com/kelwyres/Kaptive-Web. Copyright © 2018 Wick et al.

A knowledge base for tracking the impact of genomics on population health.

PubMed

Yu, Wei; Gwinn, Marta; Dotson, W David; Green, Ridgely Fisk; Clyne, Mindy; Wulf, Anja; Bowen, Scott; Kolor, Katherine; Khoury, Muin J

2016-12-01

We created an online knowledge base (the Public Health Genomics Knowledge Base (PHGKB)) to provide systematically curated and updated information that bridges population-based research on genomics with clinical and public health applications. Weekly horizon scanning of a wide variety of online resources is used to retrieve relevant scientific publications, guidelines, and commentaries. After curation by domain experts, links are deposited into Web-based databases. PHGKB currently consists of nine component databases. Users can search the entire knowledge base or search one or more component databases directly and choose options for customizing the display of their search results. PHGKB offers researchers, policy makers, practitioners, and the general public a way to find information they need to understand the complicated landscape of genomics and population health.Genet Med 18 12, 1312-1314.

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 .

OrthoMCL: Identification of Ortholog Groups for Eukaryotic Genomes

PubMed Central

Li, Li; Stoeckert, Christian J.; Roos, David S.

2003-01-01

The identification of orthologous groups is useful for genome annotation, studies on gene/protein evolution, comparative genomics, and the identification of taxonomically restricted sequences. Methods successfully exploited for prokaryotic genome analysis have proved difficult to apply to eukaryotes, however, as larger genomes may contain multiple paralogous genes, and sequence information is often incomplete. OrthoMCL provides a scalable method for constructing orthologous groups across multiple eukaryotic taxa, using a Markov Cluster algorithm to group (putative) orthologs and paralogs. This method performs similarly to the INPARANOID algorithm when applied to two genomes, but can be extended to cluster orthologs from multiple species. OrthoMCL clusters are coherent with groups identified by EGO, but improved recognition of “recent” paralogs permits overlapping EGO groups representing the same gene to be merged. Comparison with previously assigned EC annotations suggests a high degree of reliability, implying utility for automated eukaryotic genome annotation. OrthoMCL has been applied to the proteome data set from seven publicly available genomes (human, fly, worm, yeast, Arabidopsis, the malaria parasite Plasmodium falciparum, and Escherichia coli). A Web interface allows queries based on individual genes or user-defined phylogenetic patterns (http://www.cbil.upenn.edu/gene-family). Analysis of clusters incorporating P. falciparum genes identifies numerous enzymes that were incompletely annotated in first-pass annotation of the parasite genome. PMID:12952885

Coloc-stats: a unified web interface to perform colocalization analysis of genomic features.

PubMed

Simovski, Boris; Kanduri, Chakravarthi; Gundersen, Sveinung; Titov, Dmytro; Domanska, Diana; Bock, Christoph; Bossini-Castillo, Lara; Chikina, Maria; Favorov, Alexander; Layer, Ryan M; Mironov, Andrey A; Quinlan, Aaron R; Sheffield, Nathan C; Trynka, Gosia; Sandve, Geir K

2018-06-05

Functional genomics assays produce sets of genomic regions as one of their main outputs. To biologically interpret such region-sets, researchers often use colocalization analysis, where the statistical significance of colocalization (overlap, spatial proximity) between two or more region-sets is tested. Existing colocalization analysis tools vary in the statistical methodology and analysis approaches, thus potentially providing different conclusions for the same research question. As the findings of colocalization analysis are often the basis for follow-up experiments, it is helpful to use several tools in parallel and to compare the results. We developed the Coloc-stats web service to facilitate such analyses. Coloc-stats provides a unified interface to perform colocalization analysis across various analytical methods and method-specific options (e.g. colocalization measures, resolution, null models). Coloc-stats helps the user to find a method that supports their experimental requirements and allows for a straightforward comparison across methods. Coloc-stats is implemented as a web server with a graphical user interface that assists users with configuring their colocalization analyses. Coloc-stats is freely available at https://hyperbrowser.uio.no/coloc-stats/.

OpenFlyData: an exemplar data web integrating gene expression data on the fruit fly Drosophila melanogaster.

PubMed

Miles, Alistair; Zhao, Jun; Klyne, Graham; White-Cooper, Helen; Shotton, David

2010-10-01

Integrating heterogeneous data across distributed sources is a major requirement for in silico bioinformatics supporting translational research. For example, genome-scale data on patterns of gene expression in the fruit fly Drosophila melanogaster are widely used in functional genomic studies in many organisms to inform candidate gene selection and validate experimental results. However, current data integration solutions tend to be heavy weight, and require significant initial and ongoing investment of effort. Development of a common Web-based data integration infrastructure (a.k.a. data web), using Semantic Web standards, promises to alleviate these difficulties, but little is known about the feasibility, costs, risks or practical means of migrating to such an infrastructure. We describe the development of OpenFlyData, a proof-of-concept system integrating gene expression data on D. melanogaster, combining Semantic Web standards with light-weight approaches to Web programming based on Web 2.0 design patterns. To support researchers designing and validating functional genomic studies, OpenFlyData includes user-facing search applications providing intuitive access to and comparison of gene expression data from FlyAtlas, the BDGP in situ database, and FlyTED, using data from FlyBase to expand and disambiguate gene names. OpenFlyData's services are also openly accessible, and are available for reuse by other bioinformaticians and application developers. Semi-automated methods and tools were developed to support labour- and knowledge-intensive tasks involved in deploying SPARQL services. These include methods for generating ontologies and relational-to-RDF mappings for relational databases, which we illustrate using the FlyBase Chado database schema; and methods for mapping gene identifiers between databases. The advantages of using Semantic Web standards for biomedical data integration are discussed, as are open issues. In particular, although the performance of open source SPARQL implementations is sufficient to query gene expression data directly from user-facing applications such as Web-based data fusions (a.k.a. mashups), we found open SPARQL endpoints to be vulnerable to denial-of-service-type problems, which must be mitigated to ensure reliability of services based on this standard. These results are relevant to data integration activities in translational bioinformatics. The gene expression search applications and SPARQL endpoints developed for OpenFlyData are deployed at http://openflydata.org. FlyUI, a library of JavaScript widgets providing re-usable user-interface components for Drosophila gene expression data, is available at http://flyui.googlecode.com. Software and ontologies to support transformation of data from FlyBase, FlyAtlas, BDGP and FlyTED to RDF are available at http://openflydata.googlecode.com. SPARQLite, an implementation of the SPARQL protocol, is available at http://sparqlite.googlecode.com. All software is provided under the GPL version 3 open source license.

The EMBL nucleotide sequence database

PubMed Central

Stoesser, Guenter; Baker, Wendy; van den Broek, Alexandra; Camon, Evelyn; Garcia-Pastor, Maria; Kanz, Carola; Kulikova, Tamara; Lombard, Vincent; Lopez, Rodrigo; Parkinson, Helen; Redaschi, Nicole; Sterk, Peter; Stoehr, Peter; Tuli, Mary Ann

2001-01-01

The EMBL Nucleotide Sequence Database (http://www.ebi.ac.uk/embl/) is maintained at the European Bioinformatics Institute (EBI) in an international collaboration with the DNA Data Bank of Japan (DDBJ) and GenBank at the NCBI (USA). Data is exchanged amongst the collaborating databases on a daily basis. The major contributors to the EMBL database are individual authors and genome project groups. Webin is the preferred web-based submission system for individual submitters, whilst automatic procedures allow incorporation of sequence data from large-scale genome sequencing centres and from the European Patent Office (EPO). Database releases are produced quarterly. Network services allow free access to the most up-to-date data collection via ftp, email and World Wide Web interfaces. EBI’s Sequence Retrieval System (SRS), a network browser for databanks in molecular biology, integrates and links the main nucleotide and protein databases plus many specialized databases. For sequence similarity searching a variety of tools (e.g. Blitz, Fasta, BLAST) are available which allow external users to compare their own sequences against the latest data in the EMBL Nucleotide Sequence Database and SWISS-PROT. PMID:11125039

GoWeb: a semantic search engine for the life science web.

PubMed

Dietze, Heiko; Schroeder, Michael

2009-10-01

Current search engines are keyword-based. Semantic technologies promise a next generation of semantic search engines, which will be able to answer questions. Current approaches either apply natural language processing to unstructured text or they assume the existence of structured statements over which they can reason. Here, we introduce a third approach, GoWeb, which combines classical keyword-based Web search with text-mining and ontologies to navigate large results sets and facilitate question answering. We evaluate GoWeb on three benchmarks of questions on genes and functions, on symptoms and diseases, and on proteins and diseases. The first benchmark is based on the BioCreAtivE 1 Task 2 and links 457 gene names with 1352 functions. GoWeb finds 58% of the functional GeneOntology annotations. The second benchmark is based on 26 case reports and links symptoms with diseases. GoWeb achieves 77% success rate improving an existing approach by nearly 20%. The third benchmark is based on 28 questions in the TREC genomics challenge and links proteins to diseases. GoWeb achieves a success rate of 79%. GoWeb's combination of classical Web search with text-mining and ontologies is a first step towards answering questions in the biomedical domain. GoWeb is online at: http://www.gopubmed.org/goweb.

ViralEpi v1.0: a high-throughput spectrum of viral epigenomic methylation profiles from diverse diseases.

PubMed

Khan, Mohd Shoaib; Gupta, Amit Kumar; Kumar, Manoj

2016-01-01

To develop a computational resource for viral epigenomic methylation profiles from diverse diseases. Methylation patterns of Epstein-Barr virus and hepatitis B virus genomic regions are provided as web platform developed using open source Linux-Apache-MySQL-PHP (LAMP) bundle: programming and scripting languages, that is, HTML, JavaScript and PERL. A comprehensive and integrated web resource ViralEpi v1.0 is developed providing well-organized compendium of methylation events and statistical analysis associated with several diseases. Additionally, it also facilitates 'Viral EpiGenome Browser' for user-affable browsing experience using JavaScript-based JBrowse. This web resource would be helpful for research community engaged in studying epigenetic biomarkers for appropriate prognosis and diagnosis of diseases and its various stages.

CsSNP: A Web-Based Tool for the Detecting of Comparative Segments SNPs.

PubMed

Wang, Yi; Wang, Shuangshuang; Zhou, Dongjie; Yang, Shuai; Xu, Yongchao; Yang, Chao; Yang, Long

2016-07-01

SNP (single nucleotide polymorphism) is a popular tool for the study of genetic diversity, evolution, and other areas. Therefore, it is necessary to develop a convenient, utility, robust, rapid, and open source detecting-SNP tool for all researchers. Since the detection of SNPs needs special software and series steps including alignment, detection, analysis and present, the study of SNPs is limited for nonprofessional users. CsSNP (Comparative segments SNP, http://biodb.sdau.edu.cn/cssnp/ ) is a freely available web tool based on the Blat, Blast, and Perl programs to detect comparative segments SNPs and to show the detail information of SNPs. The results are filtered and presented in the statistics figure and a Gbrowse map. This platform contains the reference genomic sequences and coding sequences of 60 plant species, and also provides new opportunities for the users to detect SNPs easily. CsSNP is provided a convenient tool for nonprofessional users to find comparative segments SNPs in their own sequences, and give the users the information and the analysis of SNPs, and display these data in a dynamic map. It provides a new method to detect SNPs and may accelerate related studies.

Googling DNA sequences on the World Wide Web.

PubMed

Hajibabaei, Mehrdad; Singer, Gregory A C

2009-11-10

New web-based technologies provide an excellent opportunity for sharing and accessing information and using web as a platform for interaction and collaboration. Although several specialized tools are available for analyzing DNA sequence information, conventional web-based tools have not been utilized for bioinformatics applications. We have developed a novel algorithm and implemented it for searching species-specific genomic sequences, DNA barcodes, by using popular web-based methods such as Google. We developed an alignment independent character based algorithm based on dividing a sequence library (DNA barcodes) and query sequence to words. The actual search is conducted by conventional search tools such as freely available Google Desktop Search. We implemented our algorithm in two exemplar packages. We developed pre and post-processing software to provide customized input and output services, respectively. Our analysis of all publicly available DNA barcode sequences shows a high accuracy as well as rapid results. Our method makes use of conventional web-based technologies for specialized genetic data. It provides a robust and efficient solution for sequence search on the web. The integration of our search method for large-scale sequence libraries such as DNA barcodes provides an excellent web-based tool for accessing this information and linking it to other available categories of information on the web.

MoccaDB - an integrative database for functional, comparative and diversity studies in the Rubiaceae family

PubMed Central

Plechakova, Olga; Tranchant-Dubreuil, Christine; Benedet, Fabrice; Couderc, Marie; Tinaut, Alexandra; Viader, Véronique; De Block, Petra; Hamon, Perla; Campa, Claudine; de Kochko, Alexandre; Hamon, Serge; Poncet, Valérie

2009-01-01

Background In the past few years, functional genomics information has been rapidly accumulating on Rubiaceae species and especially on those belonging to the Coffea genus (coffee trees). An increasing number of expressed sequence tag (EST) data and EST- or genomic-derived microsatellite markers have been generated, together with Conserved Ortholog Set (COS) markers. This considerably facilitates comparative genomics or map-based genetic studies through the common use of orthologous loci across different species. Similar genomic information is available for e.g. tomato or potato, members of the Solanaceae family. Since both Rubiaceae and Solanaceae belong to the Euasterids I (lamiids) integration of information on genetic markers would be possible and lead to more efficient analyses and discovery of key loci involved in important traits such as fruit development, quality, and maturation, or adaptation. Our goal was to develop a comprehensive web data source for integrated information on validated orthologous markers in Rubiaceae. Description MoccaDB is an online MySQL-PHP driven relational database that houses annotated and/or mapped microsatellite markers in Rubiaceae. In its current release, the database stores 638 markers that have been defined on 259 ESTs and 379 genomic sequences. Marker information was retrieved from 11 published works, and completed with original data on 132 microsatellite markers validated in our laboratory. DNA sequences were derived from three Coffea species/hybrids. Microsatellite markers were checked for similarity, in vitro tested for cross-amplification and diversity/polymorphism status in up to 38 Rubiaceae species belonging to the Cinchonoideae and Rubioideae subfamilies. Functional annotation was provided and some markers associated with described metabolic pathways were also integrated. Users can search the database for marker, sequence, map or diversity information through multi-option query forms. The retrieved data can be browsed and downloaded, along with protocols used, using a standard web browser. MoccaDB also integrates bioinformatics tools (CMap viewer and local BLAST) and hyperlinks to related external data sources (NCBI GenBank and PubMed, SOL Genomic Network database). Conclusion We believe that MoccaDB will be extremely useful for all researchers working in the areas of comparative and functional genomics and molecular evolution, in general, and population analysis and association mapping of Rubiaceae and Solanaceae species, in particular. PMID:19788737

The Genomes OnLine Database (GOLD) v.5: a metadata management system based on a four level (meta)genome project classification

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

Reddy, Tatiparthi B. K.; Thomas, Alex D.; Stamatis, Dimitri

The Genomes OnLine Database (GOLD; http://www.genomesonline.org) is a comprehensive online resource to catalog and monitor genetic studies worldwide. GOLD provides up-to-date status on complete and ongoing sequencing projects along with a broad array of curated metadata. Within this paper, we report version 5 (v.5) of the database. The newly designed database schema and web user interface supports several new features including the implementation of a four level (meta)genome project classification system and a simplified intuitive web interface to access reports and launch search tools. The database currently hosts information for about 19 200 studies, 56 000 Biosamples, 56 000 sequencingmore » projects and 39 400 analysis projects. More than just a catalog of worldwide genome projects, GOLD is a manually curated, quality-controlled metadata warehouse. The problems encountered in integrating disparate and varying quality data into GOLD are briefly highlighted. Lastly, GOLD fully supports and follows the Genomic Standards Consortium (GSC) Minimum Information standards.« less

Analysis and visualization of Arabidopsis thaliana GWAS using web 2.0 technologies.

PubMed

Huang, Yu S; Horton, Matthew; Vilhjálmsson, Bjarni J; Seren, Umit; Meng, Dazhe; Meyer, Christopher; Ali Amer, Muhammad; Borevitz, Justin O; Bergelson, Joy; Nordborg, Magnus

2011-01-01

With large-scale genomic data becoming the norm in biological studies, the storing, integrating, viewing and searching of such data have become a major challenge. In this article, we describe the development of an Arabidopsis thaliana database that hosts the geographic information and genetic polymorphism data for over 6000 accessions and genome-wide association study (GWAS) results for 107 phenotypes representing the largest collection of Arabidopsis polymorphism data and GWAS results to date. Taking advantage of a series of the latest web 2.0 technologies, such as Ajax (Asynchronous JavaScript and XML), GWT (Google-Web-Toolkit), MVC (Model-View-Controller) web framework and Object Relationship Mapper, we have created a web-based application (web app) for the database, that offers an integrated and dynamic view of geographic information, genetic polymorphism and GWAS results. Essential search functionalities are incorporated into the web app to aid reverse genetics research. The database and its web app have proven to be a valuable resource to the Arabidopsis community. The whole framework serves as an example of how biological data, especially GWAS, can be presented and accessed through the web. In the end, we illustrate the potential to gain new insights through the web app by two examples, showcasing how it can be used to facilitate forward and reverse genetics research. Database URL: http://arabidopsis.usc.edu/

EXP-PAC: providing comparative analysis and storage of next generation gene expression data.

PubMed

Church, Philip C; Goscinski, Andrzej; Lefèvre, Christophe

2012-07-01

Microarrays and more recently RNA sequencing has led to an increase in available gene expression data. How to manage and store this data is becoming a key issue. In response we have developed EXP-PAC, a web based software package for storage, management and analysis of gene expression and sequence data. Unique to this package is SQL based querying of gene expression data sets, distributed normalization of raw gene expression data and analysis of gene expression data across experiments and species. This package has been populated with lactation data in the international milk genomic consortium web portal (http://milkgenomics.org/). Source code is also available which can be hosted on a Windows, Linux or Mac APACHE server connected to a private or public network (http://mamsap.it.deakin.edu.au/~pcc/Release/EXP_PAC.html). Copyright © 2012 Elsevier Inc. All rights reserved.

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.

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.

PLAZA 3.0: an access point for plant comparative genomics

PubMed Central

Proost, Sebastian; Van Bel, Michiel; Vaneechoutte, Dries; Van de Peer, Yves; Inzé, Dirk; Mueller-Roeber, Bernd; Vandepoele, Klaas

2015-01-01

Comparative sequence analysis has significantly altered our view on the complexity of genome organization and gene functions in different kingdoms. PLAZA 3.0 is designed to make comparative genomics data for plants available through a user-friendly web interface. Structural and functional annotation, gene families, protein domains, phylogenetic trees and detailed information about genome organization can easily be queried and visualized. Compared with the first version released in 2009, which featured nine organisms, the number of integrated genomes is more than four times higher, and now covers 37 plant species. The new species provide a wider phylogenetic range as well as a more in-depth sampling of specific clades, and genomes of additional crop species are present. The functional annotation has been expanded and now comprises data from Gene Ontology, MapMan, UniProtKB/Swiss-Prot, PlnTFDB and PlantTFDB. Furthermore, we improved the algorithms to transfer functional annotation from well-characterized plant genomes to other species. The additional data and new features make PLAZA 3.0 (http://bioinformatics.psb.ugent.be/plaza/) a versatile and comprehensible resource for users wanting to explore genome information to study different aspects of plant biology, both in model and non-model organisms. PMID:25324309

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.

The Global Invertebrate Genomics Alliance (GIGA): Developing Community Resources to Study Diverse Invertebrate Genomes

PubMed Central

2014-01-01

Over 95% of all metazoan (animal) species comprise the “invertebrates,” but very few genomes from these organisms have been sequenced. We have, therefore, formed a “Global Invertebrate Genomics Alliance” (GIGA). Our intent is to build a collaborative network of diverse scientists to tackle major challenges (e.g., species selection, sample collection and storage, sequence assembly, annotation, analytical tools) associated with genome/transcriptome sequencing across a large taxonomic spectrum. We aim to promote standards that will facilitate comparative approaches to invertebrate genomics and collaborations across the international scientific community. Candidate study taxa include species from Porifera, Ctenophora, Cnidaria, Placozoa, Mollusca, Arthropoda, Echinodermata, Annelida, Bryozoa, and Platyhelminthes, among others. GIGA will target 7000 noninsect/nonnematode species, with an emphasis on marine taxa because of the unrivaled phyletic diversity in the oceans. Priorities for selecting invertebrates for sequencing will include, but are not restricted to, their phylogenetic placement; relevance to organismal, ecological, and conservation research; and their importance to fisheries and human health. We highlight benefits of sequencing both whole genomes (DNA) and transcriptomes and also suggest policies for genomic-level data access and sharing based on transparency and inclusiveness. The GIGA Web site (http://giga.nova.edu) has been launched to facilitate this collaborative venture. PMID:24336862

The Global Invertebrate Genomics Alliance (GIGA): developing community resources to study diverse invertebrate genomes.

PubMed

Bracken-Grissom, Heather; Collins, Allen G; Collins, Timothy; Crandall, Keith; Distel, Daniel; Dunn, Casey; Giribet, Gonzalo; Haddock, Steven; Knowlton, Nancy; Martindale, Mark; Medina, Mónica; Messing, Charles; O'Brien, Stephen J; Paulay, Gustav; Putnam, Nicolas; Ravasi, Timothy; Rouse, Greg W; Ryan, Joseph F; Schulze, Anja; Wörheide, Gert; Adamska, Maja; Bailly, Xavier; Breinholt, Jesse; Browne, William E; Diaz, M Christina; Evans, Nathaniel; Flot, Jean-François; Fogarty, Nicole; Johnston, Matthew; Kamel, Bishoy; Kawahara, Akito Y; Laberge, Tammy; Lavrov, Dennis; Michonneau, François; Moroz, Leonid L; Oakley, Todd; Osborne, Karen; Pomponi, Shirley A; Rhodes, Adelaide; Santos, Scott R; Satoh, Nori; Thacker, Robert W; Van de Peer, Yves; Voolstra, Christian R; Welch, David Mark; Winston, Judith; Zhou, Xin

2014-01-01

Over 95% of all metazoan (animal) species comprise the "invertebrates," but very few genomes from these organisms have been sequenced. We have, therefore, formed a "Global Invertebrate Genomics Alliance" (GIGA). Our intent is to build a collaborative network of diverse scientists to tackle major challenges (e.g., species selection, sample collection and storage, sequence assembly, annotation, analytical tools) associated with genome/transcriptome sequencing across a large taxonomic spectrum. We aim to promote standards that will facilitate comparative approaches to invertebrate genomics and collaborations across the international scientific community. Candidate study taxa include species from Porifera, Ctenophora, Cnidaria, Placozoa, Mollusca, Arthropoda, Echinodermata, Annelida, Bryozoa, and Platyhelminthes, among others. GIGA will target 7000 noninsect/nonnematode species, with an emphasis on marine taxa because of the unrivaled phyletic diversity in the oceans. Priorities for selecting invertebrates for sequencing will include, but are not restricted to, their phylogenetic placement; relevance to organismal, ecological, and conservation research; and their importance to fisheries and human health. We highlight benefits of sequencing both whole genomes (DNA) and transcriptomes and also suggest policies for genomic-level data access and sharing based on transparency and inclusiveness. The GIGA Web site (http://giga.nova.edu) has been launched to facilitate this collaborative venture.

blend4php: a PHP API for galaxy

PubMed Central

Wytko, Connor; Soto, Brian; Ficklin, Stephen P.

2017-01-01

Galaxy is a popular framework for execution of complex analytical pipelines typically for large data sets, and is a commonly used for (but not limited to) genomic, genetic and related biological analysis. It provides a web front-end and integrates with high performance computing resources. Here we report the development of the blend4php library that wraps Galaxy’s RESTful API into a PHP-based library. PHP-based web applications can use blend4php to automate execution, monitoring and management of a remote Galaxy server, including its users, workflows, jobs and more. The blend4php library was specifically developed for the integration of Galaxy with Tripal, the open-source toolkit for the creation of online genomic and genetic web sites. However, it was designed as an independent library for use by any application, and is freely available under version 3 of the GNU Lesser General Public License (LPGL v3.0) at https://github.com/galaxyproject/blend4php. Database URL: https://github.com/galaxyproject/blend4php PMID:28077564

SGP-1: Prediction and Validation of Homologous Genes Based on Sequence Alignments

PubMed Central

Wiehe, Thomas; Gebauer-Jung, Steffi; Mitchell-Olds, Thomas; Guigó, Roderic

2001-01-01

Conventional methods of gene prediction rely on the recognition of DNA-sequence signals, the coding potential or the comparison of a genomic sequence with a cDNA, EST, or protein database. Reasons for limited accuracy in many circumstances are species-specific training and the incompleteness of reference databases. Lately, comparative genome analysis has attracted increasing attention. Several analysis tools that are based on human/mouse comparisons are already available. Here, we present a program for the prediction of protein-coding genes, termed SGP-1 (Syntenic Gene Prediction), which is based on the similarity of homologous genomic sequences. In contrast to most existing tools, the accuracy of SGP-1 depends little on species-specific properties such as codon usage or the nucleotide distribution. SGP-1 may therefore be applied to nonstandard model organisms in vertebrates as well as in plants, without the need for extensive parameter training. In addition to predicting genes in large-scale genomic sequences, the program may be useful to validate gene structure annotations from databases. To this end, SGP-1 output also contains comparisons between predicted and annotated gene structures in HTML format. The program can be accessed via a Web server at http://soft.ice.mpg.de/sgp-1. The source code, written in ANSI C, is available on request from the authors. PMID:11544202

The Changing Face of Scientific Discourse: Analysis of Genomic and Proteomic Database Usage and Acceptance.

ERIC Educational Resources Information Center

Brown, Cecelia

2003-01-01

Discusses the growth in use and acceptance of Web-based genomic and proteomic databases (GPD) in scholarly communication. Confirms the role of GPD in the scientific literature cycle, suggests GPD are a storage and retrieval mechanism for molecular biology information, and recommends that existing models of scientific communication be updated to…

A machine learning approach for viral genome classification.

PubMed

Remita, Mohamed Amine; Halioui, Ahmed; Malick Diouara, Abou Abdallah; Daigle, Bruno; Kiani, Golrokh; Diallo, Abdoulaye Baniré

2017-04-11

Advances in cloning and sequencing technology are yielding a massive number of viral genomes. The classification and annotation of these genomes constitute important assets in the discovery of genomic variability, taxonomic characteristics and disease mechanisms. Existing classification methods are often designed for specific well-studied family of viruses. Thus, the viral comparative genomic studies could benefit from more generic, fast and accurate tools for classifying and typing newly sequenced strains of diverse virus families. Here, we introduce a virus classification platform, CASTOR, based on machine learning methods. CASTOR is inspired by a well-known technique in molecular biology: restriction fragment length polymorphism (RFLP). It simulates, in silico, the restriction digestion of genomic material by different enzymes into fragments. It uses two metrics to construct feature vectors for machine learning algorithms in the classification step. We benchmark CASTOR for the classification of distinct datasets of human papillomaviruses (HPV), hepatitis B viruses (HBV) and human immunodeficiency viruses type 1 (HIV-1). Results reveal true positive rates of 99%, 99% and 98% for HPV Alpha species, HBV genotyping and HIV-1 M subtyping, respectively. Furthermore, CASTOR shows a competitive performance compared to well-known HIV-1 specific classifiers (REGA and COMET) on whole genomes and pol fragments. The performance of CASTOR, its genericity and robustness could permit to perform novel and accurate large scale virus studies. The CASTOR web platform provides an open access, collaborative and reproducible machine learning classifiers. CASTOR can be accessed at http://castor.bioinfo.uqam.ca .

The ChIP-Seq tools and web server: a resource for analyzing ChIP-seq and other types of genomic data.

PubMed

Ambrosini, Giovanna; Dreos, René; Kumar, Sunil; Bucher, Philipp

2016-11-18

ChIP-seq and related high-throughput chromatin profilig assays generate ever increasing volumes of highly valuable biological data. To make sense out of it, biologists need versatile, efficient and user-friendly tools for access, visualization and itegrative analysis of such data. Here we present the ChIP-Seq command line tools and web server, implementing basic algorithms for ChIP-seq data analysis starting with a read alignment file. The tools are optimized for memory-efficiency and speed thus allowing for processing of large data volumes on inexpensive hardware. The web interface provides access to a large database of public data. The ChIP-Seq tools have a modular and interoperable design in that the output from one application can serve as input to another one. Complex and innovative tasks can thus be achieved by running several tools in a cascade. The various ChIP-Seq command line tools and web services either complement or compare favorably to related bioinformatics resources in terms of computational efficiency, ease of access to public data and interoperability with other web-based tools. The ChIP-Seq server is accessible at http://ccg.vital-it.ch/chipseq/ .

Cloud computing for comparative genomics

PubMed Central

2010-01-01

Background Large comparative genomics studies and tools are becoming increasingly more compute-expensive as the number of available genome sequences continues to rise. The capacity and cost of local computing infrastructures are likely to become prohibitive with the increase, especially as the breadth of questions continues to rise. Alternative computing architectures, in particular cloud computing environments, may help alleviate this increasing pressure and enable fast, large-scale, and cost-effective comparative genomics strategies going forward. To test this, we redesigned a typical comparative genomics algorithm, the reciprocal smallest distance algorithm (RSD), to run within Amazon's Elastic Computing Cloud (EC2). We then employed the RSD-cloud for ortholog calculations across a wide selection of fully sequenced genomes. Results We ran more than 300,000 RSD-cloud processes within the EC2. These jobs were farmed simultaneously to 100 high capacity compute nodes using the Amazon Web Service Elastic Map Reduce and included a wide mix of large and small genomes. The total computation time took just under 70 hours and cost a total of $6,302 USD. Conclusions The effort to transform existing comparative genomics algorithms from local compute infrastructures is not trivial. However, the speed and flexibility of cloud computing environments provides a substantial boost with manageable cost. The procedure designed to transform the RSD algorithm into a cloud-ready application is readily adaptable to similar comparative genomics problems. PMID:20482786

Cloud computing for comparative genomics.

PubMed

Wall, Dennis P; Kudtarkar, Parul; Fusaro, Vincent A; Pivovarov, Rimma; Patil, Prasad; Tonellato, Peter J

2010-05-18

Large comparative genomics studies and tools are becoming increasingly more compute-expensive as the number of available genome sequences continues to rise. The capacity and cost of local computing infrastructures are likely to become prohibitive with the increase, especially as the breadth of questions continues to rise. Alternative computing architectures, in particular cloud computing environments, may help alleviate this increasing pressure and enable fast, large-scale, and cost-effective comparative genomics strategies going forward. To test this, we redesigned a typical comparative genomics algorithm, the reciprocal smallest distance algorithm (RSD), to run within Amazon's Elastic Computing Cloud (EC2). We then employed the RSD-cloud for ortholog calculations across a wide selection of fully sequenced genomes. We ran more than 300,000 RSD-cloud processes within the EC2. These jobs were farmed simultaneously to 100 high capacity compute nodes using the Amazon Web Service Elastic Map Reduce and included a wide mix of large and small genomes. The total computation time took just under 70 hours and cost a total of $6,302 USD. The effort to transform existing comparative genomics algorithms from local compute infrastructures is not trivial. However, the speed and flexibility of cloud computing environments provides a substantial boost with manageable cost. The procedure designed to transform the RSD algorithm into a cloud-ready application is readily adaptable to similar comparative genomics problems.

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 .

JGI Fungal Genomics Program

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

Grigoriev, Igor V.

2011-03-14

Genomes of energy and environment fungi are in focus of the Fungal Genomic Program at the US Department of Energy Joint Genome Institute (JGI). Its key project, the Genomics Encyclopedia of Fungi, targets fungi related to plant health (symbionts, pathogens, and biocontrol agents) and biorefinery processes (cellulose degradation, sugar fermentation, industrial hosts), and explores fungal diversity by means of genome sequencing and analysis. Over 50 fungal genomes have been sequenced by JGI to date and released through MycoCosm (www.jgi.doe.gov/fungi), a fungal web-portal, which integrates sequence and functional data with genome analysis tools for user community. Sequence analysis supported by functionalmore » genomics leads to developing parts list for complex systems ranging from ecosystems of biofuel crops to biorefineries. Recent examples of such 'parts' suggested by comparative genomics and functional analysis in these areas are presented here« less

Genome of Drosophila suzukii, the Spotted Wing Drosophila

PubMed Central

Chiu, Joanna C.; Jiang, Xuanting; Zhao, Li; Hamm, Christopher A.; Cridland, Julie M.; Saelao, Perot; Hamby, Kelly A.; Lee, Ernest K.; Kwok, Rosanna S.; Zhang, Guojie; Zalom, Frank G.; Walton, Vaughn M.; Begun, David J.

2013-01-01

Drosophila suzukii Matsumura (spotted wing drosophila) has recently become a serious pest of a wide variety of fruit crops in the United States as well as in Europe, leading to substantial yearly crop losses. To enable basic and applied research of this important pest, we sequenced the D. suzukii genome to obtain a high-quality reference sequence. Here, we discuss the basic properties of the genome and transcriptome and describe patterns of genome evolution in D. suzukii and its close relatives. Our analyses and genome annotations are presented in a web portal, SpottedWingFlyBase, to facilitate public access. PMID:24142924

Rice-Map: a new-generation rice genome browser.

PubMed

Wang, Jun; Kong, Lei; Zhao, Shuqi; Zhang, He; Tang, Liang; Li, Zhe; Gu, Xiaocheng; Luo, Jingchu; Gao, Ge

2011-03-30

The concurrent release of rice genome sequences for two subspecies (Oryza sativa L. ssp. japonica and Oryza sativa L. ssp. indica) facilitates rice studies at the whole genome level. Since the advent of high-throughput analysis, huge amounts of functional genomics data have been delivered rapidly, making an integrated online genome browser indispensable for scientists to visualize and analyze these data. Based on next-generation web technologies and high-throughput experimental data, we have developed Rice-Map, a novel genome browser for researchers to navigate, analyze and annotate rice genome interactively. More than one hundred annotation tracks (81 for japonica and 82 for indica) have been compiled and loaded into Rice-Map. These pre-computed annotations cover gene models, transcript evidences, expression profiling, epigenetic modifications, inter-species and intra-species homologies, genetic markers and other genomic features. In addition to these pre-computed tracks, registered users can interactively add comments and research notes to Rice-Map as User-Defined Annotation entries. By smoothly scrolling, dragging and zooming, users can browse various genomic features simultaneously at multiple scales. On-the-fly analysis for selected entries could be performed through dedicated bioinformatic analysis platforms such as WebLab and Galaxy. Furthermore, a BioMart-powered data warehouse "Rice Mart" is offered for advanced users to fetch bulk datasets based on complex criteria. Rice-Map delivers abundant up-to-date japonica and indica annotations, providing a valuable resource for both computational and bench biologists. Rice-Map is publicly accessible at http://www.ricemap.org/, with all data available for free downloading.

Using GBrowse 2.0 to visualize and share next-generation sequence data

PubMed Central

2013-01-01

GBrowse is a mature web-based genome browser that is suitable for deployment on both public and private web sites. It supports most of genome browser features, including qualitative and quantitative (wiggle) tracks, track uploading, track sharing, interactive track configuration, semantic zooming and limited smooth track panning. As of version 2.0, GBrowse supports next-generation sequencing (NGS) data by providing for the direct display of SAM and BAM sequence alignment files. SAM/BAM tracks provide semantic zooming and support both local and remote data sources. This article provides step-by-step instructions for configuring GBrowse to display NGS data. PMID:23376193

A knowledge base for Vitis vinifera functional analysis.

PubMed

Pulvirenti, Alfredo; Giugno, Rosalba; Distefano, Rosario; Pigola, Giuseppe; Mongiovi, Misael; Giudice, Girolamo; Vendramin, Vera; Lombardo, Alessandro; Cattonaro, Federica; Ferro, Alfredo

2015-01-01

Vitis vinifera (Grapevine) is the most important fruit species in the modern world. Wine and table grapes sales contribute significantly to the economy of major wine producing countries. The most relevant goals in wine production concern quality and safety. In order to significantly improve the achievement of these objectives and to gain biological knowledge about cultivars, a genomic approach is the most reliable strategy. The recent grapevine genome sequencing offers the opportunity to study the potential roles of genes and microRNAs in fruit maturation and other physiological and pathological processes. Although several systems allowing the analysis of plant genomes have been reported, none of them has been designed specifically for the functional analysis of grapevine genomes of cultivars under environmental stress in connection with microRNA data. Here we introduce a novel knowledge base, called BIOWINE, designed for the functional analysis of Vitis vinifera genomes of cultivars present in Sicily. The system allows the analysis of RNA-seq experiments of two different cultivars, namely Nero d'Avola and Nerello Mascalese. Samples were taken under different climatic conditions of phenological phases, diseases, and geographic locations. The BIOWINE web interface is equipped with data analysis modules for grapevine genomes. In particular users may analyze the current genome assembly together with the RNA-seq data through a customized version of GBrowse. The web interface allows users to perform gene set enrichment by exploiting third-party databases. BIOWINE is a knowledge base implementing a set of bioinformatics tools for the analysis of grapevine genomes. The system aims to increase our understanding of the grapevine varieties and species of Sicilian products focusing on adaptability to different climatic conditions, phenological phases, diseases, and geographic locations.

GREAT: a web portal for Genome Regulatory Architecture Tools.

PubMed

Bouyioukos, Costas; Bucchini, François; Elati, Mohamed; Képès, François

2016-07-08

GREAT (Genome REgulatory Architecture Tools) is a novel web portal for tools designed to generate user-friendly and biologically useful analysis of genome architecture and regulation. The online tools of GREAT are freely accessible and compatible with essentially any operating system which runs a modern browser. GREAT is based on the analysis of genome layout -defined as the respective positioning of co-functional genes- and its relation with chromosome architecture and gene expression. GREAT tools allow users to systematically detect regular patterns along co-functional genomic features in an automatic way consisting of three individual steps and respective interactive visualizations. In addition to the complete analysis of regularities, GREAT tools enable the use of periodicity and position information for improving the prediction of transcription factor binding sites using a multi-view machine learning approach. The outcome of this integrative approach features a multivariate analysis of the interplay between the location of a gene and its regulatory sequence. GREAT results are plotted in web interactive graphs and are available for download either as individual plots, self-contained interactive pages or as machine readable tables for downstream analysis. The GREAT portal can be reached at the following URL https://absynth.issb.genopole.fr/GREAT and each individual GREAT tool is available for downloading. © The Author(s) 2016. Published by Oxford University Press on behalf of Nucleic Acids Research.

KONAGAbase: a genomic and transcriptomic database for the diamondback moth, Plutella xylostella.

PubMed

Jouraku, Akiya; Yamamoto, Kimiko; Kuwazaki, Seigo; Urio, Masahiro; Suetsugu, Yoshitaka; Narukawa, Junko; Miyamoto, Kazuhisa; Kurita, Kanako; Kanamori, Hiroyuki; Katayose, Yuichi; Matsumoto, Takashi; Noda, Hiroaki

2013-07-09

The diamondback moth (DBM), Plutella xylostella, is one of the most harmful insect pests for crucifer crops worldwide. DBM has rapidly evolved high resistance to most conventional insecticides such as pyrethroids, organophosphates, fipronil, spinosad, Bacillus thuringiensis, and diamides. Therefore, it is important to develop genomic and transcriptomic DBM resources for analysis of genes related to insecticide resistance, both to clarify the mechanism of resistance of DBM and to facilitate the development of insecticides with a novel mode of action for more effective and environmentally less harmful insecticide rotation. To contribute to this goal, we developed KONAGAbase, a genomic and transcriptomic database for DBM (KONAGA is the Japanese word for DBM). KONAGAbase provides (1) transcriptomic sequences of 37,340 ESTs/mRNAs and 147,370 RNA-seq contigs which were clustered and assembled into 84,570 unigenes (30,695 contigs, 50,548 pseudo singletons, and 3,327 singletons); and (2) genomic sequences of 88,530 WGS contigs with 246,244 degenerate contigs and 106,455 singletons from which 6,310 de novo identified repeat sequences and 34,890 predicted gene-coding sequences were extracted. The unigenes and predicted gene-coding sequences were clustered and 32,800 representative sequences were extracted as a comprehensive putative gene set. These sequences were annotated with BLAST descriptions, Gene Ontology (GO) terms, and Pfam descriptions, respectively. KONAGAbase contains rich graphical user interface (GUI)-based web interfaces for easy and efficient searching, browsing, and downloading sequences and annotation data. Five useful search interfaces consisting of BLAST search, keyword search, BLAST result-based search, GO tree-based search, and genome browser are provided. KONAGAbase is publicly available from our website (http://dbm.dna.affrc.go.jp/px/) through standard web browsers. KONAGAbase provides DBM comprehensive transcriptomic and draft genomic sequences with useful annotation information with easy-to-use web interfaces, which helps researchers to efficiently search for target sequences such as insect resistance-related genes. KONAGAbase will be continuously updated and additional genomic/transcriptomic resources and analysis tools will be provided for further efficient analysis of the mechanism of insecticide resistance and the development of effective insecticides with a novel mode of action for DBM.

PeanutDB: an integrated bioinformatics web portal for Arachis hypogaea transcriptomics

PubMed Central

2012-01-01

Background The peanut (Arachis hypogaea) is an important crop cultivated worldwide for oil production and food sources. Its complex genetic architecture (e.g., the large and tetraploid genome possibly due to unique cross of wild diploid relatives and subsequent chromosome duplication: 2n = 4x = 40, AABB, 2800 Mb) presents a major challenge for its genome sequencing and makes it a less-studied crop. Without a doubt, transcriptome sequencing is the most effective way to harness the genome structure and gene expression dynamics of this non-model species that has a limited genomic resource. Description With the development of next generation sequencing technologies such as 454 pyro-sequencing and Illumina sequencing by synthesis, the transcriptomics data of peanut is rapidly accumulated in both the public databases and private sectors. Integrating 187,636 Sanger reads (103,685,419 bases), 1,165,168 Roche 454 reads (333,862,593 bases) and 57,135,995 Illumina reads (4,073,740,115 bases), we generated the first release of our peanut transcriptome assembly that contains 32,619 contigs. We provided EC, KEGG and GO functional annotations to these contigs and detected SSRs, SNPs and other genetic polymorphisms for each contig. Based on both open-source and our in-house tools, PeanutDB presents many seamlessly integrated web interfaces that allow users to search, filter, navigate and visualize easily the whole transcript assembly, its annotations and detected polymorphisms and simple sequence repeats. For each contig, sequence alignment is presented in both bird’s-eye view and nucleotide level resolution, with colorfully highlighted regions of mismatches, indels and repeats that facilitate close examination of assembly quality, genetic polymorphisms, sequence repeats and/or sequencing errors. Conclusion As a public genomic database that integrates peanut transcriptome data from different sources, PeanutDB (http://bioinfolab.muohio.edu/txid3818v1) provides the Peanut research community with an easy-to-use web portal that will definitely facilitate genomics research and molecular breeding in this less-studied crop. PMID:22712730

AnnoLnc: a web server for systematically annotating novel human lncRNAs.

PubMed

Hou, Mei; Tang, Xing; Tian, Feng; Shi, Fangyuan; Liu, Fenglin; Gao, Ge

2016-11-16

Long noncoding RNAs (lncRNAs) have been shown to play essential roles in almost every important biological process through multiple mechanisms. Although the repertoire of human lncRNAs has rapidly expanded, their biological function and regulation remain largely elusive, calling for a systematic and integrative annotation tool. Here we present AnnoLnc ( http://annolnc.cbi.pku.edu.cn ), a one-stop portal for systematically annotating novel human lncRNAs. Based on more than 700 data sources and various tool chains, AnnoLnc enables a systematic annotation covering genomic location, secondary structure, expression patterns, transcriptional regulation, miRNA interaction, protein interaction, genetic association and evolution. An intuitive web interface is available for interactive analysis through both desktops and mobile devices, and programmers can further integrate AnnoLnc into their pipeline through standard JSON-based Web Service APIs. To the best of our knowledge, AnnoLnc is the only web server to provide on-the-fly and systematic annotation for newly identified human lncRNAs. Compared with similar tools, the annotation generated by AnnoLnc covers a much wider spectrum with intuitive visualization. Case studies demonstrate the power of AnnoLnc in not only rediscovering known functions of human lncRNAs but also inspiring novel hypotheses.

MIPS PlantsDB: a database framework for comparative plant genome research.

PubMed

Nussbaumer, Thomas; Martis, Mihaela M; Roessner, Stephan K; Pfeifer, Matthias; Bader, Kai C; Sharma, Sapna; Gundlach, Heidrun; Spannagl, Manuel

2013-01-01

The rapidly increasing amount of plant genome (sequence) data enables powerful comparative analyses and integrative approaches and also requires structured and comprehensive information resources. Databases are needed for both model and crop plant organisms and both intuitive search/browse views and comparative genomics tools should communicate the data to researchers and help them interpret it. MIPS PlantsDB (http://mips.helmholtz-muenchen.de/plant/genomes.jsp) was initially described in NAR in 2007 [Spannagl,M., Noubibou,O., Haase,D., Yang,L., Gundlach,H., Hindemitt, T., Klee,K., Haberer,G., Schoof,H. and Mayer,K.F. (2007) MIPSPlantsDB-plant database resource for integrative and comparative plant genome research. Nucleic Acids Res., 35, D834-D840] and was set up from the start to provide data and information resources for individual plant species as well as a framework for integrative and comparative plant genome research. PlantsDB comprises database instances for tomato, Medicago, Arabidopsis, Brachypodium, Sorghum, maize, rice, barley and wheat. Building up on that, state-of-the-art comparative genomics tools such as CrowsNest are integrated to visualize and investigate syntenic relationships between monocot genomes. Results from novel genome analysis strategies targeting the complex and repetitive genomes of triticeae species (wheat and barley) are provided and cross-linked with model species. The MIPS Repeat Element Database (mips-REdat) and Catalog (mips-REcat) as well as tight connections to other databases, e.g. via web services, are further important components of PlantsDB.

MIPS PlantsDB: a database framework for comparative plant genome research

PubMed Central

Nussbaumer, Thomas; Martis, Mihaela M.; Roessner, Stephan K.; Pfeifer, Matthias; Bader, Kai C.; Sharma, Sapna; Gundlach, Heidrun; Spannagl, Manuel

2013-01-01

The rapidly increasing amount of plant genome (sequence) data enables powerful comparative analyses and integrative approaches and also requires structured and comprehensive information resources. Databases are needed for both model and crop plant organisms and both intuitive search/browse views and comparative genomics tools should communicate the data to researchers and help them interpret it. MIPS PlantsDB (http://mips.helmholtz-muenchen.de/plant/genomes.jsp) was initially described in NAR in 2007 [Spannagl,M., Noubibou,O., Haase,D., Yang,L., Gundlach,H., Hindemitt, T., Klee,K., Haberer,G., Schoof,H. and Mayer,K.F. (2007) MIPSPlantsDB–plant database resource for integrative and comparative plant genome research. Nucleic Acids Res., 35, D834–D840] and was set up from the start to provide data and information resources for individual plant species as well as a framework for integrative and comparative plant genome research. PlantsDB comprises database instances for tomato, Medicago, Arabidopsis, Brachypodium, Sorghum, maize, rice, barley and wheat. Building up on that, state-of-the-art comparative genomics tools such as CrowsNest are integrated to visualize and investigate syntenic relationships between monocot genomes. Results from novel genome analysis strategies targeting the complex and repetitive genomes of triticeae species (wheat and barley) are provided and cross-linked with model species. The MIPS Repeat Element Database (mips-REdat) and Catalog (mips-REcat) as well as tight connections to other databases, e.g. via web services, are further important components of PlantsDB. PMID:23203886

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

w4CSeq: software and web application to analyze 4C-seq data.

PubMed

Cai, Mingyang; Gao, Fan; Lu, Wange; Wang, Kai

2016-11-01

Circularized Chromosome Conformation Capture followed by deep sequencing (4C-Seq) is a powerful technique to identify genome-wide partners interacting with a pre-specified genomic locus. Here, we present a computational and statistical approach to analyze 4C-Seq data generated from both enzyme digestion and sonication fragmentation-based methods. We implemented a command line software tool and a web interface called w4CSeq, which takes in the raw 4C sequencing data (FASTQ files) as input, performs automated statistical analysis and presents results in a user-friendly manner. Besides providing users with the list of candidate interacting sites/regions, w4CSeq generates figures showing genome-wide distribution of interacting regions, and sketches the enrichment of key features such as TSSs, TTSs, CpG sites and DNA replication timing around 4C sites. Users can establish their own web server by downloading source codes at https://github.com/WGLab/w4CSeq Additionally, a demo web server is available at http://w4cseq.wglab.org CONTACT: kaiwang@usc.edu or wangelu@usc.eduSupplementary information: Supplementary data are available at Bioinformatics online. © The Author 2016. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

Semantic Web repositories for genomics data using the eXframe platform.

PubMed

Merrill, Emily; Corlosquet, Stéphane; Ciccarese, Paolo; Clark, Tim; Das, Sudeshna

2014-01-01

With the advent of inexpensive assay technologies, there has been an unprecedented growth in genomics data as well as the number of databases in which it is stored. In these databases, sample annotation using ontologies and controlled vocabularies is becoming more common. However, the annotation is rarely available as Linked Data, in a machine-readable format, or for standardized queries using SPARQL. This makes large-scale reuse, or integration with other knowledge bases very difficult. To address this challenge, we have developed the second generation of our eXframe platform, a reusable framework for creating online repositories of genomics experiments. This second generation model now publishes Semantic Web data. To accomplish this, we created an experiment model that covers provenance, citations, external links, assays, biomaterials used in the experiment, and the data collected during the process. The elements of our model are mapped to classes and properties from various established biomedical ontologies. Resource Description Framework (RDF) data is automatically produced using these mappings and indexed in an RDF store with a built-in Sparql Protocol and RDF Query Language (SPARQL) endpoint. Using the open-source eXframe software, institutions and laboratories can create Semantic Web repositories of their experiments, integrate it with heterogeneous resources and make it interoperable with the vast Semantic Web of biomedical knowledge.

RRE: a tool for the extraction of non-coding regions surrounding annotated genes from genomic datasets.

PubMed

Lazzarato, F; Franceschinis, G; Botta, M; Cordero, F; Calogero, R A

2004-11-01

RRE allows the extraction of non-coding regions surrounding a coding sequence [i.e. gene upstream region, 5'-untranslated region (5'-UTR), introns, 3'-UTR, downstream region] from annotated genomic datasets available at NCBI. RRE parser and web-based interface are accessible at http://www.bioinformatica.unito.it/bioinformatics/rre/rre.html

MetaPhinder—Identifying Bacteriophage Sequences in Metagenomic Data Sets

PubMed Central

Villarroel, Julia; Lund, Ole; Voldby Larsen, Mette; Nielsen, Morten

2016-01-01

Bacteriophages are the most abundant biological entity on the planet, but at the same time do not account for much of the genetic material isolated from most environments due to their small genome sizes. They also show great genetic diversity and mosaic genomes making it challenging to analyze and understand them. Here we present MetaPhinder, a method to identify assembled genomic fragments (i.e.contigs) of phage origin in metagenomic data sets. The method is based on a comparison to a database of whole genome bacteriophage sequences, integrating hits to multiple genomes to accomodate for the mosaic genome structure of many bacteriophages. The method is demonstrated to out-perform both BLAST methods based on single hits and methods based on k-mer comparisons. MetaPhinder is available as a web service at the Center for Genomic Epidemiology https://cge.cbs.dtu.dk/services/MetaPhinder/, while the source code can be downloaded from https://bitbucket.org/genomicepidemiology/metaphinder or https://github.com/vanessajurtz/MetaPhinder. PMID:27684958

MetaPhinder-Identifying Bacteriophage Sequences in Metagenomic Data Sets.

PubMed

Jurtz, Vanessa Isabell; Villarroel, Julia; Lund, Ole; Voldby Larsen, Mette; Nielsen, Morten

Bacteriophages are the most abundant biological entity on the planet, but at the same time do not account for much of the genetic material isolated from most environments due to their small genome sizes. They also show great genetic diversity and mosaic genomes making it challenging to analyze and understand them. Here we present MetaPhinder, a method to identify assembled genomic fragments (i.e.contigs) of phage origin in metagenomic data sets. The method is based on a comparison to a database of whole genome bacteriophage sequences, integrating hits to multiple genomes to accomodate for the mosaic genome structure of many bacteriophages. The method is demonstrated to out-perform both BLAST methods based on single hits and methods based on k-mer comparisons. MetaPhinder is available as a web service at the Center for Genomic Epidemiology https://cge.cbs.dtu.dk/services/MetaPhinder/, while the source code can be downloaded from https://bitbucket.org/genomicepidemiology/metaphinder or https://github.com/vanessajurtz/MetaPhinder.

The Salmonella In Silico Typing Resource (SISTR): An Open Web-Accessible Tool for Rapidly Typing and Subtyping Draft Salmonella Genome Assemblies.

PubMed

Yoshida, Catherine E; Kruczkiewicz, Peter; Laing, Chad R; Lingohr, Erika J; Gannon, Victor P J; Nash, John H E; Taboada, Eduardo N

2016-01-01

For nearly 100 years serotyping has been the gold standard for the identification of Salmonella serovars. Despite the increasing adoption of DNA-based subtyping approaches, serotype information remains a cornerstone in food safety and public health activities aimed at reducing the burden of salmonellosis. At the same time, recent advances in whole-genome sequencing (WGS) promise to revolutionize our ability to perform advanced pathogen characterization in support of improved source attribution and outbreak analysis. We present the Salmonella In Silico Typing Resource (SISTR), a bioinformatics platform for rapidly performing simultaneous in silico analyses for several leading subtyping methods on draft Salmonella genome assemblies. In addition to performing serovar prediction by genoserotyping, this resource integrates sequence-based typing analyses for: Multi-Locus Sequence Typing (MLST), ribosomal MLST (rMLST), and core genome MLST (cgMLST). We show how phylogenetic context from cgMLST analysis can supplement the genoserotyping analysis and increase the accuracy of in silico serovar prediction to over 94.6% on a dataset comprised of 4,188 finished genomes and WGS draft assemblies. In addition to allowing analysis of user-uploaded whole-genome assemblies, the SISTR platform incorporates a database comprising over 4,000 publicly available genomes, allowing users to place their isolates in a broader phylogenetic and epidemiological context. The resource incorporates several metadata driven visualizations to examine the phylogenetic, geospatial and temporal distribution of genome-sequenced isolates. As sequencing of Salmonella isolates at public health laboratories around the world becomes increasingly common, rapid in silico analysis of minimally processed draft genome assemblies provides a powerful approach for molecular epidemiology in support of public health investigations. Moreover, this type of integrated analysis using multiple sequence-based methods of sub-typing allows for continuity with historical serotyping data as we transition towards the increasing adoption of genomic analyses in epidemiology. The SISTR platform is freely available on the web at https://lfz.corefacility.ca/sistr-app/.

International Cancer Genome Consortium Data Portal--a one-stop shop for cancer genomics data.

PubMed

Zhang, Junjun; Baran, Joachim; Cros, A; Guberman, Jonathan M; Haider, Syed; Hsu, Jack; Liang, Yong; Rivkin, Elena; Wang, Jianxin; Whitty, Brett; Wong-Erasmus, Marie; Yao, Long; Kasprzyk, Arek

2011-01-01

The International Cancer Genome Consortium (ICGC) is a collaborative effort to characterize genomic abnormalities in 50 different cancer types. To make this data available, the ICGC has created the ICGC Data Portal. Powered by the BioMart software, the Data Portal allows each ICGC member institution to manage and maintain its own databases locally, while seamlessly presenting all the data in a single access point for users. The Data Portal currently contains data from 24 cancer projects, including ICGC, The Cancer Genome Atlas (TCGA), Johns Hopkins University, and the Tumor Sequencing Project. It consists of 3478 genomes and 13 cancer types and subtypes. Available open access data types include simple somatic mutations, copy number alterations, structural rearrangements, gene expression, microRNAs, DNA methylation and exon junctions. Additionally, simple germline variations are available as controlled access data. The Data Portal uses a web-based graphical user interface (GUI) to offer researchers multiple ways to quickly and easily search and analyze the available data. The web interface can assist in constructing complicated queries across multiple data sets. Several application programming interfaces are also available for programmatic access. Here we describe the organization, functionality, and capabilities of the ICGC Data Portal.

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.

Genomic Encyclopedia of Fungi

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

Grigoriev, Igor

Genomes of fungi relevant to energy and environment are in focus of the Fungal Genomic Program at the US Department of Energy Joint Genome Institute (JGI). Its key project, the Genomics Encyclopedia of Fungi, targets fungi related to plant health (symbionts, pathogens, and biocontrol agents) and biorefinery processes (cellulose degradation, sugar fermentation, industrial hosts), and explores fungal diversity by means of genome sequencing and analysis. Over 150 fungal genomes have been sequenced by JGI to date and released through MycoCosm (www.jgi.doe.gov/fungi), a fungal web-portal, which integrates sequence and functional data with genome analysis tools for user community. Sequence analysis supportedmore » by functional genomics leads to developing parts list for complex systems ranging from ecosystems of biofuel crops to biorefineries. Recent examples of such parts suggested by comparative genomics and functional analysis in these areas are presented here.« less

Likelihood-based gene annotations for gap filling and quality assessment in genome-scale metabolic models

DOE PAGES

Benedict, Matthew N.; Mundy, Michael B.; Henry, Christopher S.; ...

2014-10-16

Genome-scale metabolic models provide a powerful means to harness information from genomes to deepen biological insights. With exponentially increasing sequencing capacity, there is an enormous need for automated reconstruction techniques that can provide more accurate models in a short time frame. Current methods for automated metabolic network reconstruction rely on gene and reaction annotations to build draft metabolic networks and algorithms to fill gaps in these networks. However, automated reconstruction is hampered by database inconsistencies, incorrect annotations, and gap filling largely without considering genomic information. Here we develop an approach for applying genomic information to predict alternative functions for genesmore » and estimate their likelihoods from sequence homology. We show that computed likelihood values were significantly higher for annotations found in manually curated metabolic networks than those that were not. We then apply these alternative functional predictions to estimate reaction likelihoods, which are used in a new gap filling approach called likelihood-based gap filling to predict more genomically consistent solutions. To validate the likelihood-based gap filling approach, we applied it to models where essential pathways were removed, finding that likelihood-based gap filling identified more biologically relevant solutions than parsimony-based gap filling approaches. We also demonstrate that models gap filled using likelihood-based gap filling provide greater coverage and genomic consistency with metabolic gene functions compared to parsimony-based approaches. Interestingly, despite these findings, we found that likelihoods did not significantly affect consistency of gap filled models with Biolog and knockout lethality data. This indicates that the phenotype data alone cannot necessarily be used to discriminate between alternative solutions for gap filling and therefore, that the use of other information is necessary to obtain a more accurate network. All described workflows are implemented as part of the DOE Systems Biology Knowledgebase (KBase) and are publicly available via API or command-line web interface.« less

Likelihood-Based Gene Annotations for Gap Filling and Quality Assessment in Genome-Scale Metabolic Models

PubMed Central

Benedict, Matthew N.; Mundy, Michael B.; Henry, Christopher S.; Chia, Nicholas; Price, Nathan D.

2014-01-01

Genome-scale metabolic models provide a powerful means to harness information from genomes to deepen biological insights. With exponentially increasing sequencing capacity, there is an enormous need for automated reconstruction techniques that can provide more accurate models in a short time frame. Current methods for automated metabolic network reconstruction rely on gene and reaction annotations to build draft metabolic networks and algorithms to fill gaps in these networks. However, automated reconstruction is hampered by database inconsistencies, incorrect annotations, and gap filling largely without considering genomic information. Here we develop an approach for applying genomic information to predict alternative functions for genes and estimate their likelihoods from sequence homology. We show that computed likelihood values were significantly higher for annotations found in manually curated metabolic networks than those that were not. We then apply these alternative functional predictions to estimate reaction likelihoods, which are used in a new gap filling approach called likelihood-based gap filling to predict more genomically consistent solutions. To validate the likelihood-based gap filling approach, we applied it to models where essential pathways were removed, finding that likelihood-based gap filling identified more biologically relevant solutions than parsimony-based gap filling approaches. We also demonstrate that models gap filled using likelihood-based gap filling provide greater coverage and genomic consistency with metabolic gene functions compared to parsimony-based approaches. Interestingly, despite these findings, we found that likelihoods did not significantly affect consistency of gap filled models with Biolog and knockout lethality data. This indicates that the phenotype data alone cannot necessarily be used to discriminate between alternative solutions for gap filling and therefore, that the use of other information is necessary to obtain a more accurate network. All described workflows are implemented as part of the DOE Systems Biology Knowledgebase (KBase) and are publicly available via API or command-line web interface. PMID:25329157

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.

PLAZA 3.0: an access point for plant comparative genomics.

PubMed

Proost, Sebastian; Van Bel, Michiel; Vaneechoutte, Dries; Van de Peer, Yves; Inzé, Dirk; Mueller-Roeber, Bernd; Vandepoele, Klaas

2015-01-01

Comparative sequence analysis has significantly altered our view on the complexity of genome organization and gene functions in different kingdoms. PLAZA 3.0 is designed to make comparative genomics data for plants available through a user-friendly web interface. Structural and functional annotation, gene families, protein domains, phylogenetic trees and detailed information about genome organization can easily be queried and visualized. Compared with the first version released in 2009, which featured nine organisms, the number of integrated genomes is more than four times higher, and now covers 37 plant species. The new species provide a wider phylogenetic range as well as a more in-depth sampling of specific clades, and genomes of additional crop species are present. The functional annotation has been expanded and now comprises data from Gene Ontology, MapMan, UniProtKB/Swiss-Prot, PlnTFDB and PlantTFDB. Furthermore, we improved the algorithms to transfer functional annotation from well-characterized plant genomes to other species. The additional data and new features make PLAZA 3.0 (http://bioinformatics.psb.ugent.be/plaza/) a versatile and comprehensible resource for users wanting to explore genome information to study different aspects of plant biology, both in model and non-model organisms. © The Author(s) 2014. Published by Oxford University Press on behalf of Nucleic Acids Research.

Comprehensive Genome-Wide Classification Reveals That Many Plant-Specific Transcription Factors Evolved in Streptophyte Algae

PubMed Central

Wilhelmsson, Per K I; Mühlich, Cornelia; Ullrich, Kristian K

2017-01-01

Abstract Plant genomes encode many lineage-specific, unique transcription factors. Expansion of such gene families has been previously found to coincide with the evolution of morphological complexity, although comparative analyses have been hampered by severe sampling bias. Here, we make use of the recently increased availability of plant genomes. We have updated and expanded previous rule sets for domain-based classification of transcription associated proteins (TAPs), comprising transcription factors and transcriptional regulators. The genome-wide annotation of these protein families has been analyzed and made available via the novel TAPscan web interface. We find that many TAP families previously thought to be specific for land plants actually evolved in streptophyte (charophyte) algae; 26 out of 36 TAP family gains are inferred to have occurred in the common ancestor of the Streptophyta (uniting the land plants—Embryophyta—with their closest algal relatives). In contrast, expansions of TAP families were found to occur throughout streptophyte evolution. 17 out of 76 expansion events were found to be common to all land plants and thus probably evolved concomitant with the water-to-land-transition. PMID:29216360

CNV Workshop: an integrated platform for high-throughput copy number variation discovery and clinical diagnostics.

PubMed

Gai, Xiaowu; Perin, Juan C; Murphy, Kevin; O'Hara, Ryan; D'arcy, Monica; Wenocur, Adam; Xie, Hongbo M; Rappaport, Eric F; Shaikh, Tamim H; White, Peter S

2010-02-04

Recent studies have shown that copy number variations (CNVs) are frequent in higher eukaryotes and associated with a substantial portion of inherited and acquired risk for various human diseases. The increasing availability of high-resolution genome surveillance platforms provides opportunity for rapidly assessing research and clinical samples for CNV content, as well as for determining the potential pathogenicity of identified variants. However, few informatics tools for accurate and efficient CNV detection and assessment currently exist. We developed a suite of software tools and resources (CNV Workshop) for automated, genome-wide CNV detection from a variety of SNP array platforms. CNV Workshop includes three major components: detection, annotation, and presentation of structural variants from genome array data. CNV detection utilizes a robust and genotype-specific extension of the Circular Binary Segmentation algorithm, and the use of additional detection algorithms is supported. Predicted CNVs are captured in a MySQL database that supports cohort-based projects and incorporates a secure user authentication layer and user/admin roles. To assist with determination of pathogenicity, detected CNVs are also annotated automatically for gene content, known disease loci, and gene-based literature references. Results are easily queried, sorted, filtered, and visualized via a web-based presentation layer that includes a GBrowse-based graphical representation of CNV content and relevant public data, integration with the UCSC Genome Browser, and tabular displays of genomic attributes for each CNV. To our knowledge, CNV Workshop represents the first cohesive and convenient platform for detection, annotation, and assessment of the biological and clinical significance of structural variants. CNV Workshop has been successfully utilized for assessment of genomic variation in healthy individuals and disease cohorts and is an ideal platform for coordinating multiple associated projects. Available on the web at: http://sourceforge.net/projects/cnv.

Integrating genomics into undergraduate nursing education.

PubMed

Daack-Hirsch, Sandra; Dieter, Carla; Quinn Griffin, Mary T

2011-09-01

To prepare the next generation of nurses, faculty are now faced with the challenge of incorporating genomics into curricula. Here we discuss how to meet this challenge. Steps to initiate curricular changes to include genomics are presented along with a discussion on creating a genomic curriculum thread versus a standalone course. Ideas for use of print material and technology on genomic topics are also presented. Information is based on review of the literature and curriculum change efforts by the authors. In recognition of advances in genomics, the nursing profession is increasing an emphasis on the integration of genomics into professional practice and educational standards. Incorporating genomics into nurses' practices begins with changes in our undergraduate curricula. Information given in didactic courses should be reinforced in clinical practica, and Internet-based tools such as WebQuest, Second Life, and wikis offer attractive, up-to-date platforms to deliver this now crucial content. To provide information that may assist faculty to prepare the next generation of nurses to practice using genomics. © 2011 Sigma Theta Tau International.

ProbFAST: Probabilistic functional analysis system tool.

PubMed

Silva, Israel T; Vêncio, Ricardo Z N; Oliveira, Thiago Y K; Molfetta, Greice A; Silva, Wilson A

2010-03-30

The post-genomic era has brought new challenges regarding the understanding of the organization and function of the human genome. Many of these challenges are centered on the meaning of differential gene regulation under distinct biological conditions and can be performed by analyzing the Multiple Differential Expression (MDE) of genes associated with normal and abnormal biological processes. Currently MDE analyses are limited to usual methods of differential expression initially designed for paired analysis. We proposed a web platform named ProbFAST for MDE analysis which uses Bayesian inference to identify key genes that are intuitively prioritized by means of probabilities. A simulated study revealed that our method gives a better performance when compared to other approaches and when applied to public expression data, we demonstrated its flexibility to obtain relevant genes biologically associated with normal and abnormal biological processes. ProbFAST is a free accessible web-based application that enables MDE analysis on a global scale. It offers an efficient methodological approach for MDE analysis of a set of genes that are turned on and off related to functional information during the evolution of a tumor or tissue differentiation. ProbFAST server can be accessed at http://gdm.fmrp.usp.br/probfast.

ProbFAST: Probabilistic Functional Analysis System Tool

PubMed Central

2010-01-01

Background The post-genomic era has brought new challenges regarding the understanding of the organization and function of the human genome. Many of these challenges are centered on the meaning of differential gene regulation under distinct biological conditions and can be performed by analyzing the Multiple Differential Expression (MDE) of genes associated with normal and abnormal biological processes. Currently MDE analyses are limited to usual methods of differential expression initially designed for paired analysis. Results We proposed a web platform named ProbFAST for MDE analysis which uses Bayesian inference to identify key genes that are intuitively prioritized by means of probabilities. A simulated study revealed that our method gives a better performance when compared to other approaches and when applied to public expression data, we demonstrated its flexibility to obtain relevant genes biologically associated with normal and abnormal biological processes. Conclusions ProbFAST is a free accessible web-based application that enables MDE analysis on a global scale. It offers an efficient methodological approach for MDE analysis of a set of genes that are turned on and off related to functional information during the evolution of a tumor or tissue differentiation. ProbFAST server can be accessed at http://gdm.fmrp.usp.br/probfast. PMID:20353576

VISA--Vector Integration Site Analysis server: a web-based server to rapidly identify retroviral integration sites from next-generation sequencing.

PubMed

Hocum, Jonah D; Battrell, Logan R; Maynard, Ryan; Adair, Jennifer E; Beard, Brian C; Rawlings, David J; Kiem, Hans-Peter; Miller, Daniel G; Trobridge, Grant D

2015-07-07

Analyzing the integration profile of retroviral vectors is a vital step in determining their potential genotoxic effects and developing safer vectors for therapeutic use. Identifying retroviral vector integration sites is also important for retroviral mutagenesis screens. We developed VISA, a vector integration site analysis server, to analyze next-generation sequencing data for retroviral vector integration sites. Sequence reads that contain a provirus are mapped to the human genome, sequence reads that cannot be localized to a unique location in the genome are filtered out, and then unique retroviral vector integration sites are determined based on the alignment scores of the remaining sequence reads. VISA offers a simple web interface to upload sequence files and results are returned in a concise tabular format to allow rapid analysis of retroviral vector integration sites.

Virus-Clip: a fast and memory-efficient viral integration site detection tool at single-base resolution with annotation capability.

PubMed

Ho, Daniel W H; Sze, Karen M F; Ng, Irene O L

2015-08-28

Viral integration into the human genome upon infection is an important risk factor for various human malignancies. We developed viral integration site detection tool called Virus-Clip, which makes use of information extracted from soft-clipped sequencing reads to identify exact positions of human and virus breakpoints of integration events. With initial read alignment to virus reference genome and streamlined procedures, Virus-Clip delivers a simple, fast and memory-efficient solution to viral integration site detection. Moreover, it can also automatically annotate the integration events with the corresponding affected human genes. Virus-Clip has been verified using whole-transcriptome sequencing data and its detection was validated to have satisfactory sensitivity and specificity. Marked advancement in performance was detected, compared to existing tools. It is applicable to versatile types of data including whole-genome sequencing, whole-transcriptome sequencing, and targeted sequencing. Virus-Clip is available at http://web.hku.hk/~dwhho/Virus-Clip.zip.

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

BISQUE: locus- and variant-specific conversion of genomic, transcriptomic and proteomic database identifiers.

PubMed

Meyer, Michael J; Geske, Philip; Yu, Haiyuan

2016-05-15

Biological sequence databases are integral to efforts to characterize and understand biological molecules and share biological data. However, when analyzing these data, scientists are often left holding disparate biological currency-molecular identifiers from different databases. For downstream applications that require converting the identifiers themselves, there are many resources available, but analyzing associated loci and variants can be cumbersome if data is not given in a form amenable to particular analyses. Here we present BISQUE, a web server and customizable command-line tool for converting molecular identifiers and their contained loci and variants between different database conventions. BISQUE uses a graph traversal algorithm to generalize the conversion process for residues in the human genome, genes, transcripts and proteins, allowing for conversion across classes of molecules and in all directions through an intuitive web interface and a URL-based web service. BISQUE is freely available via the web using any major web browser (http://bisque.yulab.org/). Source code is available in a public GitHub repository (https://github.com/hyulab/BISQUE). haiyuan.yu@cornell.edu 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.

Reverse vaccinology as an approach for developing Histophilus somni vaccine candidates.

PubMed

Madampage, Claudia Avis; Rawlyk, Neil; Crockford, Gordon; Wang, Yejun; White, Aaron P; Brownlie, Robert; Van Donkersgoed, Joyce; Dorin, Craig; Potter, Andrew

2015-11-01

Histophilosis of cattle is caused by the Gram negative bacterial pathogen Histophilus somni (H. somni) which is also associated with the bovine respiratory disease (BRD) complex. Existing vaccines for H. somni include either killed cells or bacteria-free outer membrane proteins from the organism which have proven to be moderately successful. In this study, reverse vaccinology was used to predict potential H. somni vaccine candidates from genome sequences. In turn, these may protect animals against new strains circulating in the field. Whole genome sequencing of six recent clinical H. somni isolates was performed using an Illumina MiSeq and compared to six genomes from the 1980's. De novo assembly of crude whole genomes was completed using Geneious 6.1.7. Protein coding regions was predicted using Glimmer3. Scores from multiple web-based programs were utilized to evaluate the antigenicity of these predicted proteins which were finally ranked based on their surface exposure scores. A single new strain was selected for future vaccine development based on conservation of the protein candidates among all 12 isolates. A positive signal with convalescent serum for these antigens in western blots indicates in vivo recognition. In order to test the protective capacity of these antigens bovine animal trials are ongoing. Copyright © 2015 The International Alliance for Biological Standardization. Published by Elsevier Ltd. All rights reserved.

Brassica ASTRA: an integrated database for Brassica genomic research.

PubMed

Love, Christopher G; Robinson, Andrew J; Lim, Geraldine A C; Hopkins, Clare J; Batley, Jacqueline; Barker, Gary; Spangenberg, German C; Edwards, David

2005-01-01

Brassica ASTRA is a public database for genomic information on Brassica species. The database incorporates expressed sequences with Swiss-Prot and GenBank comparative sequence annotation as well as secondary Gene Ontology (GO) annotation derived from the comparison with Arabidopsis TAIR GO annotations. Simple sequence repeat molecular markers are identified within resident sequences and mapped onto the closely related Arabidopsis genome sequence. Bacterial artificial chromosome (BAC) end sequences derived from the Multinational Brassica Genome Project are also mapped onto the Arabidopsis genome sequence enabling users to identify candidate Brassica BACs corresponding to syntenic regions of Arabidopsis. This information is maintained in a MySQL database with a web interface providing the primary means of interrogation. The database is accessible at http://hornbill.cspp.latrobe.edu.au.

The BioExtract Server: a web-based bioinformatic workflow platform

PubMed Central

Lushbough, Carol M.; Jennewein, Douglas M.; Brendel, Volker P.

2011-01-01

The BioExtract Server (bioextract.org) is an open, web-based system designed to aid researchers in the analysis of genomic data by providing a platform for the creation of bioinformatic workflows. Scientific workflows are created within the system by recording tasks performed by the user. These tasks may include querying multiple, distributed data sources, saving query results as searchable data extracts, and executing local and web-accessible analytic tools. The series of recorded tasks can then be saved as a reproducible, sharable workflow available for subsequent execution with the original or modified inputs and parameter settings. Integrated data resources include interfaces to the National Center for Biotechnology Information (NCBI) nucleotide and protein databases, the European Molecular Biology Laboratory (EMBL-Bank) non-redundant nucleotide database, the Universal Protein Resource (UniProt), and the UniProt Reference Clusters (UniRef) database. The system offers access to numerous preinstalled, curated analytic tools and also provides researchers with the option of selecting computational tools from a large list of web services including the European Molecular Biology Open Software Suite (EMBOSS), BioMoby, and the Kyoto Encyclopedia of Genes and Genomes (KEGG). The system further allows users to integrate local command line tools residing on their own computers through a client-side Java applet. PMID:21546552

Phylogenomics, Diversification Dynamics, and Comparative Transcriptomics across the Spider Tree of Life.

PubMed

Fernández, Rosa; Kallal, Robert J; Dimitrov, Dimitar; Ballesteros, Jesús A; Arnedo, Miquel A; Giribet, Gonzalo; Hormiga, Gustavo

2018-05-07

Dating back to almost 400 mya, spiders are among the most diverse terrestrial predators [1]. However, despite considerable effort [1-9], their phylogenetic relationships and diversification dynamics remain poorly understood. Here, we use a synergistic approach to study spider evolution through phylogenomics, comparative transcriptomics, and lineage diversification analyses. Our analyses, based on ca. 2,500 genes from 159 spider species, reject a single origin of the orb web (the "ancient orb-web hypothesis") and suggest that orb webs evolved multiple times since the late Triassic-Jurassic. We find no significant association between the loss of foraging webs and increases in diversification rates, suggesting that other factors (e.g., habitat heterogeneity or biotic interactions) potentially played a key role in spider diversification. Finally, we report notable genomic differences in the main spider lineages: while araneoids (ecribellate orb-weavers and their allies) reveal an enrichment in genes related to behavior and sensory reception, the retrolateral tibial apophysis (RTA) clade-the most diverse araneomorph spider lineage-shows enrichment in genes related to immune responses and polyphenic determination. This study, one of the largest invertebrate phylogenomic analyses to date, highlights the usefulness of transcriptomic data not only to build a robust backbone for the Spider Tree of Life, but also to address the genetic basis of diversification in the spider evolutionary chronicle. Copyright © 2018 Elsevier Ltd. All rights reserved.

PlantRGDB: A Database of Plant Retrocopied Genes.

PubMed

Wang, Yi

2017-01-01

RNA-based gene duplication, known as retrocopy, plays important roles in gene origination and genome evolution. The genomes of many plants have been sequenced, offering an opportunity to annotate and mine the retrocopies in plant genomes. However, comprehensive and unified annotation of retrocopies in these plants is still lacking. In this study I constructed the PlantRGDB (Plant Retrocopied Gene DataBase), the first database of plant retrocopies, to provide a putatively complete centralized list of retrocopies in plant genomes. The database is freely accessible at http://probes.pw.usda.gov/plantrgdb or http://aegilops.wheat.ucdavis.edu/plantrgdb. It currently integrates 49 plant species and 38,997 retrocopies along with characterization information. PlantRGDB provides a user-friendly web interface for searching, browsing and downloading the retrocopies in the database. PlantRGDB also offers graphical viewer-integrated sequence information for displaying the structure of each retrocopy. The attributes of the retrocopies of each species are reported using a browse function. In addition, useful tools, such as an advanced search and BLAST, are available to search the database more conveniently. In conclusion, the database will provide a web platform for obtaining valuable insight into the generation of retrocopies and will supplement research on gene duplication and genome evolution in plants. © The Author 2017. Published by Oxford University Press on behalf of Japanese Society of Plant Physiologists. All rights reserved. For permissions, please email: journals.permissions@oup.com.

GREAM: A Web Server to Short-List Potentially Important Genomic Repeat Elements Based on Over-/Under-Representation in Specific Chromosomal Locations, Such as the Gene Neighborhoods, within or across 17 Mammalian Species

PubMed Central

Chandrashekar, Darshan Shimoga; Dey, Poulami; Acharya, Kshitish K.

2015-01-01

Background Genome-wide repeat sequences, such as LINEs, SINEs and LTRs share a considerable part of the mammalian nuclear genomes. These repeat elements seem to be important for multiple functions including the regulation of transcription initiation, alternative splicing and DNA methylation. But it is not possible to study all repeats and, hence, it would help to short-list before exploring their potential functional significance via experimental studies and/or detailed in silico analyses. Result We developed the ‘Genomic Repeat Element Analyzer for Mammals’ (GREAM) for analysis, screening and selection of potentially important mammalian genomic repeats. This web-server offers many novel utilities. For example, this is the only tool that can reveal a categorized list of specific types of transposons, retro-transposons and other genome-wide repetitive elements that are statistically over-/under-represented in regions around a set of genes, such as those expressed differentially in a disease condition. The output displays the position and frequency of identified elements within the specified regions. In addition, GREAM offers two other types of analyses of genomic repeat sequences: a) enrichment within chromosomal region(s) of interest, and b) comparative distribution across the neighborhood of orthologous genes. GREAM successfully short-listed a repeat element (MER20) known to contain functional motifs. In other case studies, we could use GREAM to short-list repetitive elements in the azoospermia factor a (AZFa) region of the human Y chromosome and those around the genes associated with rat liver injury. GREAM could also identify five over-represented repeats around some of the human and mouse transcription factor coding genes that had conserved expression patterns across the two species. Conclusion GREAM has been developed to provide an impetus to research on the role of repetitive sequences in mammalian genomes by offering easy selection of more interesting repeats in various contexts/regions. GREAM is freely available at http://resource.ibab.ac.in/GREAM/. PMID:26208093

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 Genomic HyperBrowser: an analysis web server for genome-scale data

PubMed Central

Sandve, Geir K.; Gundersen, Sveinung; Johansen, Morten; Glad, Ingrid K.; Gunathasan, Krishanthi; Holden, Lars; Holden, Marit; Liestøl, Knut; Nygård, Ståle; Nygaard, Vegard; Paulsen, Jonas; Rydbeck, Halfdan; Trengereid, Kai; Clancy, Trevor; Drabløs, Finn; Ferkingstad, Egil; Kalaš, Matúš; Lien, Tonje; Rye, Morten B.; Frigessi, Arnoldo; Hovig, Eivind

2013-01-01

The immense increase in availability of genomic scale datasets, such as those provided by the ENCODE and Roadmap Epigenomics projects, presents unprecedented opportunities for individual researchers to pose novel falsifiable biological questions. With this opportunity, however, researchers are faced with the challenge of how to best analyze and interpret their genome-scale datasets. A powerful way of representing genome-scale data is as feature-specific coordinates relative to reference genome assemblies, i.e. as genomic tracks. The Genomic HyperBrowser (http://hyperbrowser.uio.no) is an open-ended web server for the analysis of genomic track data. Through the provision of several highly customizable components for processing and statistical analysis of genomic tracks, the HyperBrowser opens for a range of genomic investigations, related to, e.g., gene regulation, disease association or epigenetic modifications of the genome. PMID:23632163

The Genomic HyperBrowser: an analysis web server for genome-scale data.

PubMed

Sandve, Geir K; Gundersen, Sveinung; Johansen, Morten; Glad, Ingrid K; Gunathasan, Krishanthi; Holden, Lars; Holden, Marit; Liestøl, Knut; Nygård, Ståle; Nygaard, Vegard; Paulsen, Jonas; Rydbeck, Halfdan; Trengereid, Kai; Clancy, Trevor; Drabløs, Finn; Ferkingstad, Egil; Kalas, Matús; Lien, Tonje; Rye, Morten B; Frigessi, Arnoldo; Hovig, Eivind

2013-07-01

The immense increase in availability of genomic scale datasets, such as those provided by the ENCODE and Roadmap Epigenomics projects, presents unprecedented opportunities for individual researchers to pose novel falsifiable biological questions. With this opportunity, however, researchers are faced with the challenge of how to best analyze and interpret their genome-scale datasets. A powerful way of representing genome-scale data is as feature-specific coordinates relative to reference genome assemblies, i.e. as genomic tracks. The Genomic HyperBrowser (http://hyperbrowser.uio.no) is an open-ended web server for the analysis of genomic track data. Through the provision of several highly customizable components for processing and statistical analysis of genomic tracks, the HyperBrowser opens for a range of genomic investigations, related to, e.g., gene regulation, disease association or epigenetic modifications of the genome.

ZCURVE 3.0: identify prokaryotic genes with higher accuracy as well as automatically and accurately select essential genes

PubMed Central

Hua, Zhi-Gang; Lin, Yan; Yuan, Ya-Zhou; Yang, De-Chang; Wei, Wen; Guo, Feng-Biao

2015-01-01

In 2003, we developed an ab initio program, ZCURVE 1.0, to find genes in bacterial and archaeal genomes. In this work, we present the updated version (i.e. ZCURVE 3.0). Using 422 prokaryotic genomes, the average accuracy was 93.7% with the updated version, compared with 88.7% with the original version. Such results also demonstrate that ZCURVE 3.0 is comparable with Glimmer 3.02 and may provide complementary predictions to it. In fact, the joint application of the two programs generated better results by correctly finding more annotated genes while also containing fewer false-positive predictions. As the exclusive function, ZCURVE 3.0 contains one post-processing program that can identify essential genes with high accuracy (generally >90%). We hope ZCURVE 3.0 will receive wide use with the web-based running mode. The updated ZCURVE can be freely accessed from http://cefg.uestc.edu.cn/zcurve/ or http://tubic.tju.edu.cn/zcurveb/ without any restrictions. PMID:25977299

Fast and sensitive taxonomic classification for metagenomics with Kaiju

PubMed Central

Menzel, Peter; Ng, Kim Lee; Krogh, Anders

2016-01-01

Metagenomics emerged as an important field of research not only in microbial ecology but also for human health and disease, and metagenomic studies are performed on increasingly larger scales. While recent taxonomic classification programs achieve high speed by comparing genomic k-mers, they often lack sensitivity for overcoming evolutionary divergence, so that large fractions of the metagenomic reads remain unclassified. Here we present the novel metagenome classifier Kaiju, which finds maximum (in-)exact matches on the protein-level using the Burrows–Wheeler transform. We show in a genome exclusion benchmark that Kaiju classifies reads with higher sensitivity and similar precision compared with current k-mer-based classifiers, especially in genera that are underrepresented in reference databases. We also demonstrate that Kaiju classifies up to 10 times more reads in real metagenomes. Kaiju can process millions of reads per minute and can run on a standard PC. Source code and web server are available at http://kaiju.binf.ku.dk. PMID:27071849

Fast and sensitive taxonomic classification for metagenomics with Kaiju.

PubMed

Menzel, Peter; Ng, Kim Lee; Krogh, Anders

2016-04-13

Metagenomics emerged as an important field of research not only in microbial ecology but also for human health and disease, and metagenomic studies are performed on increasingly larger scales. While recent taxonomic classification programs achieve high speed by comparing genomic k-mers, they often lack sensitivity for overcoming evolutionary divergence, so that large fractions of the metagenomic reads remain unclassified. Here we present the novel metagenome classifier Kaiju, which finds maximum (in-)exact matches on the protein-level using the Burrows-Wheeler transform. We show in a genome exclusion benchmark that Kaiju classifies reads with higher sensitivity and similar precision compared with current k-mer-based classifiers, especially in genera that are underrepresented in reference databases. We also demonstrate that Kaiju classifies up to 10 times more reads in real metagenomes. Kaiju can process millions of reads per minute and can run on a standard PC. Source code and web server are available at http://kaiju.binf.ku.dk.

Semantic Web repositories for genomics data using the eXframe platform

PubMed Central

2014-01-01

Background With the advent of inexpensive assay technologies, there has been an unprecedented growth in genomics data as well as the number of databases in which it is stored. In these databases, sample annotation using ontologies and controlled vocabularies is becoming more common. However, the annotation is rarely available as Linked Data, in a machine-readable format, or for standardized queries using SPARQL. This makes large-scale reuse, or integration with other knowledge bases very difficult. Methods To address this challenge, we have developed the second generation of our eXframe platform, a reusable framework for creating online repositories of genomics experiments. This second generation model now publishes Semantic Web data. To accomplish this, we created an experiment model that covers provenance, citations, external links, assays, biomaterials used in the experiment, and the data collected during the process. The elements of our model are mapped to classes and properties from various established biomedical ontologies. Resource Description Framework (RDF) data is automatically produced using these mappings and indexed in an RDF store with a built-in Sparql Protocol and RDF Query Language (SPARQL) endpoint. Conclusions Using the open-source eXframe software, institutions and laboratories can create Semantic Web repositories of their experiments, integrate it with heterogeneous resources and make it interoperable with the vast Semantic Web of biomedical knowledge. PMID:25093072

Ontologies as integrative tools for plant science

PubMed Central

Walls, Ramona L.; Athreya, Balaji; Cooper, Laurel; Elser, Justin; Gandolfo, Maria A.; Jaiswal, Pankaj; Mungall, Christopher J.; Preece, Justin; Rensing, Stefan; Smith, Barry; Stevenson, Dennis W.

2012-01-01

Premise of the study Bio-ontologies are essential tools for accessing and analyzing the rapidly growing pool of plant genomic and phenomic data. Ontologies provide structured vocabularies to support consistent aggregation of data and a semantic framework for automated analyses and reasoning. They are a key component of the semantic web. Methods This paper provides background on what bio-ontologies are, why they are relevant to botany, and the principles of ontology development. It includes an overview of ontologies and related resources that are relevant to plant science, with a detailed description of the Plant Ontology (PO). We discuss the challenges of building an ontology that covers all green plants (Viridiplantae). Key results Ontologies can advance plant science in four keys areas: (1) comparative genetics, genomics, phenomics, and development; (2) taxonomy and systematics; (3) semantic applications; and (4) education. Conclusions Bio-ontologies offer a flexible framework for comparative plant biology, based on common botanical understanding. As genomic and phenomic data become available for more species, we anticipate that the annotation of data with ontology terms will become less centralized, while at the same time, the need for cross-species queries will become more common, causing more researchers in plant science to turn to ontologies. PMID:22847540

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

ProGeRF: Proteome and Genome Repeat Finder Utilizing a Fast Parallel Hash Function

PubMed Central

Moraes, Walas Jhony Lopes; Rodrigues, Thiago de Souza; Bartholomeu, Daniella Castanheira

2015-01-01

Repetitive element sequences are adjacent, repeating patterns, also called motifs, and can be of different lengths; repetitions can involve their exact or approximate copies. They have been widely used as molecular markers in population biology. Given the sizes of sequenced genomes, various bioinformatics tools have been developed for the extraction of repetitive elements from DNA sequences. However, currently available tools do not provide options for identifying repetitive elements in the genome or proteome, displaying a user-friendly web interface, and performing-exhaustive searches. ProGeRF is a web site for extracting repetitive regions from genome and proteome sequences. It was designed to be efficient, fast, and accurate and primarily user-friendly web tool allowing many ways to view and analyse the results. ProGeRF (Proteome and Genome Repeat Finder) is freely available as a stand-alone program, from which the users can download the source code, and as a web tool. It was developed using the hash table approach to extract perfect and imperfect repetitive regions in a (multi)FASTA file, while allowing a linear time complexity. PMID:25811026

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

Scripps Genome ADVISER: Annotation and Distributed Variant Interpretation SERver

PubMed Central

Pham, Phillip H.; Shipman, William J.; Erikson, Galina A.; Schork, Nicholas J.; Torkamani, Ali

2015-01-01

Interpretation of human genomes is a major challenge. We present the Scripps Genome ADVISER (SG-ADVISER) suite, which aims to fill the gap between data generation and genome interpretation by performing holistic, in-depth, annotations and functional predictions on all variant types and effects. The SG-ADVISER suite includes a de-identification tool, a variant annotation web-server, and a user interface for inheritance and annotation-based filtration. SG-ADVISER allows users with no bioinformatics expertise to manipulate large volumes of variant data with ease – without the need to download large reference databases, install software, or use a command line interface. SG-ADVISER is freely available at genomics.scripps.edu/ADVISER. PMID:25706643

InSilico DB genomic datasets hub: an efficient starting point for analyzing genome-wide studies in GenePattern, Integrative Genomics Viewer, and R/Bioconductor.

PubMed

Coletta, Alain; Molter, Colin; Duqué, Robin; Steenhoff, David; Taminau, Jonatan; de Schaetzen, Virginie; Meganck, Stijn; Lazar, Cosmin; Venet, David; Detours, Vincent; Nowé, Ann; Bersini, Hugues; Weiss Solís, David Y

2012-11-18

Genomics datasets are increasingly useful for gaining biomedical insights, with adoption in the clinic underway. However, multiple hurdles related to data management stand in the way of their efficient large-scale utilization. The solution proposed is a web-based data storage hub. Having clear focus, flexibility and adaptability, InSilico DB seamlessly connects genomics dataset repositories to state-of-the-art and free GUI and command-line data analysis tools. The InSilico DB platform is a powerful collaborative environment, with advanced capabilities for biocuration, dataset sharing, and dataset subsetting and combination. InSilico DB is available from https://insilicodb.org.

Heat*seq: an interactive web tool for high-throughput sequencing experiment comparison with public data.

PubMed

Devailly, Guillaume; Mantsoki, Anna; Joshi, Anagha

2016-11-01

Better protocols and decreasing costs have made high-throughput sequencing experiments now accessible even to small experimental laboratories. However, comparing one or few experiments generated by an individual lab to the vast amount of relevant data freely available in the public domain might be limited due to lack of bioinformatics expertise. Though several tools, including genome browsers, allow such comparison at a single gene level, they do not provide a genome-wide view. We developed Heat*seq, a web-tool that allows genome scale comparison of high throughput experiments chromatin immuno-precipitation followed by sequencing, RNA-sequencing and Cap Analysis of Gene Expression) provided by a user, to the data in the public domain. Heat*seq currently contains over 12 000 experiments across diverse tissues and cell types in human, mouse and drosophila. Heat*seq displays interactive correlation heatmaps, with an ability to dynamically subset datasets to contextualize user experiments. High quality figures and tables are produced and can be downloaded in multiple formats. Web application: http://www.heatstarseq.roslin.ed.ac.uk/ Source code: https://github.com/gdevailly CONTACT: Guillaume.Devailly@roslin.ed.ac.uk or Anagha.Joshi@roslin.ed.ac.ukSupplementary information: Supplementary data are available at Bioinformatics online. © The Author 2016. Published by Oxford University Press.

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.

WebStruct and VisualStruct: Web interfaces and visualization for Structure software implemented in a cluster environment.

PubMed

Jayashree, B; Rajgopal, S; Hoisington, D; Prasanth, V P; Chandra, S

2008-09-24

Structure, is a widely used software tool to investigate population genetic structure with multi-locus genotyping data. The software uses an iterative algorithm to group individuals into "K" clusters, representing possibly K genetically distinct subpopulations. The serial implementation of this programme is processor-intensive even with small datasets. We describe an implementation of the program within a parallel framework. Speedup was achieved by running different replicates and values of K on each node of the cluster. A web-based user-oriented GUI has been implemented in PHP, through which the user can specify input parameters for the programme. The number of processors to be used can be specified in the background command. A web-based visualization tool "Visualstruct", written in PHP (HTML and Java script embedded), allows for the graphical display of population clusters output from Structure, where each individual may be visualized as a line segment with K colors defining its possible genomic composition with respect to the K genetic sub-populations. The advantage over available programs is in the increased number of individuals that can be visualized. The analyses of real datasets indicate a speedup of up to four, when comparing the speed of execution on clusters of eight processors with the speed of execution on one desktop. The software package is freely available to interested users upon request.

SynFind: Compiling Syntenic Regions across Any Set of Genomes on Demand.

PubMed

Tang, Haibao; Bomhoff, Matthew D; Briones, Evan; Zhang, Liangsheng; Schnable, James C; Lyons, Eric

2015-11-11

The identification of conserved syntenic regions enables discovery of predicted locations for orthologous and homeologous genes, even when no such gene is present. This capability means that synteny-based methods are far more effective than sequence similarity-based methods in identifying true-negatives, a necessity for studying gene loss and gene transposition. However, the identification of syntenic regions requires complex analyses which must be repeated for pairwise comparisons between any two species. Therefore, as the number of published genomes increases, there is a growing demand for scalable, simple-to-use applications to perform comparative genomic analyses that cater to both gene family studies and genome-scale studies. We implemented SynFind, a web-based tool that addresses this need. Given one query genome, SynFind is capable of identifying conserved syntenic regions in any set of target genomes. SynFind is capable of reporting per-gene information, useful for researchers studying specific gene families, as well as genome-wide data sets of syntenic gene and predicted gene locations, critical for researchers focused on large-scale genomic analyses. Inference of syntenic homologs provides the basis for correlation of functional changes around genes of interests between related organisms. Deployed on the CoGe online platform, SynFind is connected to the genomic data from over 15,000 organisms from all domains of life as well as supporting multiple releases of the same organism. SynFind makes use of a powerful job execution framework that promises scalability and reproducibility. SynFind can be accessed at http://genomevolution.org/CoGe/SynFind.pl. A video tutorial of SynFind using Phytophthrora as an example is available at http://www.youtube.com/watch?v=2Agczny9Nyc. © The Author(s) 2015. Published by Oxford University Press on behalf of the Society for Molecular Biology and Evolution.

SIMBA: a web tool for managing bacterial genome assembly generated by Ion PGM sequencing technology.

PubMed

Mariano, Diego C B; Pereira, Felipe L; Aguiar, Edgar L; Oliveira, Letícia C; Benevides, Leandro; Guimarães, Luís C; Folador, Edson L; Sousa, Thiago J; Ghosh, Preetam; Barh, Debmalya; Figueiredo, Henrique C P; Silva, Artur; Ramos, Rommel T J; Azevedo, Vasco A C

2016-12-15

The evolution of Next-Generation Sequencing (NGS) has considerably reduced the cost per sequenced-base, allowing a significant rise of sequencing projects, mainly in prokaryotes. However, the range of available NGS platforms requires different strategies and software to correctly assemble genomes. Different strategies are necessary to properly complete an assembly project, in addition to the installation or modification of various software. This requires users to have significant expertise in these software and command line scripting experience on Unix platforms, besides possessing the basic expertise on methodologies and techniques for genome assembly. These difficulties often delay the complete genome assembly projects. In order to overcome this, we developed SIMBA (SImple Manager for Bacterial Assemblies), a freely available web tool that integrates several component tools for assembling and finishing bacterial genomes. SIMBA provides a friendly and intuitive user interface so bioinformaticians, even with low computational expertise, can work under a centralized administrative control system of assemblies managed by the assembly center head. SIMBA guides the users to execute assembly process through simple and interactive pages. SIMBA workflow was divided in three modules: (i) projects: allows a general vision of genome sequencing projects, in addition to data quality analysis and data format conversions; (ii) assemblies: allows de novo assemblies with the software Mira, Minia, Newbler and SPAdes, also assembly quality validations using QUAST software; and (iii) curation: presents methods to finishing assemblies through tools for scaffolding contigs and close gaps. We also presented a case study that validated the efficacy of SIMBA to manage bacterial assemblies projects sequenced using Ion Torrent PGM. Besides to be a web tool for genome assembly, SIMBA is a complete genome assemblies project management system, which can be useful for managing of several projects in laboratories. SIMBA source code is available to download and install in local webservers at http://ufmg-simba.sourceforge.net .

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

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.

In silico mining of putative microsatellite markers from whole genome sequence of water buffalo (Bubalus bubalis) and development of first BuffSatDB

PubMed Central

2013-01-01

Background Though India has sequenced water buffalo genome but its draft assembly is based on cattle genome BTau 4.0, thus de novo chromosome wise assembly is a major pending issue for global community. The existing radiation hybrid of buffalo and these reported STR can be used further in final gap plugging and “finishing” expected in de novo genome assembly. QTL and gene mapping needs mining of putative STR from buffalo genome at equal interval on each and every chromosome. Such markers have potential role in improvement of desirable characteristics, such as high milk yields, resistance to diseases, high growth rate. The STR mining from whole genome and development of user friendly database is yet to be done to reap the benefit of whole genome sequence. Description By in silico microsatellite mining of whole genome, we have developed first STR database of water buffalo, BuffSatDb (Buffalo MicroSatellite Database (http://cabindb.iasri.res.in/buffsatdb/) which is a web based relational database of 910529 microsatellite markers, developed using PHP and MySQL database. Microsatellite markers have been generated using MIcroSAtellite tool. It is simple and systematic web based search for customised retrieval of chromosome wise and genome-wide microsatellites. Search has been enabled based on chromosomes, motif type (mono-hexa), repeat motif and repeat kind (simple and composite). The search may be customised by limiting location of STR on chromosome as well as number of markers in that range. This is a novel approach and not been implemented in any of the existing marker database. This database has been further appended with Primer3 for primer designing of the selected markers enabling researcher to select markers of choice at desired interval over the chromosome. The unique add-on of degenerate bases further helps in resolving presence of degenerate bases in current buffalo assembly. Conclusion Being first buffalo STR database in the world , this would not only pave the way in resolving current assembly problem but shall be of immense use for global community in QTL/gene mapping critically required to increase knowledge in the endeavour to increase buffalo productivity, especially for third world country where rural economy is significantly dependent on buffalo productivity. PMID:23336431

In silico mining of putative microsatellite markers from whole genome sequence of water buffalo (Bubalus bubalis) and development of first BuffSatDB.

PubMed

Sarika; Arora, Vasu; Iquebal, Mir Asif; Rai, Anil; Kumar, Dinesh

2013-01-19

Though India has sequenced water buffalo genome but its draft assembly is based on cattle genome BTau 4.0, thus de novo chromosome wise assembly is a major pending issue for global community. The existing radiation hybrid of buffalo and these reported STR can be used further in final gap plugging and "finishing" expected in de novo genome assembly. QTL and gene mapping needs mining of putative STR from buffalo genome at equal interval on each and every chromosome. Such markers have potential role in improvement of desirable characteristics, such as high milk yields, resistance to diseases, high growth rate. The STR mining from whole genome and development of user friendly database is yet to be done to reap the benefit of whole genome sequence. By in silico microsatellite mining of whole genome, we have developed first STR database of water buffalo, BuffSatDb (Buffalo MicroSatellite Database (http://cabindb.iasri.res.in/buffsatdb/) which is a web based relational database of 910529 microsatellite markers, developed using PHP and MySQL database. Microsatellite markers have been generated using MIcroSAtellite tool. It is simple and systematic web based search for customised retrieval of chromosome wise and genome-wide microsatellites. Search has been enabled based on chromosomes, motif type (mono-hexa), repeat motif and repeat kind (simple and composite). The search may be customised by limiting location of STR on chromosome as well as number of markers in that range. This is a novel approach and not been implemented in any of the existing marker database. This database has been further appended with Primer3 for primer designing of the selected markers enabling researcher to select markers of choice at desired interval over the chromosome. The unique add-on of degenerate bases further helps in resolving presence of degenerate bases in current buffalo assembly. Being first buffalo STR database in the world , this would not only pave the way in resolving current assembly problem but shall be of immense use for global community in QTL/gene mapping critically required to increase knowledge in the endeavour to increase buffalo productivity, especially for third world country where rural economy is significantly dependent on buffalo productivity.

Chromhome: A rich internet application for accessing comparative chromosome homology maps

PubMed Central

Nagarajan, Sridevi; Rens, Willem; Stalker, James; Cox, Tony; Ferguson-Smith, Malcolm A

2008-01-01

Background Comparative genomics has become a significant research area in recent years, following the availability of a number of sequenced genomes. The comparison of genomes is of great importance in the analysis of functionally important genome regions. It can also be used to understand the phylogenetic relationships of species and the mechanisms leading to rearrangement of karyotypes during evolution. Many species have been studied at the cytogenetic level by cross species chromosome painting. With the large amount of such information, it has become vital to computerize the data and make them accessible worldwide. Chromhome is a comprehensive web application that is designed to provide cytogenetic comparisons among species and to fulfil this need. Results The Chromhome application architecture is multi-tiered with an interactive client layer, business logic and database layers. Enterprise java platform with open source framework OpenLaszlo is used to implement the Rich Internet Chromhome Application. Cross species comparative mapping raw data are collected and the processed information is stored into MySQL Chromhome database. Chromhome Release 1.0 contains 109 homology maps from 51 species. The data cover species from 14 orders and 30 families. The homology map displays all the chromosomes of the compared species as one image, making comparisons among species easier. Inferred data also provides maps of homologous regions that could serve as a guideline for researchers involved in phylogenetic or evolution based studies. Conclusion Chromhome provides a useful resource for comparative genomics, holding graphical homology maps of a wide range of species. It brings together cytogenetic data of many genomes under one roof. Inferred painting can often determine the chromosomal homologous regions between two species, if each has been compared with a common third species. Inferred painting greatly reduces the need to map entire genomes and helps focus only on relevant regions of the chromosomes of the species under study. Future releases of Chromhome will accommodate more species and their respective gene and BAC maps, in addition to chromosome painting data. Chromhome application provides a single-page interface (SPI) with desktop style layout, delivering a better and richer user experience. PMID:18366796

Chromhome: a rich internet application for accessing comparative chromosome homology maps.

PubMed

Nagarajan, Sridevi; Rens, Willem; Stalker, James; Cox, Tony; Ferguson-Smith, Malcolm A

2008-03-26

Comparative genomics has become a significant research area in recent years, following the availability of a number of sequenced genomes. The comparison of genomes is of great importance in the analysis of functionally important genome regions. It can also be used to understand the phylogenetic relationships of species and the mechanisms leading to rearrangement of karyotypes during evolution. Many species have been studied at the cytogenetic level by cross species chromosome painting. With the large amount of such information, it has become vital to computerize the data and make them accessible worldwide. Chromhome http://www.chromhome.org is a comprehensive web application that is designed to provide cytogenetic comparisons among species and to fulfil this need. The Chromhome application architecture is multi-tiered with an interactive client layer, business logic and database layers. Enterprise java platform with open source framework OpenLaszlo is used to implement the Rich Internet Chromhome Application. Cross species comparative mapping raw data are collected and the processed information is stored into MySQL Chromhome database. Chromhome Release 1.0 contains 109 homology maps from 51 species. The data cover species from 14 orders and 30 families. The homology map displays all the chromosomes of the compared species as one image, making comparisons among species easier. Inferred data also provides maps of homologous regions that could serve as a guideline for researchers involved in phylogenetic or evolution based studies. Chromhome provides a useful resource for comparative genomics, holding graphical homology maps of a wide range of species. It brings together cytogenetic data of many genomes under one roof. Inferred painting can often determine the chromosomal homologous regions between two species, if each has been compared with a common third species. Inferred painting greatly reduces the need to map entire genomes and helps focus only on relevant regions of the chromosomes of the species under study. Future releases of Chromhome will accommodate more species and their respective gene and BAC maps, in addition to chromosome painting data. Chromhome application provides a single-page interface (SPI) with desktop style layout, delivering a better and richer user experience.

FMM: a web server for metabolic pathway reconstruction and comparative analysis.

PubMed

Chou, Chih-Hung; Chang, Wen-Chi; Chiu, Chih-Min; Huang, Chih-Chang; Huang, Hsien-Da

2009-07-01

Synthetic Biology, a multidisciplinary field, is growing rapidly. Improving the understanding of biological systems through mimicry and producing bio-orthogonal systems with new functions are two complementary pursuits in this field. A web server called FMM (From Metabolite to Metabolite) was developed for this purpose. FMM can reconstruct metabolic pathways form one metabolite to another metabolite among different species, based mainly on the Kyoto Encyclopedia of Genes and Genomes (KEGG) database and other integrated biological databases. Novel presentation for connecting different KEGG maps is newly provided. Both local and global graphical views of the metabolic pathways are designed. FMM has many applications in Synthetic Biology and Metabolic Engineering. For example, the reconstruction of metabolic pathways to produce valuable metabolites or secondary metabolites in bacteria or yeast is a promising strategy for drug production. FMM provides a highly effective way to elucidate the genes from which species should be cloned into those microorganisms based on FMM pathway comparative analysis. Consequently, FMM is an effective tool for applications in synthetic biology to produce both drugs and biofuels. This novel and innovative resource is now freely available at http://FMM.mbc.nctu.edu.tw/.

Genomic Target Database (GTD): A database of potential targets in human pathogenic bacteria

PubMed Central

Barh, Debmalya; Kumar, Anil; Misra, Amarendra Narayana

2009-01-01

A Genomic Target Database (GTD) has been developed having putative genomic drug targets for human bacterial pathogens. The selected pathogens are either drug resistant or vaccines are yet to be developed against them. The drug targets have been identified using subtractive genomics approaches and these are subsequently classified into Drug targets in pathogen specific unique metabolic pathways,Drug targets in host-pathogen common metabolic pathways, andMembrane localized drug targets. HTML code is used to link each target to its various properties and other available public resources. Essential resources and tools for subtractive genomic analysis, sub-cellular localization, vaccine and drug designing are also mentioned. To the best of authors knowledge, no such database (DB) is presently available that has listed metabolic pathways and membrane specific genomic drug targets based on subtractive genomics. Listed targets in GTD are readily available resource in developing drug and vaccine against the respective pathogen, its subtypes, and other family members. Currently GTD contains 58 drug targets for four pathogens. Shortly, drug targets for six more pathogens will be listed. Availability GTD is available at IIOAB website http://www.iioab.webs.com/GTD.htm. It can also be accessed at http://www.iioabdgd.webs.com.GTD is free for academic research and non-commercial use only. Commercial use is strictly prohibited without prior permission from IIOAB. PMID:20011153

dbWGFP: a database and web server of human whole-genome single nucleotide variants and their functional predictions.

PubMed

Wu, Jiaxin; Wu, Mengmeng; Li, Lianshuo; Liu, Zhuo; Zeng, Wanwen; Jiang, Rui

2016-01-01

The recent advancement of the next generation sequencing technology has enabled the fast and low-cost detection of all genetic variants spreading across the entire human genome, making the application of whole-genome sequencing a tendency in the study of disease-causing genetic variants. Nevertheless, there still lacks a repository that collects predictions of functionally damaging effects of human genetic variants, though it has been well recognized that such predictions play a central role in the analysis of whole-genome sequencing data. To fill this gap, we developed a database named dbWGFP (a database and web server of human whole-genome single nucleotide variants and their functional predictions) that contains functional predictions and annotations of nearly 8.58 billion possible human whole-genome single nucleotide variants. Specifically, this database integrates 48 functional predictions calculated by 17 popular computational methods and 44 valuable annotations obtained from various data sources. Standalone software, user-friendly query services and free downloads of this database are available at http://bioinfo.au.tsinghua.edu.cn/dbwgfp. dbWGFP provides a valuable resource for the analysis of whole-genome sequencing, exome sequencing and SNP array data, thereby complementing existing data sources and computational resources in deciphering genetic bases of human inherited diseases. © The Author(s) 2016. Published by Oxford University Press.

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.

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

WormBase 2014: new views of curated biology

PubMed Central

Harris, Todd W.; Baran, Joachim; Bieri, Tamberlyn; Cabunoc, Abigail; Chan, Juancarlos; Chen, Wen J.; Davis, Paul; Done, James; Grove, Christian; Howe, Kevin; Kishore, Ranjana; Lee, Raymond; Li, Yuling; Muller, Hans-Michael; Nakamura, Cecilia; Ozersky, Philip; Paulini, Michael; Raciti, Daniela; Schindelman, Gary; Tuli, Mary Ann; Auken, Kimberly Van; Wang, Daniel; Wang, Xiaodong; Williams, Gary; Wong, J. D.; Yook, Karen; Schedl, Tim; Hodgkin, Jonathan; Berriman, Matthew; Kersey, Paul; Spieth, John; Stein, Lincoln; Sternberg, Paul W.

2014-01-01

WormBase (http://www.wormbase.org/) is a highly curated resource dedicated to supporting research using the model organism Caenorhabditis elegans. With an electronic history predating the World Wide Web, WormBase contains information ranging from the sequence and phenotype of individual alleles to genome-wide studies generated using next-generation sequencing technologies. In recent years, we have expanded the contents to include data on additional nematodes of agricultural and medical significance, bringing the knowledge of C. elegans to bear on these systems and providing support for underserved research communities. Manual curation of the primary literature remains a central focus of the WormBase project, providing users with reliable, up-to-date and highly cross-linked information. In this update, we describe efforts to organize the original atomized and highly contextualized curated data into integrated syntheses of discrete biological topics. Next, we discuss our experiences coping with the vast increase in available genome sequences made possible through next-generation sequencing platforms. Finally, we describe some of the features and tools of the new WormBase Web site that help users better find and explore data of interest. PMID:24194605

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.

Development of universal genetic markers based on single-copy orthologous (COSII) genes in Poaceae.

PubMed

Liu, Hailan; Guo, Xiaoqin; Wu, Jiasheng; Chen, Guo-Bo; Ying, Yeqing

2013-03-01

KEY MESSAGE : We develop a set of universal genetic markers based on single-copy orthologous (COSII) genes in Poaceae. Being evolutionary conserved, single-copy orthologous (COSII) genes are particularly useful in comparative mapping and phylogenetic investigation among species. In this study, we identified 2,684 COSII genes based on five sequenced Poaceae genomes including rice, maize, sorghum, foxtail millet, and brachypodium, and then developed 1,072 COSII markers whose transferability and polymorphism among five bamboo species were further evaluated with 46 pairs of randomly selected primers. 91.3 % of the 46 primers obtained clear amplification in at least one bamboo species, and 65.2 % of them produced polymorphism in more than one species. We also used 42 of them to construct the phylogeny for the five bamboo species, and it might reflect more precise evolutionary relationship than the one based on the vegetative morphology. The results indicated a promising prospect of applying these markers to the investigation of genetic diversity and the classification of Poaceae. To ease and facilitate access of the information of common interest to readers, a web-based database of the COSII markers is provided ( http://www.sicau.edu.cn/web/yms/PCOSWeb/PCOS.html ).

An XML transfer schema for exchange of genomic and genetic mapping data: implementation as a web service in a Taverna workflow.

PubMed

Paterson, Trevor; Law, Andy

2009-08-14

Genomic analysis, particularly for less well-characterized organisms, is greatly assisted by performing comparative analyses between different types of genome maps and across species boundaries. Various providers publish a plethora of on-line resources collating genome mapping data from a multitude of species. Datasources range in scale and scope from small bespoke resources for particular organisms, through larger web-resources containing data from multiple species, to large-scale bioinformatics resources providing access to data derived from genome projects for model and non-model organisms. The heterogeneity of information held in these resources reflects both the technologies used to generate the data and the target users of each resource. Currently there is no common information exchange standard or protocol to enable access and integration of these disparate resources. Consequently data integration and comparison must be performed in an ad hoc manner. We have developed a simple generic XML schema (GenomicMappingData.xsd - GMD) to allow export and exchange of mapping data in a common lightweight XML document format. This schema represents the various types of data objects commonly described across mapping datasources and provides a mechanism for recording relationships between data objects. The schema is sufficiently generic to allow representation of any map type (for example genetic linkage maps, radiation hybrid maps, sequence maps and physical maps). It also provides mechanisms for recording data provenance and for cross referencing external datasources (including for example ENSEMBL, PubMed and Genbank.). The schema is extensible via the inclusion of additional datatypes, which can be achieved by importing further schemas, e.g. a schema defining relationship types. We have built demonstration web services that export data from our ArkDB database according to the GMD schema, facilitating the integration of data retrieval into Taverna workflows. The data exchange standard we present here provides a useful generic format for transfer and integration of genomic and genetic mapping data. The extensibility of our schema allows for inclusion of additional data and provides a mechanism for typing mapping objects via third party standards. Web services retrieving GMD-compliant mapping data demonstrate that use of this exchange standard provides a practical mechanism for achieving data integration, by facilitating syntactically and semantically-controlled access to the data.

An XML transfer schema for exchange of genomic and genetic mapping data: implementation as a web service in a Taverna workflow

PubMed Central

Paterson, Trevor; Law, Andy

2009-01-01

Background Genomic analysis, particularly for less well-characterized organisms, is greatly assisted by performing comparative analyses between different types of genome maps and across species boundaries. Various providers publish a plethora of on-line resources collating genome mapping data from a multitude of species. Datasources range in scale and scope from small bespoke resources for particular organisms, through larger web-resources containing data from multiple species, to large-scale bioinformatics resources providing access to data derived from genome projects for model and non-model organisms. The heterogeneity of information held in these resources reflects both the technologies used to generate the data and the target users of each resource. Currently there is no common information exchange standard or protocol to enable access and integration of these disparate resources. Consequently data integration and comparison must be performed in an ad hoc manner. Results We have developed a simple generic XML schema (GenomicMappingData.xsd – GMD) to allow export and exchange of mapping data in a common lightweight XML document format. This schema represents the various types of data objects commonly described across mapping datasources and provides a mechanism for recording relationships between data objects. The schema is sufficiently generic to allow representation of any map type (for example genetic linkage maps, radiation hybrid maps, sequence maps and physical maps). It also provides mechanisms for recording data provenance and for cross referencing external datasources (including for example ENSEMBL, PubMed and Genbank.). The schema is extensible via the inclusion of additional datatypes, which can be achieved by importing further schemas, e.g. a schema defining relationship types. We have built demonstration web services that export data from our ArkDB database according to the GMD schema, facilitating the integration of data retrieval into Taverna workflows. Conclusion The data exchange standard we present here provides a useful generic format for transfer and integration of genomic and genetic mapping data. The extensibility of our schema allows for inclusion of additional data and provides a mechanism for typing mapping objects via third party standards. Web services retrieving GMD-compliant mapping data demonstrate that use of this exchange standard provides a practical mechanism for achieving data integration, by facilitating syntactically and semantically-controlled access to the data. PMID:19682365

A manually annotated Actinidia chinensis var. chinensis (kiwifruit) genome highlights the challenges associated with draft genomes and gene prediction in plants.

PubMed

Pilkington, Sarah M; Crowhurst, Ross; Hilario, Elena; Nardozza, Simona; Fraser, Lena; Peng, Yongyan; Gunaseelan, Kularajathevan; Simpson, Robert; Tahir, Jibran; Deroles, Simon C; Templeton, Kerry; Luo, Zhiwei; Davy, Marcus; Cheng, Canhong; McNeilage, Mark; Scaglione, Davide; Liu, Yifei; Zhang, Qiong; Datson, Paul; De Silva, Nihal; Gardiner, Susan E; Bassett, Heather; Chagné, David; McCallum, John; Dzierzon, Helge; Deng, Cecilia; Wang, Yen-Yi; Barron, Lorna; Manako, Kelvina; Bowen, Judith; Foster, Toshi M; Erridge, Zoe A; Tiffin, Heather; Waite, Chethi N; Davies, Kevin M; Grierson, Ella P; Laing, William A; Kirk, Rebecca; Chen, Xiuyin; Wood, Marion; Montefiori, Mirco; Brummell, David A; Schwinn, Kathy E; Catanach, Andrew; Fullerton, Christina; Li, Dawei; Meiyalaghan, Sathiyamoorthy; Nieuwenhuizen, Niels; Read, Nicola; Prakash, Roneel; Hunter, Don; Zhang, Huaibi; McKenzie, Marian; Knäbel, Mareike; Harris, Alastair; Allan, Andrew C; Gleave, Andrew; Chen, Angela; Janssen, Bart J; Plunkett, Blue; Ampomah-Dwamena, Charles; Voogd, Charlotte; Leif, Davin; Lafferty, Declan; Souleyre, Edwige J F; Varkonyi-Gasic, Erika; Gambi, Francesco; Hanley, Jenny; Yao, Jia-Long; Cheung, Joey; David, Karine M; Warren, Ben; Marsh, Ken; Snowden, Kimberley C; Lin-Wang, Kui; Brian, Lara; Martinez-Sanchez, Marcela; Wang, Mindy; Ileperuma, Nadeesha; Macnee, Nikolai; Campin, Robert; McAtee, Peter; Drummond, Revel S M; Espley, Richard V; Ireland, Hilary S; Wu, Rongmei; Atkinson, Ross G; Karunairetnam, Sakuntala; Bulley, Sean; Chunkath, Shayhan; Hanley, Zac; Storey, Roy; Thrimawithana, Amali H; Thomson, Susan; David, Charles; Testolin, Raffaele; Huang, Hongwen; Hellens, Roger P; Schaffer, Robert J

2018-04-16

Most published genome sequences are drafts, and most are dominated by computational gene prediction. Draft genomes typically incorporate considerable sequence data that are not assigned to chromosomes, and predicted genes without quality confidence measures. The current Actinidia chinensis (kiwifruit) 'Hongyang' draft genome has 164 Mb of sequences unassigned to pseudo-chromosomes, and omissions have been identified in the gene models. A second genome of an A. chinensis (genotype Red5) was fully sequenced. This new sequence resulted in a 554.0 Mb assembly with all but 6 Mb assigned to pseudo-chromosomes. Pseudo-chromosomal comparisons showed a considerable number of translocation events have occurred following a whole genome duplication (WGD) event some consistent with centromeric Robertsonian-like translocations. RNA sequencing data from 12 tissues and ab initio analysis informed a genome-wide manual annotation, using the WebApollo tool. In total, 33,044 gene loci represented by 33,123 isoforms were identified, named and tagged for quality of evidential support. Of these 3114 (9.4%) were identical to a protein within 'Hongyang' The Kiwifruit Information Resource (KIR v2). Some proportion of the differences will be varietal polymorphisms. However, as most computationally predicted Red5 models required manual re-annotation this proportion is expected to be small. The quality of the new gene models was tested by fully sequencing 550 cloned 'Hort16A' cDNAs and comparing with the predicted protein models for Red5 and both the original 'Hongyang' assembly and the revised annotation from KIR v2. Only 48.9% and 63.5% of the cDNAs had a match with 90% identity or better to the original and revised 'Hongyang' annotation, respectively, compared with 90.9% to the Red5 models. Our study highlights the need to take a cautious approach to draft genomes and computationally predicted genes. Our use of the manual annotation tool WebApollo facilitated manual checking and correction of gene models enabling improvement of computational prediction. This utility was especially relevant for certain types of gene families such as the EXPANSIN like genes. Finally, this high quality gene set will supply the kiwifruit and general plant community with a new tool for genomics and other comparative analysis.

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.

QuadBase2: web server for multiplexed guanine quadruplex mining and visualization

PubMed Central

Dhapola, Parashar; Chowdhury, Shantanu

2016-01-01

DNA guanine quadruplexes or G4s are non-canonical DNA secondary structures which affect genomic processes like replication, transcription and recombination. G4s are computationally identified by specific nucleotide motifs which are also called putative G4 (PG4) motifs. Despite the general relevance of these structures, there is currently no tool available that can allow batch queries and genome-wide analysis of these motifs in a user-friendly interface. QuadBase2 (quadbase.igib.res.in) presents a completely reinvented web server version of previously published QuadBase database. QuadBase2 enables users to mine PG4 motifs in up to 178 eukaryotes through the EuQuad module. This module interfaces with Ensembl Compara database, to allow users mine PG4 motifs in the orthologues of genes of interest across eukaryotes. PG4 motifs can be mined across genes and their promoter sequences in 1719 prokaryotes through ProQuad module. This module includes a feature that allows genome-wide mining of PG4 motifs and their visualization as circular histograms. TetraplexFinder, the module for mining PG4 motifs in user-provided sequences is now capable of handling up to 20 MB of data. QuadBase2 is a comprehensive PG4 motif mining tool that further expands the configurations and algorithms for mining PG4 motifs in a user-friendly way. PMID:27185890

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

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

King, Zachary A.; Drager, Andreas; Ebrahim, Ali

Escher is a web application for visualizing data on biological pathways. Three key features make Escher a uniquely effective tool for pathway visualization. First, users can rapidly design new pathway maps. Escher provides pathway suggestions based on user data and genome-scale models, so users can draw pathways in a semi-automated way. Second, users can visualize data related to genes or proteins on the associated reactions and pathways, using rules that define which enzymes catalyze each reaction. Thus, users can identify trends in common genomic data types (e.g. RNA-Seq, proteomics, ChIP)—in conjunction with metabolite- and reaction-oriented data types (e.g. metabolomics, fluxomics).more » Third, Escher harnesses the strengths of web technologies (SVG, D3, developer tools) so that visualizations can be rapidly adapted, extended, shared, and embedded. This paper provides examples of each of these features and explains how the development approach used for Escher can be used to guide the development of future visualization tools.« less

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

PubMed Central

King, Zachary A.; Dräger, Andreas; Ebrahim, Ali; Sonnenschein, Nikolaus; Lewis, Nathan E.; Palsson, Bernhard O.

2015-01-01

Escher is a web application for visualizing data on biological pathways. Three key features make Escher a uniquely effective tool for pathway visualization. First, users can rapidly design new pathway maps. Escher provides pathway suggestions based on user data and genome-scale models, so users can draw pathways in a semi-automated way. Second, users can visualize data related to genes or proteins on the associated reactions and pathways, using rules that define which enzymes catalyze each reaction. Thus, users can identify trends in common genomic data types (e.g. RNA-Seq, proteomics, ChIP)—in conjunction with metabolite- and reaction-oriented data types (e.g. metabolomics, fluxomics). Third, Escher harnesses the strengths of web technologies (SVG, D3, developer tools) so that visualizations can be rapidly adapted, extended, shared, and embedded. This paper provides examples of each of these features and explains how the development approach used for Escher can be used to guide the development of future visualization tools. PMID:26313928

CNV-WebStore: online CNV analysis, storage and interpretation.

PubMed

Vandeweyer, Geert; Reyniers, Edwin; Wuyts, Wim; Rooms, Liesbeth; Kooy, R Frank

2011-01-05

Microarray technology allows the analysis of genomic aberrations at an ever increasing resolution, making functional interpretation of these vast amounts of data the main bottleneck in routine implementation of high resolution array platforms, and emphasising the need for a centralised and easy to use CNV data management and interpretation system. We present CNV-WebStore, an online platform to streamline the processing and downstream interpretation of microarray data in a clinical context, tailored towards but not limited to the Illumina BeadArray platform. Provided analysis tools include CNV analsyis, parent of origin and uniparental disomy detection. Interpretation tools include data visualisation, gene prioritisation, automated PubMed searching, linking data to several genome browsers and annotation of CNVs based on several public databases. Finally a module is provided for uniform reporting of results. CNV-WebStore is able to present copy number data in an intuitive way to both lab technicians and clinicians, making it a useful tool in daily clinical practice.

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

Simplifier: a web tool to eliminate redundant NGS contigs.

PubMed

Ramos, Rommel Thiago Jucá; Carneiro, Adriana Ribeiro; Azevedo, Vasco; Schneider, Maria Paula; Barh, Debmalya; Silva, Artur

2012-01-01

Modern genomic sequencing technologies produce a large amount of data with reduced cost per base; however, this data consists of short reads. This reduction in the size of the reads, compared to those obtained with previous methodologies, presents new challenges, including a need for efficient algorithms for the assembly of genomes from short reads and for resolving repetitions. Additionally after abinitio assembly, curation of the hundreds or thousands of contigs generated by assemblers demands considerable time and computational resources. We developed Simplifier, a stand-alone software that selectively eliminates redundant sequences from the collection of contigs generated by ab initio assembly of genomes. Application of Simplifier to data generated by assembly of the genome of Corynebacterium pseudotuberculosis strain 258 reduced the number of contigs generated by ab initio methods from 8,004 to 5,272, a reduction of 34.14%; in addition, N50 increased from 1 kb to 1.5 kb. Processing the contigs of Escherichia coli DH10B with Simplifier reduced the mate-paired library 17.47% and the fragment library 23.91%. Simplifier removed redundant sequences from datasets produced by assemblers, thereby reducing the effort required for finalization of genome assembly in tests with data from Prokaryotic organisms. Simplifier is available at http://www.genoma.ufpa.br/rramos/softwares/simplifier.xhtmlIt requires Sun jdk 6 or higher.

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

MODBASE, a database of annotated comparative protein structure models

PubMed Central

Pieper, Ursula; Eswar, Narayanan; Stuart, Ashley C.; Ilyin, Valentin A.; Sali, Andrej

2002-01-01

MODBASE (http://guitar.rockefeller.edu/modbase) is a relational database of annotated comparative protein structure models for all available protein sequences matched to at least one known protein structure. The models are calculated by MODPIPE, an automated modeling pipeline that relies on PSI-BLAST, IMPALA and MODELLER. MODBASE uses the MySQL relational database management system for flexible and efficient querying, and the MODVIEW Netscape plugin for viewing and manipulating multiple sequences and structures. It is updated regularly to reflect the growth of the protein sequence and structure databases, as well as improvements in the software for calculating the models. For ease of access, MODBASE is organized into different datasets. The largest dataset contains models for domains in 304 517 out of 539 171 unique protein sequences in the complete TrEMBL database (23 March 2001); only models based on significant alignments (PSI-BLAST E-value < 10–4) and models assessed to have the correct fold are included. Other datasets include models for target selection and structure-based annotation by the New York Structural Genomics Research Consortium, models for prediction of genes in the Drosophila melanogaster genome, models for structure determination of several ribosomal particles and models calculated by the MODWEB comparative modeling web server. PMID:11752309

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.

A Bacterial Analysis Platform: An Integrated System for Analysing Bacterial Whole Genome Sequencing Data for Clinical Diagnostics and Surveillance.

PubMed

Thomsen, Martin Christen Frølund; Ahrenfeldt, Johanne; Cisneros, Jose Luis Bellod; Jurtz, Vanessa; Larsen, Mette Voldby; Hasman, Henrik; Aarestrup, Frank Møller; Lund, Ole

2016-01-01

Recent advances in whole genome sequencing have made the technology available for routine use in microbiological laboratories. However, a major obstacle for using this technology is the availability of simple and automatic bioinformatics tools. Based on previously published and already available web-based tools we developed a single pipeline for batch uploading of whole genome sequencing data from multiple bacterial isolates. The pipeline will automatically identify the bacterial species and, if applicable, assemble the genome, identify the multilocus sequence type, plasmids, virulence genes and antimicrobial resistance genes. A short printable report for each sample will be provided and an Excel spreadsheet containing all the metadata and a summary of the results for all submitted samples can be downloaded. The pipeline was benchmarked using datasets previously used to test the individual services. The reported results enable a rapid overview of the major results, and comparing that to the previously found results showed that the platform is reliable and able to correctly predict the species and find most of the expected genes automatically. In conclusion, a combined bioinformatics platform was developed and made publicly available, providing easy-to-use automated analysis of bacterial whole genome sequencing data. The platform may be of immediate relevance as a guide for investigators using whole genome sequencing for clinical diagnostics and surveillance. The platform is freely available at: https://cge.cbs.dtu.dk/services/CGEpipeline-1.1 and it is the intention that it will continue to be expanded with new features as these become available.

The Giardia genome project database.

PubMed

McArthur, A G; Morrison, H G; Nixon, J E; Passamaneck, N Q; Kim, U; Hinkle, G; Crocker, M K; Holder, M E; Farr, R; Reich, C I; Olsen, G E; Aley, S B; Adam, R D; Gillin, F D; Sogin, M L

2000-08-15

The Giardia genome project database provides an online resource for Giardia lamblia (WB strain, clone C6) genome sequence information. The database includes edited single-pass reads, the results of BLASTX searches, and details of progress towards sequencing the entire 12 million-bp Giardia genome. Pre-sorted BLASTX results can be retrieved based on keyword searches and BLAST searches of the high throughput Giardia data can be initiated from the web site or through NCBI. Descriptions of the genomic DNA libraries, project protocols and summary statistics are also available. Although the Giardia genome project is ongoing, new sequences are made available on a bi-monthly basis to ensure that researchers have access to information that may assist them in the search for genes and their biological function. The current URL of the Giardia genome project database is www.mbl.edu/Giardia.

blend4php: a PHP API for galaxy.

PubMed

Wytko, Connor; Soto, Brian; Ficklin, Stephen P

2017-01-01

Galaxy is a popular framework for execution of complex analytical pipelines typically for large data sets, and is a commonly used for (but not limited to) genomic, genetic and related biological analysis. It provides a web front-end and integrates with high performance computing resources. Here we report the development of the blend4php library that wraps Galaxy's RESTful API into a PHP-based library. PHP-based web applications can use blend4php to automate execution, monitoring and management of a remote Galaxy server, including its users, workflows, jobs and more. The blend4php library was specifically developed for the integration of Galaxy with Tripal, the open-source toolkit for the creation of online genomic and genetic web sites. However, it was designed as an independent library for use by any application, and is freely available under version 3 of the GNU Lesser General Public License (LPGL v3.0) at https://github.com/galaxyproject/blend4phpDatabase URL: https://github.com/galaxyproject/blend4php. © The Author(s) 2017. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

Pathosphere.org: Pathogen Detection and Characterization Through a Web-based, Open-source Informatics Platform

DTIC Science & Technology

2015-12-29

human), Homo sapiens chromosome (human), Mus_musculus ( rodent ), Sus scrofa (pig), mitochondrion genome, and Xenopus laevis (frog) . The taxonomy... Amazon Web Services. PLoS Comput Biol 2011, 7:e1002147. 10. Briese T, Paweska JT, McMullan LK, Hutchison SK, Street C, Palacios G, Khristova ML...human enterovirus C genotypes found in respiratory samples from Peru . J Gen Virol 2013, 94(Pt 1):120–7. 54. Jacob ST, Crozier I, Schieffelin JS

Fungal Genomics for Energy and Environment

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

Grigoriev, Igor V.

2013-03-11

Genomes of fungi relevant to energy and environment are in focus of the Fungal Genomic Program at the US Department of Energy Joint Genome Institute (JGI). One of its projects, the Genomics Encyclopedia of Fungi, targets fungi related to plant health (symbionts, pathogens, and biocontrol agents) and biorefinery processes (cellulose degradation, sugar fermentation, industrial hosts) by means of genome sequencing and analysis. New chapters of the Encyclopedia can be opened with user proposals to the JGI Community Sequencing Program (CSP). Another JGI project, the 1000 fungal genomes, explores fungal diversity on genome level at scale and is open for usersmore » to nominate new species for sequencing. Over 200 fungal genomes have been sequenced by JGI to date and released through MycoCosm (www.jgi.doe.gov/fungi), a fungal web-portal, which integrates sequence and functional data with genome analysis tools for user community. Sequence analysis supported by functional genomics leads to developing parts list for complex systems ranging from ecosystems of biofuel crops to biorefineries. Recent examples of such parts suggested by comparative genomics and functional analysis in these areas are presented here.« less

MICRA: an automatic pipeline for fast characterization of microbial genomes from high-throughput sequencing data.

PubMed

Caboche, Ségolène; Even, Gaël; Loywick, Alexandre; Audebert, Christophe; Hot, David

2017-12-19

The increase in available sequence data has advanced the field of microbiology; however, making sense of these data without bioinformatics skills is still problematic. We describe MICRA, an automatic pipeline, available as a web interface, for microbial identification and characterization through reads analysis. MICRA uses iterative mapping against reference genomes to identify genes and variations. Additional modules allow prediction of antibiotic susceptibility and resistance and comparing the results of several samples. MICRA is fast, producing few false-positive annotations and variant calls compared to current methods, making it a tool of great interest for fully exploiting sequencing data.

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.

VIPER: a web application for rapid expert review of variant calls.

PubMed

Wöste, Marius; Dugas, Martin

2018-06-01

With the rapid development in next-generation sequencing, cost and time requirements for genomic sequencing are decreasing, enabling applications in many areas such as cancer research. Many tools have been developed to analyze genomic variation ranging from single nucleotide variants to whole chromosomal aberrations. As sequencing throughput increases, the number of variants called by such tools also grows. Often employed manual inspection of such calls is thus becoming a time-consuming procedure. We developed the Variant InsPector and Expert Rating tool (VIPER) to speed up this process by integrating the Integrative Genomics Viewer into a web application. Analysts can then quickly iterate through variants, apply filters and make decisions based on the generated images and variant metadata. VIPER was successfully employed in analyses with manual inspection of more than 10 000 calls. VIPER is implemented in Java and Javascript and is freely available at https://github.com/MarWoes/viper. marius.woeste@uni-muenster.de. Supplementary data are available at Bioinformatics online.

AncestrySNPminer: A bioinformatics tool to retrieve and develop ancestry informative SNP panels

PubMed Central

Amirisetty, Sushil; Khurana Hershey, Gurjit K.; Baye, Tesfaye M.

2012-01-01

A wealth of genomic information is available in public and private databases. However, this information is underutilized for uncovering population specific and functionally relevant markers underlying complex human traits. Given the huge amount of SNP data available from the annotation of human genetic variation, data mining is a faster and cost effective approach for investigating the number of SNPs that are informative for ancestry. In this study, we present AncestrySNPminer, the first web-based bioinformatics tool specifically designed to retrieve Ancestry Informative Markers (AIMs) from genomic data sets and link these informative markers to genes and ontological annotation classes. The tool includes an automated and simple “scripting at the click of a button” functionality that enables researchers to perform various population genomics statistical analyses methods with user friendly querying and filtering of data sets across various populations through a single web interface. AncestrySNPminer can be freely accessed at https://research.cchmc.org/mershalab/AncestrySNPminer/login.php. PMID:22584067

An unsupervised classification scheme for improving predictions of prokaryotic TIS.

PubMed

Tech, Maike; Meinicke, Peter

2006-03-09

Although it is not difficult for state-of-the-art gene finders to identify coding regions in prokaryotic genomes, exact prediction of the corresponding translation initiation sites (TIS) is still a challenging problem. Recently a number of post-processing tools have been proposed for improving the annotation of prokaryotic TIS. However, inherent difficulties of these approaches arise from the considerable variation of TIS characteristics across different species. Therefore prior assumptions about the properties of prokaryotic gene starts may cause suboptimal predictions for newly sequenced genomes with TIS signals differing from those of well-investigated genomes. We introduce a clustering algorithm for completely unsupervised scoring of potential TIS, based on positionally smoothed probability matrices. The algorithm requires an initial gene prediction and the genomic sequence of the organism to perform the reannotation. As compared with other methods for improving predictions of gene starts in bacterial genomes, our approach is not based on any specific assumptions about prokaryotic TIS. Despite the generality of the underlying algorithm, the prediction rate of our method is competitive on experimentally verified test data from E. coli and B. subtilis. Regarding genomes with high G+C content, in contrast to some previously proposed methods, our algorithm also provides good performance on P. aeruginosa, B. pseudomallei and R. solanacearum. On reliable test data we showed that our method provides good results in post-processing the predictions of the widely-used program GLIMMER. The underlying clustering algorithm is robust with respect to variations in the initial TIS annotation and does not require specific assumptions about prokaryotic gene starts. These features are particularly useful on genomes with high G+C content. The algorithm has been implemented in the tool "TICO" (TIs COrrector) which is publicly available from our web site.

IVAG: An Integrative Visualization Application for Various Types of Genomic Data Based on R-Shiny and the Docker Platform.

PubMed

Lee, Tae-Rim; Ahn, Jin Mo; Kim, Gyuhee; Kim, Sangsoo

2017-12-01

Next-generation sequencing (NGS) technology has become a trend in the genomics research area. There are many software programs and automated pipelines to analyze NGS data, which can ease the pain for traditional scientists who are not familiar with computer programming. However, downstream analyses, such as finding differentially expressed genes or visualizing linkage disequilibrium maps and genome-wide association study (GWAS) data, still remain a challenge. Here, we introduce a dockerized web application written in R using the Shiny platform to visualize pre-analyzed RNA sequencing and GWAS data. In addition, we have integrated a genome browser based on the JBrowse platform and an automated intermediate parsing process required for custom track construction, so that users can easily build and navigate their personal genome tracks with in-house datasets. This application will help scientists perform series of downstream analyses and obtain a more integrative understanding about various types of genomic data by interactively visualizing them with customizable options.

7TMRmine: a Web server for hierarchical mining of 7TMR proteins

PubMed Central

Lu, Guoqing; Wang, Zhifang; Jones, Alan M; Moriyama, Etsuko N

2009-01-01

Background Seven-transmembrane region-containing receptors (7TMRs) play central roles in eukaryotic signal transduction. Due to their biomedical importance, thorough mining of 7TMRs from diverse genomes has been an active target of bioinformatics and pharmacogenomics research. The need for new and accurate 7TMR/GPCR prediction tools is paramount with the accelerated rate of acquisition of diverse sequence information. Currently available and often used protein classification methods (e.g., profile hidden Markov Models) are highly accurate for identifying their membership information among already known 7TMR subfamilies. However, these alignment-based methods are less effective for identifying remote similarities, e.g., identifying proteins from highly divergent or possibly new 7TMR families. In this regard, more sensitive (e.g., alignment-free) methods are needed to complement the existing protein classification methods. A better strategy would be to combine different classifiers, from more specific to more sensitive methods, to identify a broader spectrum of 7TMR protein candidates. Description We developed a Web server, 7TMRmine, by integrating alignment-free and alignment-based classifiers specifically trained to identify candidate 7TMR proteins as well as transmembrane (TM) prediction methods. This new tool enables researchers to easily assess the distribution of GPCR functionality in diverse genomes or individual newly-discovered proteins. 7TMRmine is easily customized and facilitates exploratory analysis of diverse genomes. Users can integrate various alignment-based, alignment-free, and TM-prediction methods in any combination and in any hierarchical order. Sixteen classifiers (including two TM-prediction methods) are available on the 7TMRmine Web server. Not only can the 7TMRmine tool be used for 7TMR mining, but also for general TM-protein analysis. Users can submit protein sequences for analysis, or explore pre-analyzed results for multiple genomes. The server currently includes prediction results and the summary statistics for 68 genomes. Conclusion 7TMRmine facilitates the discovery of 7TMR proteins. By combining prediction results from different classifiers in a multi-level filtering process, prioritized sets of 7TMR candidates can be obtained for further investigation. 7TMRmine can be also used as a general TM-protein classifier. Comparisons of TM and 7TMR protein distributions among 68 genomes revealed interesting differences in evolution of these protein families among major eukaryotic phyla. PMID:19538753

PredictSNP2: A Unified Platform for Accurately Evaluating SNP Effects by Exploiting the Different Characteristics of Variants in Distinct Genomic Regions

PubMed Central

Brezovský, Jan

2016-01-01

An important message taken from human genome sequencing projects is that the human population exhibits approximately 99.9% genetic similarity. Variations in the remaining parts of the genome determine our identity, trace our history and reveal our heritage. The precise delineation of phenotypically causal variants plays a key role in providing accurate personalized diagnosis, prognosis, and treatment of inherited diseases. Several computational methods for achieving such delineation have been reported recently. However, their ability to pinpoint potentially deleterious variants is limited by the fact that their mechanisms of prediction do not account for the existence of different categories of variants. Consequently, their output is biased towards the variant categories that are most strongly represented in the variant databases. Moreover, most such methods provide numeric scores but not binary predictions of the deleteriousness of variants or confidence scores that would be more easily understood by users. We have constructed three datasets covering different types of disease-related variants, which were divided across five categories: (i) regulatory, (ii) splicing, (iii) missense, (iv) synonymous, and (v) nonsense variants. These datasets were used to develop category-optimal decision thresholds and to evaluate six tools for variant prioritization: CADD, DANN, FATHMM, FitCons, FunSeq2 and GWAVA. This evaluation revealed some important advantages of the category-based approach. The results obtained with the five best-performing tools were then combined into a consensus score. Additional comparative analyses showed that in the case of missense variations, protein-based predictors perform better than DNA sequence-based predictors. A user-friendly web interface was developed that provides easy access to the five tools’ predictions, and their consensus scores, in a user-understandable format tailored to the specific features of different categories of variations. To enable comprehensive evaluation of variants, the predictions are complemented with annotations from eight databases. The web server is freely available to the community at http://loschmidt.chemi.muni.cz/predictsnp2. PMID:27224906

PredictSNP2: A Unified Platform for Accurately Evaluating SNP Effects by Exploiting the Different Characteristics of Variants in Distinct Genomic Regions.

PubMed

Bendl, Jaroslav; Musil, Miloš; Štourač, Jan; Zendulka, Jaroslav; Damborský, Jiří; Brezovský, Jan

2016-05-01

An important message taken from human genome sequencing projects is that the human population exhibits approximately 99.9% genetic similarity. Variations in the remaining parts of the genome determine our identity, trace our history and reveal our heritage. The precise delineation of phenotypically causal variants plays a key role in providing accurate personalized diagnosis, prognosis, and treatment of inherited diseases. Several computational methods for achieving such delineation have been reported recently. However, their ability to pinpoint potentially deleterious variants is limited by the fact that their mechanisms of prediction do not account for the existence of different categories of variants. Consequently, their output is biased towards the variant categories that are most strongly represented in the variant databases. Moreover, most such methods provide numeric scores but not binary predictions of the deleteriousness of variants or confidence scores that would be more easily understood by users. We have constructed three datasets covering different types of disease-related variants, which were divided across five categories: (i) regulatory, (ii) splicing, (iii) missense, (iv) synonymous, and (v) nonsense variants. These datasets were used to develop category-optimal decision thresholds and to evaluate six tools for variant prioritization: CADD, DANN, FATHMM, FitCons, FunSeq2 and GWAVA. This evaluation revealed some important advantages of the category-based approach. The results obtained with the five best-performing tools were then combined into a consensus score. Additional comparative analyses showed that in the case of missense variations, protein-based predictors perform better than DNA sequence-based predictors. A user-friendly web interface was developed that provides easy access to the five tools' predictions, and their consensus scores, in a user-understandable format tailored to the specific features of different categories of variations. To enable comprehensive evaluation of variants, the predictions are complemented with annotations from eight databases. The web server is freely available to the community at http://loschmidt.chemi.muni.cz/predictsnp2.

NEIBank: Genomics and bioinformatics resources for vision research

PubMed Central

Peterson, Katherine; Gao, James; Buchoff, Patee; Jaworski, Cynthia; Bowes-Rickman, Catherine; Ebright, Jessica N.; Hauser, Michael A.; Hoover, David

2008-01-01

NEIBank is an integrated resource for genomics and bioinformatics in vision research. It includes expressed sequence tag (EST) data and sequence-verified cDNA clones for multiple eye tissues of several species, web-based access to human eye-specific SAGE data through EyeSAGE, and comprehensive, annotated databases of known human eye disease genes and candidate disease gene loci. All expression- and disease-related data are integrated in EyeBrowse, an eye-centric genome browser. NEIBank provides a comprehensive overview of current knowledge of the transcriptional repertoires of eye tissues and their relation to pathology. PMID:18648525

WebArray: an online platform for microarray data analysis

PubMed Central

Xia, Xiaoqin; McClelland, Michael; Wang, Yipeng

2005-01-01

Background Many cutting-edge microarray analysis tools and algorithms, including commonly used limma and affy packages in Bioconductor, need sophisticated knowledge of mathematics, statistics and computer skills for implementation. Commercially available software can provide a user-friendly interface at considerable cost. To facilitate the use of these tools for microarray data analysis on an open platform we developed an online microarray data analysis platform, WebArray, for bench biologists to utilize these tools to explore data from single/dual color microarray experiments. Results The currently implemented functions were based on limma and affy package from Bioconductor, the spacings LOESS histogram (SPLOSH) method, PCA-assisted normalization method and genome mapping method. WebArray incorporates these packages and provides a user-friendly interface for accessing a wide range of key functions of limma and others, such as spot quality weight, background correction, graphical plotting, normalization, linear modeling, empirical bayes statistical analysis, false discovery rate (FDR) estimation, chromosomal mapping for genome comparison. Conclusion WebArray offers a convenient platform for bench biologists to access several cutting-edge microarray data analysis tools. The website is freely available at . It runs on a Linux server with Apache and MySQL. PMID:16371165

JNSViewer—A JavaScript-based Nucleotide Sequence Viewer for DNA/RNA secondary structures

PubMed Central

Dong, Min; Graham, Mitchell; Yadav, Nehul

2017-01-01

Many tools are available for visualizing RNA or DNA secondary structures, but there is scarce implementation in JavaScript that provides seamless integration with the increasingly popular web computational platforms. We have developed JNSViewer, a highly interactive web service, which is bundled with several popular tools for DNA/RNA secondary structure prediction and can provide precise and interactive correspondence among nucleotides, dot-bracket data, secondary structure graphs, and genic annotations. In JNSViewer, users can perform RNA secondary structure predictions with different programs and settings, add customized genic annotations in GFF format to structure graphs, search for specific linear motifs, and extract relevant structure graphs of sub-sequences. JNSViewer also allows users to choose a transcript or specific segment of Arabidopsis thaliana genome sequences and predict the corresponding secondary structure. Popular genome browsers (i.e., JBrowse and BrowserGenome) were integrated into JNSViewer to provide powerful visualizations of chromosomal locations, genic annotations, and secondary structures. In addition, we used StructureFold with default settings to predict some RNA structures for Arabidopsis by incorporating in vivo high-throughput RNA structure profiling data and stored the results in our web server, which might be a useful resource for RNA secondary structure studies in plants. JNSViewer is available at http://bioinfolab.miamioh.edu/jnsviewer/index.html. PMID:28582416

Fueling the Future with Fungal Genomes

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

Grigoriev, Igor V.

2014-10-27

Genomes of fungi relevant to energy and environment are in focus of the JGI Fungal Genomic Program. One of its projects, the Genomics Encyclopedia of Fungi, targets fungi related to plant health (symbionts and pathogens) and biorefinery processes (cellulose degradation and sugar fermentation) by means of genome sequencing and analysis. New chapters of the Encyclopedia can be opened with user proposals to the JGI Community Science Program (CSP). Another JGI project, the 1000 fungal genomes, explores fungal diversity on genome level at scale and is open for users to nominate new species for sequencing. Over 400 fungal genomes have beenmore » sequenced by JGI to date and released through MycoCosm (www.jgi.doe.gov/fungi), a fungal web-portal, which integrates sequence and functional data with genome analysis tools for user community. Sequence analysis supported by functional genomics will lead to developing parts list for complex systems ranging from ecosystems of biofuel crops to biorefineries. Recent examples of such ‘parts’ suggested by comparative genomics and functional analysis in these areas are presented here.« less

Automated design of paralogue ratio test assays for the accurate and rapid typing of copy number variation

PubMed Central

Veal, Colin D.; Xu, Hang; Reekie, Katherine; Free, Robert; Hardwick, Robert J.; McVey, David; Brookes, Anthony J.; Hollox, Edward J.; Talbot, Christopher J.

2013-01-01

Motivation: Genomic copy number variation (CNV) can influence susceptibility to common diseases. High-throughput measurement of gene copy number on large numbers of samples is a challenging, yet critical, stage in confirming observations from sequencing or array Comparative Genome Hybridization (CGH). The paralogue ratio test (PRT) is a simple, cost-effective method of accurately determining copy number by quantifying the amplification ratio between a target and reference amplicon. PRT has been successfully applied to several studies analyzing common CNV. However, its use has not been widespread because of difficulties in assay design. Results: We present PRTPrimer (www.prtprimer.org) software for automated PRT assay design. In addition to stand-alone software, the web site includes a database of pre-designed assays for the human genome at an average spacing of 6 kb and a web interface for custom assay design. Other reference genomes can also be analyzed through local installation of the software. The usefulness of PRTPrimer was tested within known CNV, and showed reproducible quantification. This software and database provide assays that can rapidly genotype CNV, cost-effectively, on a large number of samples and will enable the widespread adoption of PRT. Availability: PRTPrimer is available in two forms: a Perl script (version 5.14 and higher) that can be run from the command line on Linux systems and as a service on the PRTPrimer web site (www.prtprimer.org). Contact: cjt14@le.ac.uk Supplementary Information: Supplementary data are available at Bioinformatics online. PMID:23742985

MicroScope in 2017: an expanding and evolving integrated resource for community expertise of microbial genomes

PubMed Central

Vallenet, David; Calteau, Alexandra; Cruveiller, Stéphane; Gachet, Mathieu; Lajus, Aurélie; Josso, Adrien; Mercier, Jonathan; Renaux, Alexandre; Rollin, Johan; Rouy, Zoe; Roche, David; Scarpelli, Claude; Médigue, Claudine

2017-01-01

The annotation of genomes from NGS platforms needs to be automated and fully integrated. However, maintaining consistency and accuracy in genome annotation is a challenging problem because millions of protein database entries are not assigned reliable functions. This shortcoming limits the knowledge that can be extracted from genomes and metabolic models. Launched in 2005, the MicroScope platform (http://www.genoscope.cns.fr/agc/microscope) is an integrative resource that supports systematic and efficient revision of microbial genome annotation, data management and comparative analysis. Effective comparative analysis requires a consistent and complete view of biological data, and therefore, support for reviewing the quality of functional annotation is critical. MicroScope allows users to analyze microbial (meta)genomes together with post-genomic experiment results if any (i.e. transcriptomics, re-sequencing of evolved strains, mutant collections, phenotype data). It combines tools and graphical interfaces to analyze genomes and to perform the expert curation of gene functions in a comparative context. Starting with a short overview of the MicroScope system, this paper focuses on some major improvements of the Web interface, mainly for the submission of genomic data and on original tools and pipelines that have been developed and integrated in the platform: computation of pan-genomes and prediction of biosynthetic gene clusters. Today the resource contains data for more than 6000 microbial genomes, and among the 2700 personal accounts (65% of which are now from foreign countries), 14% of the users are performing expert annotations, on at least a weekly basis, contributing to improve the quality of microbial genome annotations. PMID:27899624

Genome Calligrapher: A Web Tool for Refactoring Bacterial Genome Sequences for de Novo DNA Synthesis.

PubMed

Christen, Matthias; Deutsch, Samuel; Christen, Beat

2015-08-21

Recent advances in synthetic biology have resulted in an increasing demand for the de novo synthesis of large-scale DNA constructs. Any process improvement that enables fast and cost-effective streamlining of digitized genetic information into fabricable DNA sequences holds great promise to study, mine, and engineer genomes. Here, we present Genome Calligrapher, a computer-aided design web tool intended for whole genome refactoring of bacterial chromosomes for de novo DNA synthesis. By applying a neutral recoding algorithm, Genome Calligrapher optimizes GC content and removes obstructive DNA features known to interfere with the synthesis of double-stranded DNA and the higher order assembly into large DNA constructs. Subsequent bioinformatics analysis revealed that synthesis constraints are prevalent among bacterial genomes. However, a low level of codon replacement is sufficient for refactoring bacterial genomes into easy-to-synthesize DNA sequences. To test the algorithm, 168 kb of synthetic DNA comprising approximately 20 percent of the synthetic essential genome of the cell-cycle bacterium Caulobacter crescentus was streamlined and then ordered from a commercial supplier of low-cost de novo DNA synthesis. The successful assembly into eight 20 kb segments indicates that Genome Calligrapher algorithm can be efficiently used to refactor difficult-to-synthesize DNA. Genome Calligrapher is broadly applicable to recode biosynthetic pathways, DNA sequences, and whole bacterial genomes, thus offering new opportunities to use synthetic biology tools to explore the functionality of microbial diversity. The Genome Calligrapher web tool can be accessed at https://christenlab.ethz.ch/GenomeCalligrapher  .

D-MATRIX: A web tool for constructing weight matrix of conserved DNA motifs

PubMed Central

Sen, Naresh; Mishra, Manoj; Khan, Feroz; Meena, Abha; Sharma, Ashok

2009-01-01

Despite considerable efforts to date, DNA motif prediction in whole genome remains a challenge for researchers. Currently the genome wide motif prediction tools required either direct pattern sequence (for single motif) or weight matrix (for multiple motifs). Although there are known motif pattern databases and tools for genome level prediction but no tool for weight matrix construction. Considering this, we developed a D-MATRIX tool which predicts the different types of weight matrix based on user defined aligned motif sequence set and motif width. For retrieval of known motif sequences user can access the commonly used databases such as TFD, RegulonDB, DBTBS, Transfac. D­MATRIX program uses a simple statistical approach for weight matrix construction, which can be converted into different file formats according to user requirement. It provides the possibility to identify the conserved motifs in the co­regulated genes or whole genome. As example, we successfully constructed the weight matrix of LexA transcription factor binding site with the help of known sos­box cis­regulatory elements in Deinococcus radiodurans genome. The algorithm is implemented in C-Sharp and wrapped in ASP.Net to maintain a user friendly web interface. D­MATRIX tool is accessible through the CIMAP domain network. Availability http://203.190.147.116/dmatrix/ PMID:19759861

D-MATRIX: a web tool for constructing weight matrix of conserved DNA motifs.

PubMed

Sen, Naresh; Mishra, Manoj; Khan, Feroz; Meena, Abha; Sharma, Ashok

2009-07-27

Despite considerable efforts to date, DNA motif prediction in whole genome remains a challenge for researchers. Currently the genome wide motif prediction tools required either direct pattern sequence (for single motif) or weight matrix (for multiple motifs). Although there are known motif pattern databases and tools for genome level prediction but no tool for weight matrix construction. Considering this, we developed a D-MATRIX tool which predicts the different types of weight matrix based on user defined aligned motif sequence set and motif width. For retrieval of known motif sequences user can access the commonly used databases such as TFD, RegulonDB, DBTBS, Transfac. D-MATRIX program uses a simple statistical approach for weight matrix construction, which can be converted into different file formats according to user requirement. It provides the possibility to identify the conserved motifs in the co-regulated genes or whole genome. As example, we successfully constructed the weight matrix of LexA transcription factor binding site with the help of known sos-box cis-regulatory elements in Deinococcus radiodurans genome. The algorithm is implemented in C-Sharp and wrapped in ASP.Net to maintain a user friendly web interface. D-MATRIX tool is accessible through the CIMAP domain network. http://203.190.147.116/dmatrix/

A tutorial of diverse genome analysis tools found in the CoGe web-platform using Plasmodium spp. as a model

PubMed Central

Castillo, Andreina I; Nelson, Andrew D L; Haug-Baltzell, Asher K; Lyons, Eric

2018-01-01

Abstract Integrated platforms for storage, management, analysis and sharing of large quantities of omics data have become fundamental to comparative genomics. CoGe (https://genomevolution.org/coge/) is an online platform designed to manage and study genomic data, enabling both data- and hypothesis-driven comparative genomics. CoGe’s tools and resources can be used to organize and analyse both publicly available and private genomic data from any species. Here, we demonstrate the capabilities of CoGe through three example workflows using 17 Plasmodium genomes as a model. Plasmodium genomes present unique challenges for comparative genomics due to their rapidly evolving and highly variable genomic AT/GC content. These example workflows are intended to serve as templates to help guide researchers who would like to use CoGe to examine diverse aspects of genome evolution. In the first workflow, trends in genome composition and amino acid usage are explored. In the second, changes in genome structure and the distribution of synonymous (Ks) and non-synonymous (Kn) substitution values are evaluated across species with different levels of evolutionary relatedness. In the third workflow, microsyntenic analyses of multigene families’ genomic organization are conducted using two Plasmodium-specific gene families—serine repeat antigen, and cytoadherence-linked asexual gene—as models. In general, these example workflows show how to achieve quick, reproducible and shareable results using the CoGe platform. We were able to replicate previously published results, as well as leverage CoGe’s tools and resources to gain additional insight into various aspects of Plasmodium genome evolution. Our results highlight the usefulness of the CoGe platform, particularly in understanding complex features of genome evolution. Database URL: https://genomevolution.org/coge/

JBrowse: a dynamic web platform for genome visualization and analysis

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

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

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. 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. JBrowse is a maturemore » web application suitable for genome visualization and analysis.« less

JBrowse: a dynamic web platform for genome visualization and analysis.

PubMed

Buels, Robert; Yao, Eric; Diesh, Colin M; Hayes, Richard D; Munoz-Torres, Monica; Helt, Gregg; Goodstein, David M; Elsik, Christine G; Lewis, Suzanna E; Stein, Lincoln; Holmes, Ian H

2016-04-12

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. 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. JBrowse is a mature web application suitable for genome visualization and analysis.

Prediction of lipoprotein signal peptides in Gram-negative bacteria.

PubMed

Juncker, Agnieszka S; Willenbrock, Hanni; Von Heijne, Gunnar; Brunak, Søren; Nielsen, Henrik; Krogh, Anders

2003-08-01

A method to predict lipoprotein signal peptides in Gram-negative Eubacteria, LipoP, has been developed. The hidden Markov model (HMM) was able to distinguish between lipoproteins (SPaseII-cleaved proteins), SPaseI-cleaved proteins, cytoplasmic proteins, and transmembrane proteins. This predictor was able to predict 96.8% of the lipoproteins correctly with only 0.3% false positives in a set of SPaseI-cleaved, cytoplasmic, and transmembrane proteins. The results obtained were significantly better than those of previously developed methods. Even though Gram-positive lipoprotein signal peptides differ from Gram-negatives, the HMM was able to identify 92.9% of the lipoproteins included in a Gram-positive test set. A genome search was carried out for 12 Gram-negative genomes and one Gram-positive genome. The results for Escherichia coli K12 were compared with new experimental data, and the predictions by the HMM agree well with the experimentally verified lipoproteins. A neural network-based predictor was developed for comparison, and it gave very similar results. LipoP is available as a Web server at www.cbs.dtu.dk/services/LipoP/.

Prediction of lipoprotein signal peptides in Gram-negative bacteria

PubMed Central

Juncker, Agnieszka S.; Willenbrock, Hanni; von Heijne, Gunnar; Brunak, Søren; Nielsen, Henrik; Krogh, Anders

2003-01-01

A method to predict lipoprotein signal peptides in Gram-negative Eubacteria, LipoP, has been developed. The hidden Markov model (HMM) was able to distinguish between lipoproteins (SPaseII-cleaved proteins), SPaseI-cleaved proteins, cytoplasmic proteins, and transmembrane proteins. This predictor was able to predict 96.8% of the lipoproteins correctly with only 0.3% false positives in a set of SPaseI-cleaved, cytoplasmic, and transmembrane proteins. The results obtained were significantly better than those of previously developed methods. Even though Gram-positive lipoprotein signal peptides differ from Gram-negatives, the HMM was able to identify 92.9% of the lipoproteins included in a Gram-positive test set. A genome search was carried out for 12 Gram-negative genomes and one Gram-positive genome. The results for Escherichia coli K12 were compared with new experimental data, and the predictions by the HMM agree well with the experimentally verified lipoproteins. A neural network-based predictor was developed for comparison, and it gave very similar results. LipoP is available as a Web server at www.cbs.dtu.dk/services/LipoP/. PMID:12876315

The AraGWAS Catalog: a curated and standardized Arabidopsis thaliana GWAS catalog

PubMed Central

Togninalli, Matteo; Seren, Ümit; Meng, Dazhe; Fitz, Joffrey; Nordborg, Magnus; Weigel, Detlef

2018-01-01

Abstract The abundance of high-quality genotype and phenotype data for the model organism Arabidopsis thaliana enables scientists to study the genetic architecture of many complex traits at an unprecedented level of detail using genome-wide association studies (GWAS). GWAS have been a great success in A. thaliana and many SNP-trait associations have been published. With the AraGWAS Catalog (https://aragwas.1001genomes.org) we provide a publicly available, manually curated and standardized GWAS catalog for all publicly available phenotypes from the central A. thaliana phenotype repository, AraPheno. All GWAS have been recomputed on the latest imputed genotype release of the 1001 Genomes Consortium using a standardized GWAS pipeline to ensure comparability between results. The catalog includes currently 167 phenotypes and more than 222 000 SNP-trait associations with P < 10−4, of which 3887 are significantly associated using permutation-based thresholds. The AraGWAS Catalog can be accessed via a modern web-interface and provides various features to easily access, download and visualize the results and summary statistics across GWAS. PMID:29059333

WebaCGH: an interactive online tool for the analysis and display of array comparative genomic hybridisation data.

PubMed

Frankenberger, Casey; Wu, Xiaolin; Harmon, Jerry; Church, Deanna; Gangi, Lisa M; Munroe, David J; Urzúa, Ulises

2006-01-01

Gene copy number variations occur both in normal cells and in numerous pathologies including cancer and developmental diseases. Array comparative genomic hybridisation (aCGH) is an emerging technology that allows detection of chromosomal gains and losses in a high-resolution format. When aCGH is performed on cDNA and oligonucleotide microarrays, the impact of DNA copy number on gene transcription profiles may be directly compared. We have created an online software tool, WebaCGH, that functions to (i) upload aCGH and gene transcription results from multiple experiments; (ii) identify significant aberrant regions using a local Z-score threshold in user-selected chromosomal segments subjected to smoothing with moving averages; and (iii) display results in a graphical format with full genome and individual chromosome views. In the individual chromosome display, data can be zoomed in/out in both dimensions (i.e. ratio and physical location) and plotted features can have 'mouse over' linking to outside databases to identify loci of interest. Uploaded data can be stored indefinitely for subsequent retrieval and analysis. WebaCGH was created as a Java-based web application using the open-source database MySQL. WebaCGH is freely accessible at http://129.43.22.27/WebaCGH/welcome.htm Xiaolin Wu (forestwu@mail.nih.gov) or Ulises Urzúa (uurzua@med.uchile.cl).

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.

tRNAscan-SE On-line: integrating search and context for analysis of transfer RNA genes.

PubMed

Lowe, Todd M; Chan, Patricia P

2016-07-08

High-throughput genome sequencing continues to grow the need for rapid, accurate genome annotation and tRNA genes constitute the largest family of essential, ever-present non-coding RNA genes. Newly developed tRNAscan-SE 2.0 has advanced the state-of-the-art methodology in tRNA gene detection and functional prediction, captured by rich new content of the companion Genomic tRNA Database. Previously, web-server tRNA detection was isolated from knowledge of existing tRNAs and their annotation. In this update of the tRNAscan-SE On-line resource, we tie together improvements in tRNA classification with greatly enhanced biological context via dynamically generated links between web server search results, the most relevant genes in the GtRNAdb and interactive, rich genome context provided by UCSC genome browsers. The tRNAscan-SE On-line web server can be accessed at http://trna.ucsc.edu/tRNAscan-SE/. © The Author(s) 2016. Published by Oxford University Press on behalf of Nucleic Acids Research.

Struct2Net: a web service to predict protein–protein interactions using a structure-based approach

PubMed Central

Singh, Rohit; Park, Daniel; Xu, Jinbo; Hosur, Raghavendra; Berger, Bonnie

2010-01-01

Struct2Net is a web server for predicting interactions between arbitrary protein pairs using a structure-based approach. Prediction of protein–protein interactions (PPIs) is a central area of interest and successful prediction would provide leads for experiments and drug design; however, the experimental coverage of the PPI interactome remains inadequate. We believe that Struct2Net is the first community-wide resource to provide structure-based PPI predictions that go beyond homology modeling. Also, most web-resources for predicting PPIs currently rely on functional genomic data (e.g. GO annotation, gene expression, cellular localization, etc.). Our structure-based approach is independent of such methods and only requires the sequence information of the proteins being queried. The web service allows multiple querying options, aimed at maximizing flexibility. For the most commonly studied organisms (fly, human and yeast), predictions have been pre-computed and can be retrieved almost instantaneously. For proteins from other species, users have the option of getting a quick-but-approximate result (using orthology over pre-computed results) or having a full-blown computation performed. The web service is freely available at http://struct2net.csail.mit.edu. PMID:20513650

ClusterControl: a web interface for distributing and monitoring bioinformatics applications on a Linux cluster.

PubMed

Stocker, Gernot; Rieder, Dietmar; Trajanoski, Zlatko

2004-03-22

ClusterControl is a web interface to simplify distributing and monitoring bioinformatics applications on Linux cluster systems. We have developed a modular concept that enables integration of command line oriented program into the application framework of ClusterControl. The systems facilitate integration of different applications accessed through one interface and executed on a distributed cluster system. The package is based on freely available technologies like Apache as web server, PHP as server-side scripting language and OpenPBS as queuing system and is available free of charge for academic and non-profit institutions. http://genome.tugraz.at/Software/ClusterControl

DoD High Performance Computing Modernization Program Users Group Conference (HPCMP UGC 2011) Held in Portland, Oregon on June 20-23, 2011

DTIC Science & Technology

2011-06-01

4. Conclusion The Web -based AGeS system described in this paper is a computationally-efficient and scalable system for high- throughput genome...method for protecting web services involves making them more resilient to attack using autonomic computing techniques. This paper presents our initial...20–23, 2011 2011 DoD High Performance Computing Modernzation Program Users Group Conference HPCMP UGC 2011 The papers in this book comprise the

ASPIC: a novel method to predict the exon-intron structure of a gene that is optimally compatible to a set of transcript sequences.

PubMed

Bonizzoni, Paola; Rizzi, Raffaella; Pesole, Graziano

2005-10-05

Currently available methods to predict splice sites are mainly based on the independent and progressive alignment of transcript data (mostly ESTs) to the genomic sequence. Apart from often being computationally expensive, this approach is vulnerable to several problems--hence the need to develop novel strategies. We propose a method, based on a novel multiple genome-EST alignment algorithm, for the detection of splice sites. To avoid limitations of splice sites prediction (mainly, over-predictions) due to independent single EST alignments to the genomic sequence our approach performs a multiple alignment of transcript data to the genomic sequence based on the combined analysis of all available data. We recast the problem of predicting constitutive and alternative splicing as an optimization problem, where the optimal multiple transcript alignment minimizes the number of exons and hence of splice site observations. We have implemented a splice site predictor based on this algorithm in the software tool ASPIC (Alternative Splicing PredICtion). It is distinguished from other methods based on BLAST-like tools by the incorporation of entirely new ad hoc procedures for accurate and computationally efficient transcript alignment and adopts dynamic programming for the refinement of intron boundaries. ASPIC also provides the minimal set of non-mergeable transcript isoforms compatible with the detected splicing events. The ASPIC web resource is dynamically interconnected with the Ensembl and Unigene databases and also implements an upload facility. Extensive bench marking shows that ASPIC outperforms other existing methods in the detection of novel splicing isoforms and in the minimization of over-predictions. ASPIC also requires a lower computation time for processing a single gene and an EST cluster. The ASPIC web resource is available at http://aspic.algo.disco.unimib.it/aspic-devel/.

Listeriomics: an Interactive Web Platform for Systems Biology of Listeria

PubMed Central

Koutero, Mikael; Tchitchek, Nicolas; Cerutti, Franck; Lechat, Pierre; Maillet, Nicolas; Hoede, Claire; Chiapello, Hélène; Gaspin, Christine

2017-01-01

ABSTRACT As for many model organisms, the amount of Listeria omics data produced has recently increased exponentially. There are now >80 published complete Listeria genomes, around 350 different transcriptomic data sets, and 25 proteomic data sets available. The analysis of these data sets through a systems biology approach and the generation of tools for biologists to browse these various data are a challenge for bioinformaticians. We have developed a web-based platform, named Listeriomics, that integrates different tools for omics data analyses, i.e., (i) an interactive genome viewer to display gene expression arrays, tiling arrays, and sequencing data sets along with proteomics and genomics data sets; (ii) an expression and protein atlas that connects every gene, small RNA, antisense RNA, or protein with the most relevant omics data; (iii) a specific tool for exploring protein conservation through the Listeria phylogenomic tree; and (iv) a coexpression network tool for the discovery of potential new regulations. Our platform integrates all the complete Listeria species genomes, transcriptomes, and proteomes published to date. This website allows navigation among all these data sets with enriched metadata in a user-friendly format and can be used as a central database for systems biology analysis. IMPORTANCE In the last decades, Listeria has become a key model organism for the study of host-pathogen interactions, noncoding RNA regulation, and bacterial adaptation to stress. To study these mechanisms, several genomics, transcriptomics, and proteomics data sets have been produced. We have developed Listeriomics, an interactive web platform to browse and correlate these heterogeneous sources of information. Our website will allow listeriologists and microbiologists to decipher key regulation mechanism by using a systems biology approach. PMID:28317029

India Allele Finder: a web-based annotation tool for identifying common alleles in next-generation sequencing data of Indian origin.

PubMed

Zhang, Jimmy F; James, Francis; Shukla, Anju; Girisha, Katta M; Paciorkowski, Alex R

2017-06-27

We built India Allele Finder, an online searchable database and command line tool, that gives researchers access to variant frequencies of Indian Telugu individuals, using publicly available fastq data from the 1000 Genomes Project. Access to appropriate population-based genomic variant annotation can accelerate the interpretation of genomic sequencing data. In particular, exome analysis of individuals of Indian descent will identify population variants not reflected in European exomes, complicating genomic analysis for such individuals. India Allele Finder offers improved ease-of-use to investigators seeking to identify and annotate sequencing data from Indian populations. We describe the use of India Allele Finder to identify common population variants in a disease quartet whole exome dataset, reducing the number of candidate single nucleotide variants from 84 to 7. India Allele Finder is freely available to investigators to annotate genomic sequencing data from Indian populations. Use of India Allele Finder allows efficient identification of population variants in genomic sequencing data, and is an example of a population-specific annotation tool that simplifies analysis and encourages international collaboration in genomics research.

Fungal Genomics Program

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

Grigoriev, Igor

The JGI Fungal Genomics Program aims to scale up sequencing and analysis of fungal genomes to explore the diversity of fungi important for energy and the environment, and to promote functional studies on a system level. Combining new sequencing technologies and comparative genomics tools, JGI is now leading the world in fungal genome sequencing and analysis. Over 120 sequenced fungal genomes with analytical tools are available via MycoCosm (www.jgi.doe.gov/fungi), a web-portal for fungal biologists. Our model of interacting with user communities, unique among other sequencing centers, helps organize these communities, improves genome annotation and analysis work, and facilitates new larger-scalemore » genomic projects. This resulted in 20 high-profile papers published in 2011 alone and contributing to the Genomics Encyclopedia of Fungi, which targets fungi related to plant health (symbionts, pathogens, and biocontrol agents) and biorefinery processes (cellulose degradation, sugar fermentation, industrial hosts). Our next grand challenges include larger scale exploration of fungal diversity (1000 fungal genomes), developing molecular tools for DOE-relevant model organisms, and analysis of complex systems and metagenomes.« less

Establishment of expanded and streamlined pipeline of PITCh knock-in – a web-based design tool for MMEJ-mediated gene knock-in, PITCh designer, and the variations of PITCh, PITCh-TG and PITCh-KIKO

PubMed Central

Nakamae, Kazuki; Nishimura, Yuki; Takenaga, Mitsumasa; Sakamoto, Naoaki; Ide, Hiroshi; Sakuma, Tetsushi; Yamamoto, Takashi

2017-01-01

ABSTRACT The emerging genome editing technology has enabled the creation of gene knock-in cells easily, efficiently, and rapidly, which has dramatically accelerated research in the field of mammalian functional genomics, including in humans. We recently developed a microhomology-mediated end-joining-based gene knock-in method, termed the PITCh system, and presented various examples of its application. Since the PITCh system only requires very short microhomologies (up to 40 bp) and single-guide RNA target sites on the donor vector, the targeting construct can be rapidly prepared compared with the conventional targeting vector for homologous recombination-based knock-in. Here, we established a streamlined pipeline to design and perform PITCh knock-in to further expand the availability of this method by creating web-based design software, PITCh designer (http://www.mls.sci.hiroshima-u.ac.jp/smg/PITChdesigner/index.html), as well as presenting an experimental example of versatile gene cassette knock-in. PITCh designer can automatically design not only the appropriate microhomologies but also the primers to construct locus-specific donor vectors for PITCh knock-in. By using our newly established pipeline, a reporter cell line for monitoring endogenous gene expression, and transgenesis (TG) or knock-in/knockout (KIKO) cell line can be produced systematically. Using these new variations of PITCh, an exogenous promoter-driven gene cassette expressing fluorescent protein gene and drug resistance gene can be integrated into a safe harbor or a specific gene locus to create transgenic reporter cells (PITCh-TG) or knockout cells with reporter knock-in (PITCh-KIKO), respectively. PMID:28453368

Establishment of expanded and streamlined pipeline of PITCh knock-in - a web-based design tool for MMEJ-mediated gene knock-in, PITCh designer, and the variations of PITCh, PITCh-TG and PITCh-KIKO.

PubMed

Nakamae, Kazuki; Nishimura, Yuki; Takenaga, Mitsumasa; Nakade, Shota; Sakamoto, Naoaki; Ide, Hiroshi; Sakuma, Tetsushi; Yamamoto, Takashi

2017-05-04

The emerging genome editing technology has enabled the creation of gene knock-in cells easily, efficiently, and rapidly, which has dramatically accelerated research in the field of mammalian functional genomics, including in humans. We recently developed a microhomology-mediated end-joining-based gene knock-in method, termed the PITCh system, and presented various examples of its application. Since the PITCh system only requires very short microhomologies (up to 40 bp) and single-guide RNA target sites on the donor vector, the targeting construct can be rapidly prepared compared with the conventional targeting vector for homologous recombination-based knock-in. Here, we established a streamlined pipeline to design and perform PITCh knock-in to further expand the availability of this method by creating web-based design software, PITCh designer ( http://www.mls.sci.hiroshima-u.ac.jp/smg/PITChdesigner/index.html ), as well as presenting an experimental example of versatile gene cassette knock-in. PITCh designer can automatically design not only the appropriate microhomologies but also the primers to construct locus-specific donor vectors for PITCh knock-in. By using our newly established pipeline, a reporter cell line for monitoring endogenous gene expression, and transgenesis (TG) or knock-in/knockout (KIKO) cell line can be produced systematically. Using these new variations of PITCh, an exogenous promoter-driven gene cassette expressing fluorescent protein gene and drug resistance gene can be integrated into a safe harbor or a specific gene locus to create transgenic reporter cells (PITCh-TG) or knockout cells with reporter knock-in (PITCh-KIKO), respectively.

HC Forum®: a web site based on an international human cytogenetic database

PubMed Central

Cohen, Olivier; Mermet, Marie-Ange; Demongeot, Jacques

2001-01-01

Familial structural rearrangements of chromosomes represent a factor of malformation risk that could vary over a large range, making genetic counseling difficult. However, they also represent a powerful tool for increasing knowledge of the genome, particularly by studying breakpoints and viable imbalances of the genome. We have developed a collaborative database that now includes data on more than 4100 families, from which we have developed a web site called HC Forum® (http://HCForum.imag.fr). It offers geneticists assistance in diagnosis and in genetic counseling by assessing the malformation risk with statistical models. For researchers, interactive interfaces exhibit the distribution of chromosomal breakpoints and of the genome regions observed at birth in trisomy or in monosomy. Dedicated tools including an interactive pedigree allow electronic submission of data, which will be anonymously shown in a forum for discussions. After validation, data are definitively registered in the database with the email of the sender, allowing direct location of biological material. Thus HC Forum® constitutes a link between diagnosis laboratories and genome research centers, and after 1 year, more than 700 users from about 40 different countries already exist. PMID:11125121

Clinical software development for the Web: lessons learned from the BOADICEA project

PubMed Central

2012-01-01

Background In the past 20 years, society has witnessed the following landmark scientific advances: (i) the sequencing of the human genome, (ii) the distribution of software by the open source movement, and (iii) the invention of the World Wide Web. Together, these advances have provided a new impetus for clinical software development: developers now translate the products of human genomic research into clinical software tools; they use open-source programs to build them; and they use the Web to deliver them. Whilst this open-source component-based approach has undoubtedly made clinical software development easier, clinical software projects are still hampered by problems that traditionally accompany the software process. This study describes the development of the BOADICEA Web Application, a computer program used by clinical geneticists to assess risks to patients with a family history of breast and ovarian cancer. The key challenge of the BOADICEA Web Application project was to deliver a program that was safe, secure and easy for healthcare professionals to use. We focus on the software process, problems faced, and lessons learned. Our key objectives are: (i) to highlight key clinical software development issues; (ii) to demonstrate how software engineering tools and techniques can facilitate clinical software development for the benefit of individuals who lack software engineering expertise; and (iii) to provide a clinical software development case report that can be used as a basis for discussion at the start of future projects. Results We developed the BOADICEA Web Application using an evolutionary software process. Our approach to Web implementation was conservative and we used conventional software engineering tools and techniques. The principal software development activities were: requirements, design, implementation, testing, documentation and maintenance. The BOADICEA Web Application has now been widely adopted by clinical geneticists and researchers. BOADICEA Web Application version 1 was released for general use in November 2007. By May 2010, we had > 1200 registered users based in the UK, USA, Canada, South America, Europe, Africa, Middle East, SE Asia, Australia and New Zealand. Conclusions We found that an evolutionary software process was effective when we developed the BOADICEA Web Application. The key clinical software development issues identified during the BOADICEA Web Application project were: software reliability, Web security, clinical data protection and user feedback. PMID:22490389

Clinical software development for the Web: lessons learned from the BOADICEA project.

PubMed

Cunningham, Alex P; Antoniou, Antonis C; Easton, Douglas F

2012-04-10

In the past 20 years, society has witnessed the following landmark scientific advances: (i) the sequencing of the human genome, (ii) the distribution of software by the open source movement, and (iii) the invention of the World Wide Web. Together, these advances have provided a new impetus for clinical software development: developers now translate the products of human genomic research into clinical software tools; they use open-source programs to build them; and they use the Web to deliver them. Whilst this open-source component-based approach has undoubtedly made clinical software development easier, clinical software projects are still hampered by problems that traditionally accompany the software process. This study describes the development of the BOADICEA Web Application, a computer program used by clinical geneticists to assess risks to patients with a family history of breast and ovarian cancer. The key challenge of the BOADICEA Web Application project was to deliver a program that was safe, secure and easy for healthcare professionals to use. We focus on the software process, problems faced, and lessons learned. Our key objectives are: (i) to highlight key clinical software development issues; (ii) to demonstrate how software engineering tools and techniques can facilitate clinical software development for the benefit of individuals who lack software engineering expertise; and (iii) to provide a clinical software development case report that can be used as a basis for discussion at the start of future projects. We developed the BOADICEA Web Application using an evolutionary software process. Our approach to Web implementation was conservative and we used conventional software engineering tools and techniques. The principal software development activities were: requirements, design, implementation, testing, documentation and maintenance. The BOADICEA Web Application has now been widely adopted by clinical geneticists and researchers. BOADICEA Web Application version 1 was released for general use in November 2007. By May 2010, we had > 1200 registered users based in the UK, USA, Canada, South America, Europe, Africa, Middle East, SE Asia, Australia and New Zealand. We found that an evolutionary software process was effective when we developed the BOADICEA Web Application. The key clinical software development issues identified during the BOADICEA Web Application project were: software reliability, Web security, clinical data protection and user feedback.

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/.

Design, methods, and participant characteristics of the Impact of Personal Genomics (PGen) Study, a prospective cohort study of direct-to-consumer personal genomic testing customers.

PubMed

Carere, Deanna Alexis; Couper, Mick P; Crawford, Scott D; Kalia, Sarah S; Duggan, Jake R; Moreno, Tanya A; Mountain, Joanna L; Roberts, J Scott; Green, Robert C

2014-01-01

Designed in collaboration with 23andMe and Pathway Genomics, the Impact of Personal Genomics (PGen) Study serves as a model for academic-industry partnership and provides a longitudinal dataset for studying psychosocial, behavioral, and health outcomes related to direct-to-consumer personal genomic testing (PGT). Web-based surveys administered at three time points, and linked to individual-level PGT results, provide data on 1,464 PGT customers, of which 71% completed each follow-up survey and 64% completed all three surveys. The cohort includes 15.7% individuals of non-white ethnicity, and encompasses a range of income, education, and health levels. Over 90% of participants agreed to re-contact for future research.

Genome-wide prediction of vaccine targets for human herpes simplex viruses using Vaxign reverse vaccinology

PubMed Central

2013-01-01

Herpes simplex virus (HSV) types 1 and 2 (HSV-1 and HSV-2) are the most common infectious agents of humans. No safe and effective HSV vaccines have been licensed. Reverse vaccinology is an emerging and revolutionary vaccine development strategy that starts with the prediction of vaccine targets by informatics analysis of genome sequences. Vaxign (http://www.violinet.org/vaxign) is the first web-based vaccine design program based on reverse vaccinology. In this study, we used Vaxign to analyze 52 herpesvirus genomes, including 3 HSV-1 genomes, one HSV-2 genome, 8 other human herpesvirus genomes, and 40 non-human herpesvirus genomes. The HSV-1 strain 17 genome that contains 77 proteins was used as the seed genome. These 77 proteins are conserved in two other HSV-1 strains (strain F and strain H129). Two envelope glycoproteins gJ and gG do not have orthologs in HSV-2 or 8 other human herpesviruses. Seven HSV-1 proteins (including gJ and gG) do not have orthologs in all 40 non-human herpesviruses. Nineteen proteins are conserved in all human herpesviruses, including capsid scaffold protein UL26.5 (NP_044628.1). As the only HSV-1 protein predicted to be an adhesin, UL26.5 is a promising vaccine target. The MHC Class I and II epitopes were predicted by the Vaxign Vaxitop prediction program and IEDB prediction programs recently installed and incorporated in Vaxign. Our comparative analysis found that the two programs identified largely the same top epitopes but also some positive results predicted from one program might not be positive from another program. Overall, our Vaxign computational prediction provides many promising candidates for rational HSV vaccine development. The method is generic and can also be used to predict other viral vaccine targets. PMID:23514126

ZCURVE 3.0: identify prokaryotic genes with higher accuracy as well as automatically and accurately select essential genes.

PubMed

Hua, Zhi-Gang; Lin, Yan; Yuan, Ya-Zhou; Yang, De-Chang; Wei, Wen; Guo, Feng-Biao

2015-07-01

In 2003, we developed an ab initio program, ZCURVE 1.0, to find genes in bacterial and archaeal genomes. In this work, we present the updated version (i.e. ZCURVE 3.0). Using 422 prokaryotic genomes, the average accuracy was 93.7% with the updated version, compared with 88.7% with the original version. Such results also demonstrate that ZCURVE 3.0 is comparable with Glimmer 3.02 and may provide complementary predictions to it. In fact, the joint application of the two programs generated better results by correctly finding more annotated genes while also containing fewer false-positive predictions. As the exclusive function, ZCURVE 3.0 contains one post-processing program that can identify essential genes with high accuracy (generally >90%). We hope ZCURVE 3.0 will receive wide use with the web-based running mode. The updated ZCURVE can be freely accessed from http://cefg.uestc.edu.cn/zcurve/ or http://tubic.tju.edu.cn/zcurveb/ without any restrictions. © The Author(s) 2015. Published by Oxford University Press on behalf of Nucleic Acids Research.

Bioinformatics data distribution and integration via Web Services and XML.

PubMed

Li, Xiao; Zhang, Yizheng

2003-11-01

It is widely recognized that exchange, distribution, and integration of biological data are the keys to improve bioinformatics and genome biology in post-genomic era. However, the problem of exchanging and integrating biology data is not solved satisfactorily. The eXtensible Markup Language (XML) is rapidly spreading as an emerging standard for structuring documents to exchange and integrate data on the World Wide Web (WWW). Web service is the next generation of WWW and is founded upon the open standards of W3C (World Wide Web Consortium) and IETF (Internet Engineering Task Force). This paper presents XML and Web Services technologies and their use for an appropriate solution to the problem of bioinformatics data exchange and integration.

An advanced web query interface for biological databases

PubMed Central

Latendresse, Mario; Karp, Peter D.

2010-01-01

Although most web-based biological databases (DBs) offer some type of web-based form to allow users to author DB queries, these query forms are quite restricted in the complexity of DB queries that they can formulate. They can typically query only one DB, and can query only a single type of object at a time (e.g. genes) with no possible interaction between the objects—that is, in SQL parlance, no joins are allowed between DB objects. Writing precise queries against biological DBs is usually left to a programmer skillful enough in complex DB query languages like SQL. We present a web interface for building precise queries for biological DBs that can construct much more precise queries than most web-based query forms, yet that is user friendly enough to be used by biologists. It supports queries containing multiple conditions, and connecting multiple object types without using the join concept, which is unintuitive to biologists. This interactive web interface is called the Structured Advanced Query Page (SAQP). Users interactively build up a wide range of query constructs. Interactive documentation within the SAQP describes the schema of the queried DBs. The SAQP is based on BioVelo, a query language based on list comprehension. The SAQP is part of the Pathway Tools software and is available as part of several bioinformatics web sites powered by Pathway Tools, including the BioCyc.org site that contains more than 500 Pathway/Genome DBs. PMID:20624715

My46: a web-based tool for self-guided management of genomic test results in research and clinical settings

PubMed Central

Tabor, Holly K.; Jamal, Seema M.; Yu, Joon-Ho; Crouch, Julia M.; Shankar, Aditi G.; Dent, Karin M.; Anderson, Nick; Miller, Damon A.; Futral, Brett T.; Bamshad, Michael J.

2016-01-01

A major challenge to implementing precision medicine is the need for an efficient and cost-effective strategy for returning individual genomic test results that is easily scalable and can be incorporated into multiple models of clinical practice. My46 is a web-based tool for managing the return of genetic results that was designed and developed to support a wide range of approaches to results disclosure, ranging from traditional face-to-face disclosure to self-guided models. My46 has five key functions: set and modify results return preferences, return results, educate, manage return of results, and assess return of results. These key functions are supported by six distinct modules and a suite of features that enhance the user experience, ease site navigation, facilitate knowledge sharing, and enable results return tracking. My46 is a potentially effective solution for returning results and supports current trends toward shared decision-making between patient and provider and patient-driven health management. PMID:27632689

Prediction of individualized therapeutic vulnerabilities in cancer from genomic profiles

PubMed Central

Aksoy, Bülent Arman; Demir, Emek; Babur, Özgün; Wang, Weiqing; Jing, Xiaohong; Schultz, Nikolaus; Sander, Chris

2014-01-01

Motivation: Somatic homozygous deletions of chromosomal regions in cancer, while not necessarily oncogenic, may lead to therapeutic vulnerabilities specific to cancer cells compared with normal cells. A recently reported example is the loss of one of the two isoenzymes in glioblastoma cancer cells such that the use of a specific inhibitor selectively inhibited growth of the cancer cells, which had become fully dependent on the second isoenzyme. We have now made use of the unprecedented conjunction of large-scale cancer genomics profiling of tumor samples in The Cancer Genome Atlas (TCGA) and of tumor-derived cell lines in the Cancer Cell Line Encyclopedia, as well as the availability of integrated pathway information systems, such as Pathway Commons, to systematically search for a comprehensive set of such epistatic vulnerabilities. Results: Based on homozygous deletions affecting metabolic enzymes in 16 TCGA cancer studies and 972 cancer cell lines, we identified 4104 candidate metabolic vulnerabilities present in 1019 tumor samples and 482 cell lines. Up to 44% of these vulnerabilities can be targeted with at least one Food and Drug Administration-approved drug. We suggest focused experiments to test these vulnerabilities and clinical trials based on personalized genomic profiles of those that pass preclinical filters. We conclude that genomic profiling will in the future provide a promising basis for network pharmacology of epistatic vulnerabilities as a promising therapeutic strategy. Availability and implementation: A web-based tool for exploring all vulnerabilities and their details is available at http://cbio.mskcc.org/cancergenomics/statius/ along with supplemental data files. Contact: statius@cbio.mskcc.org Supplementary information: Supplementary data are available at Bioinformatics online. PMID:24665131

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

RICD: a rice indica cDNA database resource for rice functional genomics.

PubMed

Lu, Tingting; Huang, Xuehui; Zhu, Chuanrang; Huang, Tao; Zhao, Qiang; Xie, Kabing; Xiong, Lizhong; Zhang, Qifa; Han, Bin

2008-11-26

The Oryza sativa L. indica subspecies is the most widely cultivated rice. During the last few years, we have collected over 20,000 putative full-length cDNAs and over 40,000 ESTs isolated from various cDNA libraries of two indica varieties Guangluai 4 and Minghui 63. A database of the rice indica cDNAs was therefore built to provide a comprehensive web data source for searching and retrieving the indica cDNA clones. Rice Indica cDNA Database (RICD) is an online MySQL-PHP driven database with a user-friendly web interface. It allows investigators to query the cDNA clones by keyword, genome position, nucleotide or protein sequence, and putative function. It also provides a series of information, including sequences, protein domain annotations, similarity search results, SNPs and InDels information, and hyperlinks to gene annotation in both The Rice Annotation Project Database (RAP-DB) and The TIGR Rice Genome Annotation Resource, expression atlas in RiceGE and variation report in Gramene of each cDNA. The online rice indica cDNA database provides cDNA resource with comprehensive information to researchers for functional analysis of indica subspecies and for comparative genomics. The RICD database is available through our website http://www.ncgr.ac.cn/ricd.

ClinGen Pathogenicity Calculator: a configurable system for assessing pathogenicity of genetic variants.

PubMed

Patel, Ronak Y; Shah, Neethu; Jackson, Andrew R; Ghosh, Rajarshi; Pawliczek, Piotr; Paithankar, Sameer; Baker, Aaron; Riehle, Kevin; Chen, Hailin; Milosavljevic, Sofia; Bizon, Chris; Rynearson, Shawn; Nelson, Tristan; Jarvik, Gail P; Rehm, Heidi L; Harrison, Steven M; Azzariti, Danielle; Powell, Bradford; Babb, Larry; Plon, Sharon E; Milosavljevic, Aleksandar

2017-01-12

The success of the clinical use of sequencing based tests (from single gene to genomes) depends on the accuracy and consistency of variant interpretation. Aiming to improve the interpretation process through practice guidelines, the American College of Medical Genetics and Genomics (ACMG) and the Association for Molecular Pathology (AMP) have published standards and guidelines for the interpretation of sequence variants. However, manual application of the guidelines is tedious and prone to human error. Web-based tools and software systems may not only address this problem but also document reasoning and supporting evidence, thus enabling transparency of evidence-based reasoning and resolution of discordant interpretations. In this report, we describe the design, implementation, and initial testing of the Clinical Genome Resource (ClinGen) Pathogenicity Calculator, a configurable system and web service for the assessment of pathogenicity of Mendelian germline sequence variants. The system allows users to enter the applicable ACMG/AMP-style evidence tags for a specific allele with links to supporting data for each tag and generate guideline-based pathogenicity assessment for the allele. Through automation and comprehensive documentation of evidence codes, the system facilitates more accurate application of the ACMG/AMP guidelines, improves standardization in variant classification, and facilitates collaborative resolution of discordances. The rules of reasoning are configurable with gene-specific or disease-specific guideline variations (e.g. cardiomyopathy-specific frequency thresholds and functional assays). The software is modular, equipped with robust application program interfaces (APIs), and available under a free open source license and as a cloud-hosted web service, thus facilitating both stand-alone use and integration with existing variant curation and interpretation systems. The Pathogenicity Calculator is accessible at http://calculator.clinicalgenome.org . By enabling evidence-based reasoning about the pathogenicity of genetic variants and by documenting supporting evidence, the Calculator contributes toward the creation of a knowledge commons and more accurate interpretation of sequence variants in research and clinical care.

GenomeHubs: simple containerized setup of a custom Ensembl database and web server for any species

PubMed Central

Kumar, Sujai; Stevens, Lewis; Blaxter, Mark

2017-01-01

Abstract As the generation and use of genomic datasets is becoming increasingly common in all areas of biology, the need for resources to collate, analyse and present data from one or more genome projects is becoming more pressing. The Ensembl platform is a powerful tool to make genome data and cross-species analyses easily accessible through a web interface and a comprehensive application programming interface. Here we introduce GenomeHubs, which provide a containerized environment to facilitate the setup and hosting of custom Ensembl genome browsers. This simplifies mirroring of existing content and import of new genomic data into the Ensembl database schema. GenomeHubs also provide a set of analysis containers to decorate imported genomes with results of standard analyses and functional annotations and support export to flat files, including EMBL format for submission of assemblies and annotations to International Nucleotide Sequence Database Collaboration. Database URL: http://GenomeHubs.org PMID:28605774

Gene calling and bacterial genome annotation with BG7.

PubMed

Tobes, Raquel; Pareja-Tobes, Pablo; Manrique, Marina; Pareja-Tobes, Eduardo; Kovach, Evdokim; Alekhin, Alexey; Pareja, Eduardo

2015-01-01

New massive sequencing technologies are providing many bacterial genome sequences from diverse taxa but a refined annotation of these genomes is crucial for obtaining scientific findings and new knowledge. Thus, bacterial genome annotation has emerged as a key point to investigate in bacteria. Any efficient tool designed specifically to annotate bacterial genomes sequenced with massively parallel technologies has to consider the specific features of bacterial genomes (absence of introns and scarcity of nonprotein-coding sequence) and of next-generation sequencing (NGS) technologies (presence of errors and not perfectly assembled genomes). These features make it convenient to focus on coding regions and, hence, on protein sequences that are the elements directly related with biological functions. In this chapter we describe how to annotate bacterial genomes with BG7, an open-source tool based on a protein-centered gene calling/annotation paradigm. BG7 is specifically designed for the annotation of bacterial genomes sequenced with NGS. This tool is sequence error tolerant maintaining their capabilities for the annotation of highly fragmented genomes or for annotating mixed sequences coming from several genomes (as those obtained through metagenomics samples). BG7 has been designed with scalability as a requirement, with a computing infrastructure completely based on cloud computing (Amazon Web Services).

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 .

Resolving the problem of multiple accessions of the same transcript deposited across various public databases.

PubMed

Weirick, Tyler; John, David; Uchida, Shizuka

2017-03-01

Maintaining the consistency of genomic annotations is an increasingly complex task because of the iterative and dynamic nature of assembly and annotation, growing numbers of biological databases and insufficient integration of annotations across databases. As information exchange among databases is poor, a 'novel' sequence from one reference annotation could be annotated in another. Furthermore, relationships to nearby or overlapping annotated transcripts are even more complicated when using different genome assemblies. To better understand these problems, we surveyed current and previous versions of genomic assemblies and annotations across a number of public databases containing long noncoding RNA. We identified numerous discrepancies of transcripts regarding their genomic locations, transcript lengths and identifiers. Further investigation showed that the positional differences between reference annotations of essentially the same transcript could lead to differences in its measured expression at the RNA level. To aid in resolving these problems, we present the algorithm 'Universal Genomic Accession Hash (UGAHash)' and created an open source web tool to encourage the usage of the UGAHash algorithm. The UGAHash web tool (http://ugahash.uni-frankfurt.de) can be accessed freely without registration. The web tool allows researchers to generate Universal Genomic Accessions for genomic features or to explore annotations deposited in the public databases of the past and present versions. We anticipate that the UGAHash web tool will be a valuable tool to check for the existence of transcripts before judging the newly discovered transcripts as novel. © The Author 2016. Published by Oxford University Press. For Permissions, please email: journals.permissions@oup.com.

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.

TnpPred: A Web Service for the Robust Prediction of Prokaryotic Transposases

PubMed Central

Riadi, Gonzalo; Medina-Moenne, Cristobal; Holmes, David S.

2012-01-01

Transposases (Tnps) are enzymes that participate in the movement of insertion sequences (ISs) within and between genomes. Genes that encode Tnps are amongst the most abundant and widely distributed genes in nature. However, they are difficult to predict bioinformatically and given the increasing availability of prokaryotic genomes and metagenomes, it is incumbent to develop rapid, high quality automatic annotation of ISs. This need prompted us to develop a web service, termed TnpPred for Tnp discovery. It provides better sensitivity and specificity for Tnp predictions than given by currently available programs as determined by ROC analysis. TnpPred should be useful for improving genome annotation. The TnpPred web service is freely available for noncommercial use. PMID:23251097

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

Lynx web services for annotations and systems analysis of multi-gene disorders.

PubMed

Sulakhe, Dinanath; Taylor, Andrew; Balasubramanian, Sandhya; Feng, Bo; Xie, Bingqing; Börnigen, Daniela; Dave, Utpal J; Foster, Ian T; Gilliam, T Conrad; Maltsev, Natalia

2014-07-01

Lynx is a web-based integrated systems biology platform that supports annotation and analysis of experimental data and generation of weighted hypotheses on molecular mechanisms contributing to human phenotypes and disorders of interest. Lynx has integrated multiple classes of biomedical data (genomic, proteomic, pathways, phenotypic, toxicogenomic, contextual and others) from various public databases as well as manually curated data from our group and collaborators (LynxKB). Lynx provides tools for gene list enrichment analysis using multiple functional annotations and network-based gene prioritization. Lynx provides access to the integrated database and the analytical tools via REST based Web Services (http://lynx.ci.uchicago.edu/webservices.html). This comprises data retrieval services for specific functional annotations, services to search across the complete LynxKB (powered by Lucene), and services to access the analytical tools built within the Lynx platform. © The Author(s) 2014. Published by Oxford University Press on behalf of Nucleic Acids Research.

Citrus sinensis annotation project (CAP): a comprehensive database for sweet orange genome.

PubMed

Wang, Jia; Chen, Dijun; Lei, Yang; Chang, Ji-Wei; Hao, Bao-Hai; Xing, Feng; Li, Sen; Xu, Qiang; Deng, Xiu-Xin; Chen, Ling-Ling

2014-01-01

Citrus is one of the most important and widely grown fruit crop with global production ranking firstly among all the fruit crops in the world. Sweet orange accounts for more than half of the Citrus production both in fresh fruit and processed juice. We have sequenced the draft genome of a double-haploid sweet orange (C. sinensis cv. Valencia), and constructed the Citrus sinensis annotation project (CAP) to store and visualize the sequenced genomic and transcriptome data. CAP provides GBrowse-based organization of sweet orange genomic data, which integrates ab initio gene prediction, EST, RNA-seq and RNA-paired end tag (RNA-PET) evidence-based gene annotation. Furthermore, we provide a user-friendly web interface to show the predicted protein-protein interactions (PPIs) and metabolic pathways in sweet orange. CAP provides comprehensive information beneficial to the researchers of sweet orange and other woody plants, which is freely available at http://citrus.hzau.edu.cn/.

Live and Web-based orientations are comparable for a required rotation.

PubMed

Prunuske, Jacob

2010-03-01

Studies show equivalency in knowledge when measured following Web-based learning and live lecture. However, the effectiveness of a Web-based orientation for a required clinical rotation is unknown. Medical students viewed a Web-based orientation and completed a 13-item evaluation before beginning a required 6-week community medicine rotation. Evaluation data from 2007-2008 live orientation sessions were compared to responses from 2008-2009 Web-based orientation sessions. Data were analyzed by two-sample tests of proportion. A total of 169 students completed surveys during the study period--78 following the live and 91 following the Web-based orientation. Response rates were equal in the two groups. The survey tool had a high level of reliability (Cronbach's alpha=0.96). There was no statistical difference in student evaluations for 12 of 13 orientation evaluation items. Live and Web-based formats are comparable for presenting orientation materials to a required clinical rotation. Students felt the purpose of the rotation, educational goals, course structure, and requirements were clearly presented regardless of format. Transition from a live to Web-based format reduced faculty time required to present at rotation orientations.

An integrative approach to energy, carbon, and redox metabolism in the cyanobacterium Synechocystis sp. PCC 6803

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

Overbeek, Ross; Fonstein, Veronika; Osterman, Andrei

2005-02-15

The team of the Fellowship for Interpretation of Genomes (FIG) under the leadership of Ross Overbeek, began working on this Project in November 2003. During the previous year, the Project was performed at Integrated Genomics Inc. A transition from the industrial environment to the public domain prompted us to adjust some aspects of the Project. Notwithstanding the challenges, we believe that these adjustments had a strong positive impact on our deliverables. Most importantly, the work of the research team led by R. Overbeek resulted in the deployment of a new open source genomic platform, the SEED (Specific Aim 1). Thismore » platform provided a foundation for the development of CyanoSEED a specialized portal to comparative analysis and metabolic reconstruction of all available cyanobacterial genomes (Specific Aim 3). The SEED represents a new generation of software for genome analysis. Briefly, it is a portable and extendable system, containing one of the largest and permanently growing collections of complete and partial genomes. The complete system with annotations and tools is freely available via browsing or via installation on a user's Mac or Linux computer. One of the important unique features of the SEED is the support of metabolic reconstruction and comparative genome analysis via encoding and projection of functional subsystems. During the project period, the FIG research team has validated the new software by developing a significant number of core subsystems, covering many aspects of central metabolism (Specific Aim 2), as well as metabolic areas specific for cyanobacteria and other photoautotrophic organisms (Specific Aim 3). In addition to providing a proof of technology and a starting point for further community-based efforts, these subsystems represent a valuable asset. An extensive coverage of central metabolism provides the bulk of information required for metabolic modeling in Synechocystis sp.PCC 6803. Detailed analysis of several subsystems covering energy, carbon, and redox metabolism in the Synechocystis sp. PCC 6803 and other cyanobacteria has been performed (Specific Aim 4). The main objectives for this year (adjusted to reflect a new, public domain, setting of the Project research team) were: Aim 1. To develop, test, and deploy a new open source system, the SEED, for integrating community-based annotation, and comparative analysis of all publicly available microbial genomes. Develop a comprehensive genomic database by integrating within SEED all publicly available complete and nearly complete genome sequences with special emphasis on genomes of cyanobacteria, phototrophic eukaryotes, and anoxygenic phototrophic bacteria--invaluable for comparative genomic studies of energy and carbon metabolism in Synechocystis sp. PCC 6803. Aim 2. To develop the SEED's biological content in the form of a collection of encoded Subsystems largely covering the conserved cellular machinery in prokaryotes (and central metabolic machinery in eukaryotes). Aim 3. To develop, utilizing core SEED technology, the CyanoSEED--a specialized WEB portal for community-based annotation, and comparative analysis of all publicly available cyanobacterial genomes. Encode the set of additional subsystems representing key metabolic transformations in cyanobacteria and other photoautotrophs. We envisioned this resource as complementary to other public access databases for comparative genomic analysis currently available to the cyanobacterial research community. Aim 4. Perform in-depth analysis of several subsystems covering energy, carbon, and redox metabolism in the Synechocystis sp. PCC 6803 and all other cyanobacteria with available genome sequences. Reveal inconsistencies and gaps in the current knowledge of these subsystems. Use functional and genome context analysis tools in CyanoSEED to predict, whenever possible, candidate genes for inferred functional roles. To disseminate freely these conjectures and predictions by publishing them on CyanoSEED (http://cyanoseed.thefig.info/) and the Subsystems Forum (http://brucella.uchicago.edu/SubsystemForum/) in order to facilitate experimental analysis by our collaborator on this Project and by other experimentalists working in various field of cyanobacterial physiology and biotechnology.« less

Recognition of Protein-coding Genes Based on Z-curve Algorithms

PubMed Central

-Biao Guo, Feng; Lin, Yan; -Ling Chen, Ling

2014-01-01

Recognition of protein-coding genes, a classical bioinformatics issue, is an absolutely needed step for annotating newly sequenced genomes. The Z-curve algorithm, as one of the most effective methods on this issue, has been successfully applied in annotating or re-annotating many genomes, including those of bacteria, archaea and viruses. Two Z-curve based ab initio gene-finding programs have been developed: ZCURVE (for bacteria and archaea) and ZCURVE_V (for viruses and phages). ZCURVE_C (for 57 bacteria) and Zfisher (for any bacterium) are web servers for re-annotation of bacterial and archaeal genomes. The above four tools can be used for genome annotation or re-annotation, either independently or combined with the other gene-finding programs. In addition to recognizing protein-coding genes and exons, Z-curve algorithms are also effective in recognizing promoters and translation start sites. Here, we summarize the applications of Z-curve algorithms in gene finding and genome annotation. PMID:24822027

MicroScope in 2017: an expanding and evolving integrated resource for community expertise of microbial genomes.

PubMed

Vallenet, David; Calteau, Alexandra; Cruveiller, Stéphane; Gachet, Mathieu; Lajus, Aurélie; Josso, Adrien; Mercier, Jonathan; Renaux, Alexandre; Rollin, Johan; Rouy, Zoe; Roche, David; Scarpelli, Claude; Médigue, Claudine

2017-01-04

The annotation of genomes from NGS platforms needs to be automated and fully integrated. However, maintaining consistency and accuracy in genome annotation is a challenging problem because millions of protein database entries are not assigned reliable functions. This shortcoming limits the knowledge that can be extracted from genomes and metabolic models. Launched in 2005, the MicroScope platform (http://www.genoscope.cns.fr/agc/microscope) is an integrative resource that supports systematic and efficient revision of microbial genome annotation, data management and comparative analysis. Effective comparative analysis requires a consistent and complete view of biological data, and therefore, support for reviewing the quality of functional annotation is critical. MicroScope allows users to analyze microbial (meta)genomes together with post-genomic experiment results if any (i.e. transcriptomics, re-sequencing of evolved strains, mutant collections, phenotype data). It combines tools and graphical interfaces to analyze genomes and to perform the expert curation of gene functions in a comparative context. Starting with a short overview of the MicroScope system, this paper focuses on some major improvements of the Web interface, mainly for the submission of genomic data and on original tools and pipelines that have been developed and integrated in the platform: computation of pan-genomes and prediction of biosynthetic gene clusters. Today the resource contains data for more than 6000 microbial genomes, and among the 2700 personal accounts (65% of which are now from foreign countries), 14% of the users are performing expert annotations, on at least a weekly basis, contributing to improve the quality of microbial genome annotations. © The Author(s) 2016. Published by Oxford University Press on behalf of Nucleic Acids Research.

Nuclease Target Site Selection for Maximizing On-target Activity and Minimizing Off-target Effects in Genome Editing

PubMed Central

Lee, Ciaran M; Cradick, Thomas J; Fine, Eli J; Bao, Gang

2016-01-01

The rapid advancement in targeted genome editing using engineered nucleases such as ZFNs, TALENs, and CRISPR/Cas9 systems has resulted in a suite of powerful methods that allows researchers to target any genomic locus of interest. A complementary set of design tools has been developed to aid researchers with nuclease design, target site selection, and experimental validation. Here, we review the various tools available for target selection in designing engineered nucleases, and for quantifying nuclease activity and specificity, including web-based search tools and experimental methods. We also elucidate challenges in target selection, especially in predicting off-target effects, and discuss future directions in precision genome editing and its applications. PMID:26750397

GEM-TREND: a web tool for gene expression data mining toward relevant network discovery

PubMed Central

Feng, Chunlai; Araki, Michihiro; Kunimoto, Ryo; Tamon, Akiko; Makiguchi, Hiroki; Niijima, Satoshi; Tsujimoto, Gozoh; Okuno, Yasushi

2009-01-01

Background DNA microarray technology provides us with a first step toward the goal of uncovering gene functions on a genomic scale. In recent years, vast amounts of gene expression data have been collected, much of which are available in public databases, such as the Gene Expression Omnibus (GEO). To date, most researchers have been manually retrieving data from databases through web browsers using accession numbers (IDs) or keywords, but gene-expression patterns are not considered when retrieving such data. The Connectivity Map was recently introduced to compare gene expression data by introducing gene-expression signatures (represented by a set of genes with up- or down-regulated labels according to their biological states) and is available as a web tool for detecting similar gene-expression signatures from a limited data set (approximately 7,000 expression profiles representing 1,309 compounds). In order to support researchers to utilize the public gene expression data more effectively, we developed a web tool for finding similar gene expression data and generating its co-expression networks from a publicly available database. Results GEM-TREND, a web tool for searching gene expression data, allows users to search data from GEO using gene-expression signatures or gene expression ratio data as a query and retrieve gene expression data by comparing gene-expression pattern between the query and GEO gene expression data. The comparison methods are based on the nonparametric, rank-based pattern matching approach of Lamb et al. (Science 2006) with the additional calculation of statistical significance. The web tool was tested using gene expression ratio data randomly extracted from the GEO and with in-house microarray data, respectively. The results validated the ability of GEM-TREND to retrieve gene expression entries biologically related to a query from GEO. For further analysis, a network visualization interface is also provided, whereby genes and gene annotations are dynamically linked to external data repositories. Conclusion GEM-TREND was developed to retrieve gene expression data by comparing query gene-expression pattern with those of GEO gene expression data. It could be a very useful resource for finding similar gene expression profiles and constructing its gene co-expression networks from a publicly available database. GEM-TREND was designed to be user-friendly and is expected to support knowledge discovery. GEM-TREND is freely available at . PMID:19728865

GEM-TREND: a web tool for gene expression data mining toward relevant network discovery.

PubMed

Feng, Chunlai; Araki, Michihiro; Kunimoto, Ryo; Tamon, Akiko; Makiguchi, Hiroki; Niijima, Satoshi; Tsujimoto, Gozoh; Okuno, Yasushi

2009-09-03

DNA microarray technology provides us with a first step toward the goal of uncovering gene functions on a genomic scale. In recent years, vast amounts of gene expression data have been collected, much of which are available in public databases, such as the Gene Expression Omnibus (GEO). To date, most researchers have been manually retrieving data from databases through web browsers using accession numbers (IDs) or keywords, but gene-expression patterns are not considered when retrieving such data. The Connectivity Map was recently introduced to compare gene expression data by introducing gene-expression signatures (represented by a set of genes with up- or down-regulated labels according to their biological states) and is available as a web tool for detecting similar gene-expression signatures from a limited data set (approximately 7,000 expression profiles representing 1,309 compounds). In order to support researchers to utilize the public gene expression data more effectively, we developed a web tool for finding similar gene expression data and generating its co-expression networks from a publicly available database. GEM-TREND, a web tool for searching gene expression data, allows users to search data from GEO using gene-expression signatures or gene expression ratio data as a query and retrieve gene expression data by comparing gene-expression pattern between the query and GEO gene expression data. The comparison methods are based on the nonparametric, rank-based pattern matching approach of Lamb et al. (Science 2006) with the additional calculation of statistical significance. The web tool was tested using gene expression ratio data randomly extracted from the GEO and with in-house microarray data, respectively. The results validated the ability of GEM-TREND to retrieve gene expression entries biologically related to a query from GEO. For further analysis, a network visualization interface is also provided, whereby genes and gene annotations are dynamically linked to external data repositories. GEM-TREND was developed to retrieve gene expression data by comparing query gene-expression pattern with those of GEO gene expression data. It could be a very useful resource for finding similar gene expression profiles and constructing its gene co-expression networks from a publicly available database. GEM-TREND was designed to be user-friendly and is expected to support knowledge discovery. GEM-TREND is freely available at http://cgs.pharm.kyoto-u.ac.jp/services/network.

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.

Cloning, analysis and functional annotation of expressed sequence tags from the Earthworm Eisenia fetida

PubMed Central

Pirooznia, Mehdi; Gong, Ping; Guan, Xin; Inouye, Laura S; Yang, Kuan; Perkins, Edward J; Deng, Youping

2007-01-01

Background Eisenia fetida, commonly known as red wiggler or compost worm, belongs to the Lumbricidae family of the Annelida phylum. Little is known about its genome sequence although it has been extensively used as a test organism in terrestrial ecotoxicology. In order to understand its gene expression response to environmental contaminants, we cloned 4032 cDNAs or expressed sequence tags (ESTs) from two E. fetida libraries enriched with genes responsive to ten ordnance related compounds using suppressive subtractive hybridization-PCR. Results A total of 3144 good quality ESTs (GenBank dbEST accession number EH669363–EH672369 and EL515444–EL515580) were obtained from the raw clone sequences after cleaning. Clustering analysis yielded 2231 unique sequences including 448 contigs (from 1361 ESTs) and 1783 singletons. Comparative genomic analysis showed that 743 or 33% of the unique sequences shared high similarity with existing genes in the GenBank nr database. Provisional function annotation assigned 830 Gene Ontology terms to 517 unique sequences based on their homology with the annotated genomes of four model organisms Drosophila melanogaster, Mus musculus, Saccharomyces cerevisiae, and Caenorhabditis elegans. Seven percent of the unique sequences were further mapped to 99 Kyoto Encyclopedia of Genes and Genomes pathways based on their matching Enzyme Commission numbers. All the information is stored and retrievable at a highly performed, web-based and user-friendly relational database called EST model database or ESTMD version 2. Conclusion The ESTMD containing the sequence and annotation information of 4032 E. fetida ESTs is publicly accessible at . PMID:18047730

Optimized gene editing technology for Drosophila melanogaster using germ line-specific Cas9.

PubMed

Ren, Xingjie; Sun, Jin; Housden, Benjamin E; Hu, Yanhui; Roesel, Charles; Lin, Shuailiang; Liu, Lu-Ping; Yang, Zhihao; Mao, Decai; Sun, Lingzhu; Wu, Qujie; Ji, Jun-Yuan; Xi, Jianzhong; Mohr, Stephanie E; Xu, Jiang; Perrimon, Norbert; Ni, Jian-Quan

2013-11-19

The ability to engineer genomes in a specific, systematic, and cost-effective way is critical for functional genomic studies. Recent advances using the CRISPR-associated single-guide RNA system (Cas9/sgRNA) illustrate the potential of this simple system for genome engineering in a number of organisms. Here we report an effective and inexpensive method for genome DNA editing in Drosophila melanogaster whereby plasmid DNAs encoding short sgRNAs under the control of the U6b promoter are injected into transgenic flies in which Cas9 is specifically expressed in the germ line via the nanos promoter. We evaluate the off-targets associated with the method and establish a Web-based resource, along with a searchable, genome-wide database of predicted sgRNAs appropriate for genome engineering in flies. Finally, we discuss the advantages of our method in comparison with other recently published approaches.

Genetic counselling in the era of genomic medicine

PubMed Central

Middleton, Anna

2018-01-01

Abstract Background Genomic technology can now deliver cost effective, targeted diagnosis and treatment for patients. Genetic counselling is a communication process empowering patients and families to make autonomous decisions and effectively use new genetic information. The skills of genetic counselling and expertise of genetic counsellors are integral to the effective implementation of genomic medicine. Sources of data Original papers, reviews, guidelines, policy papers and web-resources. Areas of agreement An international consensus on the definition of genetic counselling. Genetic counselling is necessary for implementation of genomic medicine. Areas of controversy Models of genetic counselling. Growing points Genomic medicine is a growing and strategic priority for many health care systems. Genetic counselling is part of this. Areas timely for developing research An evidence base is necessary, incorporating implementation and outcome research, to enable health care systems, practitioners, patients and families to maximize the utility (medically and psychologically) of the new genomic possibilities. PMID:29617718

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

WordCluster: detecting clusters of DNA words and genomic elements

PubMed Central

2011-01-01

Background Many k-mers (or DNA words) and genomic elements are known to be spatially clustered in the genome. Well established examples are the genes, TFBSs, CpG dinucleotides, microRNA genes and ultra-conserved non-coding regions. Currently, no algorithm exists to find these clusters in a statistically comprehensible way. The detection of clustering often relies on densities and sliding-window approaches or arbitrarily chosen distance thresholds. Results We introduce here an algorithm to detect clusters of DNA words (k-mers), or any other genomic element, based on the distance between consecutive copies and an assigned statistical significance. We implemented the method into a web server connected to a MySQL backend, which also determines the co-localization with gene annotations. We demonstrate the usefulness of this approach by detecting the clusters of CAG/CTG (cytosine contexts that can be methylated in undifferentiated cells), showing that the degree of methylation vary drastically between inside and outside of the clusters. As another example, we used WordCluster to search for statistically significant clusters of olfactory receptor (OR) genes in the human genome. Conclusions WordCluster seems to predict biological meaningful clusters of DNA words (k-mers) and genomic entities. The implementation of the method into a web server is available at http://bioinfo2.ugr.es/wordCluster/wordCluster.php including additional features like the detection of co-localization with gene regions or the annotation enrichment tool for functional analysis of overlapped genes. PMID:21261981

ContEst16S: an algorithm that identifies contaminated prokaryotic genomes using 16S RNA gene sequences.

PubMed

Lee, Imchang; Chalita, Mauricio; Ha, Sung-Min; Na, Seong-In; Yoon, Seok-Hwan; Chun, Jongsik

2017-06-01

Thanks to the recent advancement of DNA sequencing technology, the cost and time of prokaryotic genome sequencing have been dramatically decreased. It has repeatedly been reported that genome sequencing using high-throughput next-generation sequencing is prone to contaminations due to its high depth of sequencing coverage. Although a few bioinformatics tools are available to detect potential contaminations, these have inherited limitations as they only use protein-coding genes. Here we introduce a new algorithm, called ContEst16S, to detect potential contaminations using 16S rRNA genes from genome assemblies. We screened 69 745 prokaryotic genomes from the NCBI Assembly Database using ContEst16S and found that 594 were contaminated by bacteria, human and plants. Of the predicted contaminated genomes, 8 % were not predicted by the existing protein-coding gene-based tool, implying that both methods can be complementary in the detection of contaminations. A web-based service of the algorithm is available at www.ezbiocloud.net/tools/contest16s.

FASH: A web application for nucleotides sequence search.

PubMed

Veksler-Lublinksy, Isana; Barash, Danny; Avisar, Chai; Troim, Einav; Chew, Paul; Kedem, Klara

2008-05-27

: FASH (Fourier Alignment Sequence Heuristics) is a web application, based on the Fast Fourier Transform, for finding remote homologs within a long nucleic acid sequence. Given a query sequence and a long text-sequence (e.g, the human genome), FASH detects subsequences within the text that are remotely-similar to the query. FASH offers an alternative approach to Blast/Fasta for querying long RNA/DNA sequences. FASH differs from these other approaches in that it does not depend on the existence of contiguous seed-sequences in its initial detection phase. The FASH web server is user friendly and very easy to operate. FASH can be accessed athttps://fash.bgu.ac.il:8443/fash/default.jsp (secured website).

Chromothripsis Detection and Characterization Using the CTLPScanner Web Server.

PubMed

Yang, Jian; Liu, Bo; Cai, Haoyang

2018-01-01

Accurate detection of chromothripsis event is important to study the mechanisms underlying this phenomenon. CTLPScanner ( http://cgma.scu.edu.cn/CTLPScanner/ ) is a web-based tool for identification and annotation of chromothripsis-like pattern (CTLP) in genomic array data. In this chapter, we illustrate the utility of CTLPScanner for screening chromosome pulverization regions and give interpretation of the results. The web interface offers a set of parameters and thresholds for customized screening. We also provide practical recommendations for effective chromothripsis detection. In addition to the user data processing module, CTLPScanner contains more than 50,000 preprocessed oncogenomic arrays, which allow users to explore the presence of chromothripsis signatures from public data resources.

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)

Towards pathogenomics: a web-based resource for pathogenicity islands

PubMed Central

Yoon, Sung Ho; Park, Young-Kyu; Lee, Soohyun; Choi, Doil; Oh, Tae Kwang; Hur, Cheol-Goo; Kim, Jihyun F.

2007-01-01

Pathogenicity islands (PAIs) are genetic elements whose products are essential to the process of disease development. They have been horizontally (laterally) transferred from other microbes and are important in evolution of pathogenesis. In this study, a comprehensive database and search engines specialized for PAIs were established. The pathogenicity island database (PAIDB) is a comprehensive relational database of all the reported PAIs and potential PAI regions which were predicted by a method that combines feature-based analysis and similarity-based analysis. Also, using the PAI Finder search application, a multi-sequence query can be analyzed onsite for the presence of potential PAIs. As of April 2006, PAIDB contains 112 types of PAIs and 889 GenBank accessions containing either partial or all PAI loci previously reported in the literature, which are present in 497 strains of pathogenic bacteria. The database also offers 310 candidate PAIs predicted from 118 sequenced prokaryotic genomes. With the increasing number of prokaryotic genomes without functional inference and sequenced genetic regions of suspected involvement in diseases, this web-based, user-friendly resource has the potential to be of significant use in pathogenomics. PAIDB is freely accessible at . PMID:17090594

DraGnET: Software for storing, managing and analyzing annotated draft genome sequence data

PubMed Central

2010-01-01

Background New "next generation" DNA sequencing technologies offer individual researchers the ability to rapidly generate large amounts of genome sequence data at dramatically reduced costs. As a result, a need has arisen for new software tools for storage, management and analysis of genome sequence data. Although bioinformatic tools are available for the analysis and management of genome sequences, limitations still remain. For example, restrictions on the submission of data and use of these tools may be imposed, thereby making them unsuitable for sequencing projects that need to remain in-house or proprietary during their initial stages. Furthermore, the availability and use of next generation sequencing in industrial, governmental and academic environments requires biologist to have access to computational support for the curation and analysis of the data generated; however, this type of support is not always immediately available. Results To address these limitations, we have developed DraGnET (Draft Genome Evaluation Tool). DraGnET is an open source web application which allows researchers, with no experience in programming and database management, to setup their own in-house projects for storing, retrieving, organizing and managing annotated draft and complete genome sequence data. The software provides a web interface for the use of BLAST, allowing users to perform preliminary comparative analysis among multiple genomes. We demonstrate the utility of DraGnET for performing comparative genomics on closely related bacterial strains. Furthermore, DraGnET can be further developed to incorporate additional tools for more sophisticated analyses. Conclusions DraGnET is designed for use either by individual researchers or as a collaborative tool available through Internet (or Intranet) deployment. For genome projects that require genome sequencing data to initially remain proprietary, DraGnET provides the means for researchers to keep their data in-house for analysis using local programs or until it is made publicly available, at which point it may be uploaded to additional analysis software applications. The DraGnET home page is available at http://www.dragnet.cvm.iastate.edu and includes example files for examining the functionalities, a link for downloading the DraGnET setup package and a link to the DraGnET source code hosted with full documentation on SourceForge. PMID:20175920

PDB-UF: database of predicted enzymatic functions for unannotated protein structures from structural genomics.

PubMed

von Grotthuss, Marcin; Plewczynski, Dariusz; Ginalski, Krzysztof; Rychlewski, Leszek; Shakhnovich, Eugene I

2006-02-06

The number of protein structures from structural genomics centers dramatically increases in the Protein Data Bank (PDB). Many of these structures are functionally unannotated because they have no sequence similarity to proteins of known function. However, it is possible to successfully infer function using only structural similarity. Here we present the PDB-UF database, a web-accessible collection of predictions of enzymatic properties using structure-function relationship. The assignments were conducted for three-dimensional protein structures of unknown function that come from structural genomics initiatives. We show that 4 hypothetical proteins (with PDB accession codes: 1VH0, 1NS5, 1O6D, and 1TO0), for which standard BLAST tools such as PSI-BLAST or RPS-BLAST failed to assign any function, are probably methyltransferase enzymes. We suggest that the structure-based prediction of an EC number should be conducted having the different similarity score cutoff for different protein folds. Moreover, performing the annotation using two different algorithms can reduce the rate of false positive assignments. We believe, that the presented web-based repository will help to decrease the number of protein structures that have functions marked as "unknown" in the PDB file. http://paradox.harvard.edu/PDB-UF and http://bioinfo.pl/PDB-UF.

Hierarchical Scaffolding With Bambus

PubMed Central

Pop, Mihai; Kosack, Daniel S.; Salzberg, Steven L.

2004-01-01

The output of a genome assembler generally comprises a collection of contiguous DNA sequences (contigs) whose relative placement along the genome is not defined. A procedure called scaffolding is commonly used to order and orient these contigs using paired read information. This ordering of contigs is an essential step when finishing and analyzing the data from a whole-genome shotgun project. Most recent assemblers include a scaffolding module; however, users have little control over the scaffolding algorithm or the information produced. We thus developed a general-purpose scaffolder, called Bambus, which affords users significant flexibility in controlling the scaffolding parameters. Bambus was used recently to scaffold the low-coverage draft dog genome data. Most significantly, Bambus enables the use of linking data other than that inferred from mate-pair information. For example, the sequence of a completed genome can be used to guide the scaffolding of a related organism. We present several applications of Bambus: support for finishing, comparative genomics, analysis of the haplotype structure of genomes, and scaffolding of a mammalian genome at low coverage. Bambus is available as an open-source package from our Web site. PMID:14707177

Hierarchical scaffolding with Bambus.

PubMed

Pop, Mihai; Kosack, Daniel S; Salzberg, Steven L

2004-01-01

The output of a genome assembler generally comprises a collection of contiguous DNA sequences (contigs) whose relative placement along the genome is not defined. A procedure called scaffolding is commonly used to order and orient these contigs using paired read information. This ordering of contigs is an essential step when finishing and analyzing the data from a whole-genome shotgun project. Most recent assemblers include a scaffolding module; however, users have little control over the scaffolding algorithm or the information produced. We thus developed a general-purpose scaffolder, called Bambus, which affords users significant flexibility in controlling the scaffolding parameters. Bambus was used recently to scaffold the low-coverage draft dog genome data. Most significantly, Bambus enables the use of linking data other than that inferred from mate-pair information. For example, the sequence of a completed genome can be used to guide the scaffolding of a related organism. We present several applications of Bambus: support for finishing, comparative genomics, analysis of the haplotype structure of genomes, and scaffolding of a mammalian genome at low coverage. Bambus is available as an open-source package from our Web site.

Wasabi: An Integrated Platform for Evolutionary Sequence Analysis and Data Visualization.

PubMed

Veidenberg, Andres; Medlar, Alan; Löytynoja, Ari

2016-04-01

Wasabi is an open source, web-based environment for evolutionary sequence analysis. Wasabi visualizes sequence data together with a phylogenetic tree within a modern, user-friendly interface: The interface hides extraneous options, supports context sensitive menus, drag-and-drop editing, and displays additional information, such as ancestral sequences, associated with specific tree nodes. The Wasabi environment supports reproducibility by automatically storing intermediate analysis steps and includes built-in functions to share data between users and publish analysis results. For computational analysis, Wasabi supports PRANK and PAGAN for phylogeny-aware alignment and alignment extension, and it can be easily extended with other tools. Along with drag-and-drop import of local files, Wasabi can access remote data through URL and import sequence data, GeneTrees and EPO alignments directly from Ensembl. To demonstrate a typical workflow using Wasabi, we reproduce key findings from recent comparative genomics studies, including a reanalysis of the EGLN1 gene from the tiger genome study: These case studies can be browsed within Wasabi at http://wasabiapp.org:8000?id=usecases. Wasabi runs inside a web browser and does not require any installation. One can start using it at http://wasabiapp.org. All source code is licensed under the AGPLv3. © The Author(s) 2015. 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.

FlyAtlas 2: a new version of the Drosophila melanogaster expression atlas with RNA-Seq, miRNA-Seq and sex-specific data

PubMed Central

Krause, Sue A; Pandit, Aniruddha; Davies, Shireen A

2018-01-01

Abstract FlyAtlas 2 (www.flyatlas2.org) is part successor, part complement to the FlyAtlas database and web application for studying the expression of the genes of Drosophila melanogaster in different tissues of adults and larvae. Although generated in the same lab with the same fly line raised on the same diet as FlyAtlas, the FlyAtlas2 resource employs a completely new set of expression data based on RNA-Seq, rather than microarray analysis, and so it allows the user to obtain information for the expression of different transcripts of a gene. Furthermore, the data for somatic tissues are now available for both male and female adult flies, allowing studies of sexual dimorphism. Gene coverage has been extended by the inclusion of microRNAs and many of the RNA genes included in Release 6 of the Drosophila reference genome. The web interface has been modified to accommodate the extra data, but at the same time has been adapted for viewing on small mobile devices. Users also have access to the RNA-Seq reads displayed alongside the annotated Drosophila genome in the (external) UCSC browser, and are able to link out to the previous FlyAtlas resource to compare the data obtained by RNA-Seq with that obtained using microarrays. PMID:29069479

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.

Web-based bioinformatics workflows for end-to-end RNA-seq data computation and analysis in agricultural animal species

USDA-ARS?s Scientific Manuscript database

Remarkable advances in next-generation sequencing (NGS) technologies, bioinformatics algorithms, and computational technologies have significantly accelerated genomic research. However, complicated NGS data analysis still remains as a major bottleneck. RNA-seq, as one of the major area in the NGS fi...

Genomics Portals: integrative web-platform for mining genomics data.

PubMed

Shinde, Kaustubh; Phatak, Mukta; Johannes, Freudenberg M; Chen, Jing; Li, Qian; Vineet, Joshi K; Hu, Zhen; Ghosh, Krishnendu; Meller, Jaroslaw; Medvedovic, Mario

2010-01-13

A large amount of experimental data generated by modern high-throughput technologies is available through various public repositories. Our knowledge about molecular interaction networks, functional biological pathways and transcriptional regulatory modules is rapidly expanding, and is being organized in lists of functionally related genes. Jointly, these two sources of information hold a tremendous potential for gaining new insights into functioning of living systems. Genomics Portals platform integrates access to an extensive knowledge base and a large database of human, mouse, and rat genomics data with basic analytical visualization tools. It provides the context for analyzing and interpreting new experimental data and the tool for effective mining of a large number of publicly available genomics datasets stored in the back-end databases. The uniqueness of this platform lies in the volume and the diversity of genomics data that can be accessed and analyzed (gene expression, ChIP-chip, ChIP-seq, epigenomics, computationally predicted binding sites, etc), and the integration with an extensive knowledge base that can be used in such analysis. The integrated access to primary genomics data, functional knowledge and analytical tools makes Genomics Portals platform a unique tool for interpreting results of new genomics experiments and for mining the vast amount of data stored in the Genomics Portals backend databases. Genomics Portals can be accessed and used freely at http://GenomicsPortals.org.

Genomics Portals: integrative web-platform for mining genomics data

PubMed Central

2010-01-01

Background A large amount of experimental data generated by modern high-throughput technologies is available through various public repositories. Our knowledge about molecular interaction networks, functional biological pathways and transcriptional regulatory modules is rapidly expanding, and is being organized in lists of functionally related genes. Jointly, these two sources of information hold a tremendous potential for gaining new insights into functioning of living systems. Results Genomics Portals platform integrates access to an extensive knowledge base and a large database of human, mouse, and rat genomics data with basic analytical visualization tools. It provides the context for analyzing and interpreting new experimental data and the tool for effective mining of a large number of publicly available genomics datasets stored in the back-end databases. The uniqueness of this platform lies in the volume and the diversity of genomics data that can be accessed and analyzed (gene expression, ChIP-chip, ChIP-seq, epigenomics, computationally predicted binding sites, etc), and the integration with an extensive knowledge base that can be used in such analysis. Conclusion The integrated access to primary genomics data, functional knowledge and analytical tools makes Genomics Portals platform a unique tool for interpreting results of new genomics experiments and for mining the vast amount of data stored in the Genomics Portals backend databases. Genomics Portals can be accessed and used freely at http://GenomicsPortals.org. PMID:20070909

An expression database for roots of the model legume Medicago truncatula under salt stress

PubMed Central

2009-01-01

Background Medicago truncatula is a model legume whose genome is currently being sequenced by an international consortium. Abiotic stresses such as salt stress limit plant growth and crop productivity, including those of legumes. We anticipate that studies on M. truncatula will shed light on other economically important legumes across the world. Here, we report the development of a database called MtED that contains gene expression profiles of the roots of M. truncatula based on time-course salt stress experiments using the Affymetrix Medicago GeneChip. Our hope is that MtED will provide information to assist in improving abiotic stress resistance in legumes. Description The results of our microarray experiment with roots of M. truncatula under 180 mM sodium chloride were deposited in the MtED database. Additionally, sequence and annotation information regarding microarray probe sets were included. MtED provides functional category analysis based on Gene and GeneBins Ontology, and other Web-based tools for querying and retrieving query results, browsing pathways and transcription factor families, showing metabolic maps, and comparing and visualizing expression profiles. Utilities like mapping probe sets to genome of M. truncatula and In-Silico PCR were implemented by BLAT software suite, which were also available through MtED database. Conclusion MtED was built in the PHP script language and as a MySQL relational database system on a Linux server. It has an integrated Web interface, which facilitates ready examination and interpretation of the results of microarray experiments. It is intended to help in selecting gene markers to improve abiotic stress resistance in legumes. MtED is available at http://bioinformatics.cau.edu.cn/MtED/. PMID:19906315

An expression database for roots of the model legume Medicago truncatula under salt stress.

PubMed

Li, Daofeng; Su, Zhen; Dong, Jiangli; Wang, Tao

2009-11-11

Medicago truncatula is a model legume whose genome is currently being sequenced by an international consortium. Abiotic stresses such as salt stress limit plant growth and crop productivity, including those of legumes. We anticipate that studies on M. truncatula will shed light on other economically important legumes across the world. Here, we report the development of a database called MtED that contains gene expression profiles of the roots of M. truncatula based on time-course salt stress experiments using the Affymetrix Medicago GeneChip. Our hope is that MtED will provide information to assist in improving abiotic stress resistance in legumes. The results of our microarray experiment with roots of M. truncatula under 180 mM sodium chloride were deposited in the MtED database. Additionally, sequence and annotation information regarding microarray probe sets were included. MtED provides functional category analysis based on Gene and GeneBins Ontology, and other Web-based tools for querying and retrieving query results, browsing pathways and transcription factor families, showing metabolic maps, and comparing and visualizing expression profiles. Utilities like mapping probe sets to genome of M. truncatula and In-Silico PCR were implemented by BLAT software suite, which were also available through MtED database. MtED was built in the PHP script language and as a MySQL relational database system on a Linux server. It has an integrated Web interface, which facilitates ready examination and interpretation of the results of microarray experiments. It is intended to help in selecting gene markers to improve abiotic stress resistance in legumes. MtED is available at http://bioinformatics.cau.edu.cn/MtED/.

Relax with CouchDB - Into the non-relational DBMS era of Bioinformatics

PubMed Central

Manyam, Ganiraju; Payton, Michelle A.; Roth, Jack A.; Abruzzo, Lynne V.; Coombes, Kevin R.

2012-01-01

With the proliferation of high-throughput technologies, genome-level data analysis has become common in molecular biology. Bioinformaticians are developing extensive resources to annotate and mine biological features from high-throughput data. The underlying database management systems for most bioinformatics software are based on a relational model. Modern non-relational databases offer an alternative that has flexibility, scalability, and a non-rigid design schema. Moreover, with an accelerated development pace, non-relational databases like CouchDB can be ideal tools to construct bioinformatics utilities. We describe CouchDB by presenting three new bioinformatics resources: (a) geneSmash, which collates data from bioinformatics resources and provides automated gene-centric annotations, (b) drugBase, a database of drug-target interactions with a web interface powered by geneSmash, and (c) HapMap-CN, which provides a web interface to query copy number variations from three SNP-chip HapMap datasets. In addition to the web sites, all three systems can be accessed programmatically via web services. PMID:22609849

GeneYenta: a phenotype-based rare disease case matching tool based on online dating algorithms for the acceleration of exome interpretation.

PubMed

Gottlieb, Michael M; Arenillas, David J; Maithripala, Savanie; Maurer, Zachary D; Tarailo Graovac, Maja; Armstrong, Linlea; Patel, Millan; van Karnebeek, Clara; Wasserman, Wyeth W

2015-04-01

Advances in next-generation sequencing (NGS) technologies have helped reveal causal variants for genetic diseases. In order to establish causality, it is often necessary to compare genomes of unrelated individuals with similar disease phenotypes to identify common disrupted genes. When working with cases of rare genetic disorders, finding similar individuals can be extremely difficult. We introduce a web tool, GeneYenta, which facilitates the matchmaking process, allowing clinicians to coordinate detailed comparisons for phenotypically similar cases. Importantly, the system is focused on phenotype annotation, with explicit limitations on highly confidential data that create barriers to participation. The procedure for matching of patient phenotypes, inspired by online dating services, uses an ontology-based semantic case matching algorithm with attribute weighting. We evaluate the capacity of the system using a curated reference data set and 19 clinician entered cases comparing four matching algorithms. We find that the inclusion of clinician weights can augment phenotype matching. © 2015 WILEY PERIODICALS, INC.

Mitochondrial Disease Sequence Data Resource (MSeqDR): a global grass-roots consortium to facilitate deposition, curation, annotation, and integrated analysis of genomic data for the mitochondrial disease clinical and research communities.

PubMed

Falk, Marni J; Shen, Lishuang; Gonzalez, Michael; Leipzig, Jeremy; Lott, Marie T; Stassen, Alphons P M; Diroma, Maria Angela; Navarro-Gomez, Daniel; Yeske, Philip; Bai, Renkui; Boles, Richard G; Brilhante, Virginia; Ralph, David; DaRe, Jeana T; Shelton, Robert; Terry, Sharon F; Zhang, Zhe; Copeland, William C; van Oven, Mannis; Prokisch, Holger; Wallace, Douglas C; Attimonelli, Marcella; Krotoski, Danuta; Zuchner, Stephan; Gai, Xiaowu

2015-03-01

Success rates for genomic analyses of highly heterogeneous disorders can be greatly improved if a large cohort of patient data is assembled to enhance collective capabilities for accurate sequence variant annotation, analysis, and interpretation. Indeed, molecular diagnostics requires the establishment of robust data resources to enable data sharing that informs accurate understanding of genes, variants, and phenotypes. The "Mitochondrial Disease Sequence Data Resource (MSeqDR) Consortium" is a grass-roots effort facilitated by the United Mitochondrial Disease Foundation to identify and prioritize specific genomic data analysis needs of the global mitochondrial disease clinical and research community. A central Web portal (https://mseqdr.org) facilitates the coherent compilation, organization, annotation, and analysis of sequence data from both nuclear and mitochondrial genomes of individuals and families with suspected mitochondrial disease. This Web portal provides users with a flexible and expandable suite of resources to enable variant-, gene-, and exome-level sequence analysis in a secure, Web-based, and user-friendly fashion. Users can also elect to share data with other MSeqDR Consortium members, or even the general public, either by custom annotation tracks or through the use of a convenient distributed annotation system (DAS) mechanism. A range of data visualization and analysis tools are provided to facilitate user interrogation and understanding of genomic, and ultimately phenotypic, data of relevance to mitochondrial biology and disease. Currently available tools for nuclear and mitochondrial gene analyses include an MSeqDR GBrowse instance that hosts optimized mitochondrial disease and mitochondrial DNA (mtDNA) specific annotation tracks, as well as an MSeqDR locus-specific database (LSDB) that curates variant data on more than 1300 genes that have been implicated in mitochondrial disease and/or encode mitochondria-localized proteins. MSeqDR is integrated with a diverse array of mtDNA data analysis tools that are both freestanding and incorporated into an online exome-level dataset curation and analysis resource (GEM.app) that is being optimized to support needs of the MSeqDR community. In addition, MSeqDR supports mitochondrial disease phenotyping and ontology tools, and provides variant pathogenicity assessment features that enable community review, feedback, and integration with the public ClinVar variant annotation resource. A centralized Web-based informed consent process is being developed, with implementation of a Global Unique Identifier (GUID) system to integrate data deposited on a given individual from different sources. Community-based data deposition into MSeqDR has already begun. Future efforts will enhance capabilities to incorporate phenotypic data that enhance genomic data analyses. MSeqDR will fill the existing void in bioinformatics tools and centralized knowledge that are necessary to enable efficient nuclear and mtDNA genomic data interpretation by a range of shareholders across both clinical diagnostic and research settings. Ultimately, MSeqDR is focused on empowering the global mitochondrial disease community to better define and explore mitochondrial diseases. Copyright © 2014 Elsevier Inc. All rights reserved.

Mitochondrial Disease Sequence Data Resource (MSeqDR): A global grass-roots consortium to facilitate deposition, curation, annotation, and integrated analysis of genomic data for the mitochondrial disease clinical and research communities

PubMed Central

Falk, Marni J.; Shen, Lishuang; Gonzalez, Michael; Leipzig, Jeremy; Lott, Marie T.; Stassen, Alphons P.M.; Diroma, Maria Angela; Navarro-Gomez, Daniel; Yeske, Philip; Bai, Renkui; Boles, Richard G.; Brilhante, Virginia; Ralph, David; DaRe, Jeana T.; Shelton, Robert; Terry, Sharon; Zhang, Zhe; Copeland, William C.; van Oven, Mannis; Prokisch, Holger; Wallace, Douglas C.; Attimonelli, Marcella; Krotoski, Danuta; Zuchner, Stephan; Gai, Xiaowu

2014-01-01

Success rates for genomic analyses of highly heterogeneous disorders can be greatly improved if a large cohort of patient data is assembled to enhance collective capabilities for accurate sequence variant annotation, analysis, and interpretation. Indeed, molecular diagnostics requires the establishment of robust data resources to enable data sharing that informs accurate understanding of genes, variants, and phenotypes. The “Mitochondrial Disease Sequence Data Resource (MSeqDR) Consortium” is a grass-roots effort facilitated by the United Mitochondrial Disease Foundation to identify and prioritize specific genomic data analysis needs of the global mitochondrial disease clinical and research community. A central Web portal (https://mseqdr.org) facilitates the coherent compilation, organization, annotation, and analysis of sequence data from both nuclear and mitochondrial genomes of individuals and families with suspected mitochondrial disease. This Web portal provides users with a flexible and expandable suite of resources to enable variant-, gene-, and exome-level sequence analysis in a secure, Web-based, and user-friendly fashion. Users can also elect to share data with other MSeqDR Consortium members, or even the general public, either by custom annotation tracks or through use of a convenient distributed annotation system (DAS) mechanism. A range of data visualization and analysis tools are provided to facilitate user interrogation and understanding of genomic, and ultimately phenotypic, data of relevance to mitochondrial biology and disease. Currently available tools for nuclear and mitochondrial gene analyses include an MSeqDR GBrowse instance that hosts optimized mitochondrial disease and mitochondrial DNA (mtDNA) specific annotation tracks, as well as an MSeqDR locus-specific database (LSDB) that curates variant data on more than 1,300 genes that have been implicated in mitochondrial disease and/or encode mitochondria-localized proteins. MSeqDR is integrated with a diverse array of mtDNA data analysis tools that are both freestanding and incorporated into an online exome-level dataset curation and analysis resource (GEM.app) that is being optimized to support needs of the MSeqDR community. In addition, MSeqDR supports mitochondrial disease phenotyping and ontology tools, and provides variant pathogenicity assessment features that enable community review, feedback, and integration with the public ClinVar variant annotation resource. A centralized Web-based informed consent process is being developed, with implementation of a Global Unique Identifier (GUID) system to integrate data deposited on a given individual from different sources. Community-based data deposition into MSeqDR has already begun. Future efforts will enhance capabilities to incorporate phenotypic data that enhance genomic data analyses. MSeqDR will fill the existing void in bioinformatics tools and centralized knowledge that are necessary to enable efficient nuclear and mtDNA genomic data interpretation by a range of shareholders across both clinical diagnostic and research settings. Ultimately, MSeqDR is focused on empowering the global mitochondrial disease community to better define and explore mitochondrial disease. PMID:25542617

Accessible Genetics Research Ethics Education (AGREE): A Web-Based Program for IRBs and Investigators

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

Sugarman, Jeremy; Lee, Linda

The primary objective of this project was to design and evaluate a series of web-based educational modules on genetics research ethics for members of Institutional Review Boards and investigators to facilitate the development and oversight of important research that is sensitive to the relevant ethical, legal and social issues. After a needs assessment was completed in March of 2003, five online educational modules on the ethics of research in genetics were developed, tested, and made available through a host website for AGREE: http://agree.mc.duke.edu/index.html. The 5 modules are: (1) Ethics and Genetics Research in Populations; (2) Ethics in Behavioral Genetics Research;more » (3) Ethical Issues in Research on Gene-Environment Interactions; (4) Ethical Issues in Reproductive Genetics Research; and (5) Ethical Issues in Diagnostic and Therapeutic Research. The development process adopted a tested approach used at Duke University School of Medicine in providing education for researchers and IRB members, supplementing it with expert input and a rigorous evaluation. The host website also included a description of the AGREE; short bios on the AGREE Investigators and Expert Advisory Panel; streaming media of selected presentations from a conference, Working at the Frontiers of Law and Science: Applications of the Human Genome held October 2-3, 2003, at the University of North Carolina at Chapel Hill; and links to online resources in genomics, research ethics, ethics in genomics research, and related organizations. The web site was active beginning with the posting of the first module and was maintained throughout the project period. We have also secured agreement to keep the site active an additional year beyond the project period. AGREE met its primary objective of creating web-based educational modules related to the ethical issues in genetics research. The modules have been disseminated widely. While it is clearly easier to judge the quality of the educational experience than to evaluate the impact of an educational program on research, the AGREE modules have been met with very positive feedback on the part of users.« less

MetaRanker 2.0: a web server for prioritization of genetic variation data

PubMed Central

Pers, Tune H.; Dworzyński, Piotr; Thomas, Cecilia Engel; Lage, Kasper; Brunak, Søren

2013-01-01

MetaRanker 2.0 is a web server for prioritization of common and rare frequency genetic variation data. Based on heterogeneous data sets including genetic association data, protein–protein interactions, large-scale text-mining data, copy number variation data and gene expression experiments, MetaRanker 2.0 prioritizes the protein-coding part of the human genome to shortlist candidate genes for targeted follow-up studies. MetaRanker 2.0 is made freely available at www.cbs.dtu.dk/services/MetaRanker-2.0. PMID:23703204

MetaRanker 2.0: a web server for prioritization of genetic variation data.

PubMed

Pers, Tune H; Dworzyński, Piotr; Thomas, Cecilia Engel; Lage, Kasper; Brunak, Søren

2013-07-01

MetaRanker 2.0 is a web server for prioritization of common and rare frequency genetic variation data. Based on heterogeneous data sets including genetic association data, protein-protein interactions, large-scale text-mining data, copy number variation data and gene expression experiments, MetaRanker 2.0 prioritizes the protein-coding part of the human genome to shortlist candidate genes for targeted follow-up studies. MetaRanker 2.0 is made freely available at www.cbs.dtu.dk/services/MetaRanker-2.0.

mod_bio: Apache modules for Next-Generation sequencing data.

PubMed

Lindenbaum, Pierre; Redon, Richard

2015-01-01

We describe mod_bio, a set of modules for the Apache HTTP server that allows the users to access and query fastq, tabix, fasta and bam files through a Web browser. Those data are made available in plain text, HTML, XML, JSON and JSON-P. A javascript-based genome browser using the JSON-P communication technique is provided as an example of cross-domain Web service. https://github.com/lindenb/mod_bio. © The Author 2014. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

PomBase: a comprehensive online resource for fission yeast

PubMed Central

Wood, Valerie; Harris, Midori A.; McDowall, Mark D.; Rutherford, Kim; Vaughan, Brendan W.; Staines, Daniel M.; Aslett, Martin; Lock, Antonia; Bähler, Jürg; Kersey, Paul J.; Oliver, Stephen G.

2012-01-01

PomBase (www.pombase.org) is a new model organism database established to provide access to comprehensive, accurate, and up-to-date molecular data and biological information for the fission yeast Schizosaccharomyces pombe to effectively support both exploratory and hypothesis-driven research. PomBase encompasses annotation of genomic sequence and features, comprehensive manual literature curation and genome-wide data sets, and supports sophisticated user-defined queries. The implementation of PomBase integrates a Chado relational database that houses manually curated data with Ensembl software that supports sequence-based annotation and web access. PomBase will provide user-friendly tools to promote curation by experts within the fission yeast community. This will make a key contribution to shaping its content and ensuring its comprehensiveness and long-term relevance. PMID:22039153

FY09 Final Report for LDRD Project: Understanding Viral Quasispecies Evolution through Computation and Experiment

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

Zhou, C

2009-11-12

In FY09 they will (1) complete the implementation, verification, calibration, and sensitivity and scalability analysis of the in-cell virus replication model; (2) complete the design of the cell culture (cell-to-cell infection) model; (3) continue the research, design, and development of their bioinformatics tools: the Web-based structure-alignment-based sequence variability tool and the functional annotation of the genome database; (4) collaborate with the University of California at San Francisco on areas of common interest; and (5) submit journal articles that describe the in-cell model with simulations and the bioinformatics approaches to evaluation of genome variability and fitness.

CNVinspector: a web-based tool for the interactive evaluation of copy number variations in single patients and in cohorts.

PubMed

Knierim, Ellen; Schwarz, Jana Marie; Schuelke, Markus; Seelow, Dominik

2013-08-01

Many genetic disorders are caused by copy number variations (CNVs) in the human genome. However, the large number of benign CNV polymorphisms makes it difficult to delineate causative variants for a certain disease phenotype. Hence, we set out to create software that accumulates and visualises locus-specific knowledge and enables clinicians to study their own CNVs in the context of known polymorphisms and disease variants. CNV data from healthy cohorts (Database of Genomic Variants) and from disease-related databases (DECIPHER) were integrated into a joint resource. Data are presented in an interactive web-based application that allows inspection, evaluation and filtering of CNVs in single individuals or in entire cohorts. CNVinspector provides simple interfaces to upload CNV data, compare them with own or published control data and visualise the results in graphical interfaces. Beyond choosing control data from different public studies, platforms and methods, dedicated filter options allow the detection of CNVs that are either enriched in patients or depleted in controls. Alternatively, a search can be restricted to those CNVs that appear in individuals of similar clinical phenotype. For each gene of interest within a CNV, we provide a link to NCBI, ENSEMBL and the GeneDistiller search engine to browse for potential disease-associated genes. With its user-friendly handling, the integration of control data and the filtering options, CNVinspector will facilitate the daily work of clinical geneticists and accelerate the delineation of new syndromes and gene functions. CNVinspector is freely accessible under http://www.cnvinspector.org.

Genome Wide Re-Annotation of Caldicellulosiruptor saccharolyticus with New Insights into Genes Involved in Biomass Degradation and Hydrogen Production

PubMed Central

Chowdhary, Nupoor; Selvaraj, Ashok; KrishnaKumaar, Lakshmi; Kumar, Gopal Ramesh

2015-01-01

Caldicellulosiruptor saccharolyticus has proven itself to be an excellent candidate for biological hydrogen (H2) production, but still it has major drawbacks like sensitivity to high osmotic pressure and low volumetric H2 productivity, which should be considered before it can be used industrially. A whole genome re-annotation work has been carried out as an attempt to update the incomplete genome information that causes gap in the knowledge especially in the area of metabolic engineering, to improve the H2 producing capabilities of C. saccharolyticus. Whole genome re-annotation was performed through manual means for 2,682 Coding Sequences (CDSs). Bioinformatics tools based on sequence similarity, motif search, phylogenetic analysis and fold recognition were employed for re-annotation. Our methodology could successfully add functions for 409 hypothetical proteins (HPs), 46 proteins previously annotated as putative and assigned more accurate functions for the known protein sequences. Homology based gene annotation has been used as a standard method for assigning function to novel proteins, but over the past few years many non-homology based methods such as genomic context approaches for protein function prediction have been developed. Using non-homology based functional prediction methods, we were able to assign cellular processes or physical complexes for 249 hypothetical sequences. Our re-annotation pipeline highlights the addition of 231 new CDSs generated from MicroScope Platform, to the original genome with functional prediction for 49 of them. The re-annotation of HPs and new CDSs is stored in the relational database that is available on the MicroScope web-based platform. In parallel, a comparative genome analyses were performed among the members of genus Caldicellulosiruptor to understand the function and evolutionary processes. Further, with results from integrated re-annotation studies (homology and genomic context approach), we strongly suggest that Csac_0437 and Csac_0424 encode for glycoside hydrolases (GH) and are proposed to be involved in the decomposition of recalcitrant plant polysaccharides. Similarly, HPs: Csac_0732, Csac_1862, Csac_1294 and Csac_0668 are suggested to play a significant role in biohydrogen production. Function prediction of these HPs by using our integrated approach will considerably enhance the interpretation of large-scale experiments targeting this industrially important organism. PMID:26196387

Genome Wide Re-Annotation of Caldicellulosiruptor saccharolyticus with New Insights into Genes Involved in Biomass Degradation and Hydrogen Production.

PubMed

Chowdhary, Nupoor; Selvaraj, Ashok; KrishnaKumaar, Lakshmi; Kumar, Gopal Ramesh

2015-01-01

Caldicellulosiruptor saccharolyticus has proven itself to be an excellent candidate for biological hydrogen (H2) production, but still it has major drawbacks like sensitivity to high osmotic pressure and low volumetric H2 productivity, which should be considered before it can be used industrially. A whole genome re-annotation work has been carried out as an attempt to update the incomplete genome information that causes gap in the knowledge especially in the area of metabolic engineering, to improve the H2 producing capabilities of C. saccharolyticus. Whole genome re-annotation was performed through manual means for 2,682 Coding Sequences (CDSs). Bioinformatics tools based on sequence similarity, motif search, phylogenetic analysis and fold recognition were employed for re-annotation. Our methodology could successfully add functions for 409 hypothetical proteins (HPs), 46 proteins previously annotated as putative and assigned more accurate functions for the known protein sequences. Homology based gene annotation has been used as a standard method for assigning function to novel proteins, but over the past few years many non-homology based methods such as genomic context approaches for protein function prediction have been developed. Using non-homology based functional prediction methods, we were able to assign cellular processes or physical complexes for 249 hypothetical sequences. Our re-annotation pipeline highlights the addition of 231 new CDSs generated from MicroScope Platform, to the original genome with functional prediction for 49 of them. The re-annotation of HPs and new CDSs is stored in the relational database that is available on the MicroScope web-based platform. In parallel, a comparative genome analyses were performed among the members of genus Caldicellulosiruptor to understand the function and evolutionary processes. Further, with results from integrated re-annotation studies (homology and genomic context approach), we strongly suggest that Csac_0437 and Csac_0424 encode for glycoside hydrolases (GH) and are proposed to be involved in the decomposition of recalcitrant plant polysaccharides. Similarly, HPs: Csac_0732, Csac_1862, Csac_1294 and Csac_0668 are suggested to play a significant role in biohydrogen production. Function prediction of these HPs by using our integrated approach will considerably enhance the interpretation of large-scale experiments targeting this industrially important organism.

A genomic overview of the population structure of Salmonella.

PubMed

Alikhan, Nabil-Fareed; Zhou, Zhemin; Sergeant, Martin J; Achtman, Mark

2018-04-01

For many decades, Salmonella enterica has been subdivided by serological properties into serovars or further subdivided for epidemiological tracing by a variety of diagnostic tests with higher resolution. Recently, it has been proposed that so-called eBurst groups (eBGs) based on the alleles of seven housekeeping genes (legacy multilocus sequence typing [MLST]) corresponded to natural populations and could replace serotyping. However, this approach lacks the resolution needed for epidemiological tracing and the existence of natural populations had not been independently validated by independent criteria. Here, we describe EnteroBase, a web-based platform that assembles draft genomes from Illumina short reads in the public domain or that are uploaded by users. EnteroBase implements legacy MLST as well as ribosomal gene MLST (rMLST), core genome MLST (cgMLST), and whole genome MLST (wgMLST) and currently contains over 100,000 assembled genomes from Salmonella. It also provides graphical tools for visual interrogation of these genotypes and those based on core single nucleotide polymorphisms (SNPs). eBGs based on legacy MLST are largely consistent with eBGs based on rMLST, thus demonstrating that these correspond to natural populations. rMLST also facilitated the selection of representative genotypes for SNP analyses of the entire breadth of diversity within Salmonella. In contrast, cgMLST provides the resolution needed for epidemiological investigations. These observations show that genomic genotyping, with the assistance of EnteroBase, can be applied at all levels of diversity within the Salmonella genus.

Lightweight genome viewer: portable software for browsing genomics data in its chromosomal context

PubMed Central

Faith, Jeremiah J; Olson, Andrew J; Gardner, Timothy S; Sachidanandam, Ravi

2007-01-01

Background Lightweight genome viewer (lwgv) is a web-based tool for visualization of sequence annotations in their chromosomal context. It performs most of the functions of larger genome browsers, while relying on standard flat-file formats and bypassing the database needs of most visualization tools. Visualization as an aide to discovery requires display of novel data in conjunction with static annotations in their chromosomal context. With database-based systems, displaying dynamic results requires temporary tables that need to be tracked for removal. Results lwgv simplifies the visualization of user-generated results on a local computer. The dynamic results of these analyses are written to transient files, which can import static content from a more permanent file. lwgv is currently used in many different applications, from whole genome browsers to single-gene RNAi design visualization, demonstrating its applicability in a large variety of contexts and scales. Conclusion lwgv provides a lightweight alternative to large genome browsers for visualizing biological annotations and dynamic analyses in their chromosomal context. It is particularly suited for applications ranging from short sequences to medium-sized genomes when the creation and maintenance of a large software and database infrastructure is not necessary or desired. PMID:17877794

Cloud-based interactive analytics for terabytes of genomic variants data.

PubMed

Pan, Cuiping; McInnes, Gregory; Deflaux, Nicole; Snyder, Michael; Bingham, Jonathan; Datta, Somalee; Tsao, Philip S

2017-12-01

Large scale genomic sequencing is now widely used to decipher questions in diverse realms such as biological function, human diseases, evolution, ecosystems, and agriculture. With the quantity and diversity these data harbor, a robust and scalable data handling and analysis solution is desired. We present interactive analytics using a cloud-based columnar database built on Dremel to perform information compression, comprehensive quality controls, and biological information retrieval in large volumes of genomic data. We demonstrate such Big Data computing paradigms can provide orders of magnitude faster turnaround for common genomic analyses, transforming long-running batch jobs submitted via a Linux shell into questions that can be asked from a web browser in seconds. Using this method, we assessed a study population of 475 deeply sequenced human genomes for genomic call rate, genotype and allele frequency distribution, variant density across the genome, and pharmacogenomic information. Our analysis framework is implemented in Google Cloud Platform and BigQuery. Codes are available at https://github.com/StanfordBioinformatics/mvp_aaa_codelabs. cuiping@stanford.edu or ptsao@stanford.edu. Supplementary data are available at Bioinformatics online. Published by Oxford University Press 2017. This work is written by US Government employees and are in the public domain in the US.

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 .

Lightweight genome viewer: portable software for browsing genomics data in its chromosomal context.

PubMed

Faith, Jeremiah J; Olson, Andrew J; Gardner, Timothy S; Sachidanandam, Ravi

2007-09-18

Lightweight genome viewer (lwgv) is a web-based tool for visualization of sequence annotations in their chromosomal context. It performs most of the functions of larger genome browsers, while relying on standard flat-file formats and bypassing the database needs of most visualization tools. Visualization as an aide to discovery requires display of novel data in conjunction with static annotations in their chromosomal context. With database-based systems, displaying dynamic results requires temporary tables that need to be tracked for removal. lwgv simplifies the visualization of user-generated results on a local computer. The dynamic results of these analyses are written to transient files, which can import static content from a more permanent file. lwgv is currently used in many different applications, from whole genome browsers to single-gene RNAi design visualization, demonstrating its applicability in a large variety of contexts and scales. lwgv provides a lightweight alternative to large genome browsers for visualizing biological annotations and dynamic analyses in their chromosomal context. It is particularly suited for applications ranging from short sequences to medium-sized genomes when the creation and maintenance of a large software and database infrastructure is not necessary or desired.

Cloud-based interactive analytics for terabytes of genomic variants data

PubMed Central

Pan, Cuiping; McInnes, Gregory; Deflaux, Nicole; Snyder, Michael; Bingham, Jonathan; Datta, Somalee; Tsao, Philip S

2017-01-01

Abstract Motivation Large scale genomic sequencing is now widely used to decipher questions in diverse realms such as biological function, human diseases, evolution, ecosystems, and agriculture. With the quantity and diversity these data harbor, a robust and scalable data handling and analysis solution is desired. Results We present interactive analytics using a cloud-based columnar database built on Dremel to perform information compression, comprehensive quality controls, and biological information retrieval in large volumes of genomic data. We demonstrate such Big Data computing paradigms can provide orders of magnitude faster turnaround for common genomic analyses, transforming long-running batch jobs submitted via a Linux shell into questions that can be asked from a web browser in seconds. Using this method, we assessed a study population of 475 deeply sequenced human genomes for genomic call rate, genotype and allele frequency distribution, variant density across the genome, and pharmacogenomic information. Availability and implementation Our analysis framework is implemented in Google Cloud Platform and BigQuery. Codes are available at https://github.com/StanfordBioinformatics/mvp_aaa_codelabs. Contact cuiping@stanford.edu or ptsao@stanford.edu Supplementary information Supplementary data are available at Bioinformatics online. PMID:28961771

Online Learning: A Comparison of Web-Based and Land-Based Courses

ERIC Educational Resources Information Center

Brown, Joy L. M.

2012-01-01

Distance learning has become more popular in recent years. Due to concern about the quality of web-based courses, the purpose of this study was to explore the differences in web-based versus land-based courses. In this study, the researcher compares web-based and land-based education courses to explore the strengths and weaknesses of each type of…

Novel Approach to Analyzing MFE of Noncoding RNA Sequences

PubMed Central

George, Tina P.; Thomas, Tessamma

2016-01-01

Genomic studies have become noncoding RNA (ncRNA) centric after the study of different genomes provided enormous information on ncRNA over the past decades. The function of ncRNA is decided by its secondary structure, and across organisms, the secondary structure is more conserved than the sequence itself. In this study, the optimal secondary structure or the minimum free energy (MFE) structure of ncRNA was found based on the thermodynamic nearest neighbor model. MFE of over 2600 ncRNA sequences was analyzed in view of its signal properties. Mathematical models linking MFE to the signal properties were found for each of the four classes of ncRNA analyzed. MFE values computed with the proposed models were in concordance with those obtained with the standard web servers. A total of 95% of the sequences analyzed had deviation of MFE values within ±15% relative to those obtained from standard web servers. PMID:27695341

Novel Approach to Analyzing MFE of Noncoding RNA Sequences.

PubMed

George, Tina P; Thomas, Tessamma

2016-01-01

Genomic studies have become noncoding RNA (ncRNA) centric after the study of different genomes provided enormous information on ncRNA over the past decades. The function of ncRNA is decided by its secondary structure, and across organisms, the secondary structure is more conserved than the sequence itself. In this study, the optimal secondary structure or the minimum free energy (MFE) structure of ncRNA was found based on the thermodynamic nearest neighbor model. MFE of over 2600 ncRNA sequences was analyzed in view of its signal properties. Mathematical models linking MFE to the signal properties were found for each of the four classes of ncRNA analyzed. MFE values computed with the proposed models were in concordance with those obtained with the standard web servers. A total of 95% of the sequences analyzed had deviation of MFE values within ±15% relative to those obtained from standard web servers.

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.

Computation of direct and inverse mutations with the SEGM web server (Stochastic Evolution of Genetic Motifs): an application to splice sites of human genome introns.

PubMed

Benard, Emmanuel; Michel, Christian J

2009-08-01

We present here the SEGM web server (Stochastic Evolution of Genetic Motifs) in order to study the evolution of genetic motifs both in the direct evolutionary sense (past-present) and in the inverse evolutionary sense (present-past). The genetic motifs studied can be nucleotides, dinucleotides and trinucleotides. As an example of an application of SEGM and to understand its functionalities, we give an analysis of inverse mutations of splice sites of human genome introns. SEGM is freely accessible at http://lsiit-bioinfo.u-strasbg.fr:8080/webMathematica/SEGM/SEGM.html directly or by the web site http://dpt-info.u-strasbg.fr/~michel/. To our knowledge, this SEGM web server is to date the only computational biology software in this evolutionary approach.

SnowyOwl: accurate prediction of fungal genes by using RNA-Seq and homology information to select among ab initio models

PubMed Central

2014-01-01

Background Locating the protein-coding genes in novel genomes is essential to understanding and exploiting the genomic information but it is still difficult to accurately predict all the genes. The recent availability of detailed information about transcript structure from high-throughput sequencing of messenger RNA (RNA-Seq) delineates many expressed genes and promises increased accuracy in gene prediction. Computational gene predictors have been intensively developed for and tested in well-studied animal genomes. Hundreds of fungal genomes are now or will soon be sequenced. The differences of fungal genomes from animal genomes and the phylogenetic sparsity of well-studied fungi call for gene-prediction tools tailored to them. Results SnowyOwl is a new gene prediction pipeline that uses RNA-Seq data to train and provide hints for the generation of Hidden Markov Model (HMM)-based gene predictions and to evaluate the resulting models. The pipeline has been developed and streamlined by comparing its predictions to manually curated gene models in three fungal genomes and validated against the high-quality gene annotation of Neurospora crassa; SnowyOwl predicted N. crassa genes with 83% sensitivity and 65% specificity. SnowyOwl gains sensitivity by repeatedly running the HMM gene predictor Augustus with varied input parameters and selectivity by choosing the models with best homology to known proteins and best agreement with the RNA-Seq data. Conclusions SnowyOwl efficiently uses RNA-Seq data to produce accurate gene models in both well-studied and novel fungal genomes. The source code for the SnowyOwl pipeline (in Python) and a web interface (in PHP) is freely available from http://sourceforge.net/projects/snowyowl/. PMID:24980894

LS-SNP: large-scale annotation of coding non-synonymous SNPs based on multiple information sources.

PubMed

Karchin, Rachel; Diekhans, Mark; Kelly, Libusha; Thomas, Daryl J; Pieper, Ursula; Eswar, Narayanan; Haussler, David; Sali, Andrej

2005-06-15

The NCBI dbSNP database lists over 9 million single nucleotide polymorphisms (SNPs) in the human genome, but currently contains limited annotation information. SNPs that result in amino acid residue changes (nsSNPs) are of critical importance in variation between individuals, including disease and drug sensitivity. We have developed LS-SNP, a genomic scale software pipeline to annotate nsSNPs. LS-SNP comprehensively maps nsSNPs onto protein sequences, functional pathways and comparative protein structure models, and predicts positions where nsSNPs destabilize proteins, interfere with the formation of domain-domain interfaces, have an effect on protein-ligand binding or severely impact human health. It currently annotates 28,043 validated SNPs that produce amino acid residue substitutions in human proteins from the SwissProt/TrEMBL database. Annotations can be viewed via a web interface either in the context of a genomic region or by selecting sets of SNPs, genes, proteins or pathways. These results are useful for identifying candidate functional SNPs within a gene, haplotype or pathway and in probing molecular mechanisms responsible for functional impacts of nsSNPs. http://www.salilab.org/LS-SNP CONTACT: rachelk@salilab.org http://salilab.org/LS-SNP/supp-info.pdf.

Methods for open innovation on a genome-design platform associating scientific, commercial, and educational communities in synthetic biology.

PubMed

Toyoda, Tetsuro

2011-01-01

Synthetic biology requires both engineering efficiency and compliance with safety guidelines and ethics. Focusing on the rational construction of biological systems based on engineering principles, synthetic biology depends on a genome-design platform to explore the combinations of multiple biological components or BIO bricks for quickly producing innovative devices. This chapter explains the differences among various platform models and details a methodology for promoting open innovation within the scope of the statutory exemption of patent laws. The detailed platform adopts a centralized evaluation model (CEM), computer-aided design (CAD) bricks, and a freemium model. It is also important for the platform to support the legal aspects of copyrights as well as patent and safety guidelines because intellectual work including DNA sequences designed rationally by human intelligence is basically copyrightable. An informational platform with high traceability, transparency, auditability, and security is required for copyright proof, safety compliance, and incentive management for open innovation in synthetic biology. GenoCon, which we have organized and explained here, is a competition-styled, open-innovation method involving worldwide participants from scientific, commercial, and educational communities that aims to improve the designs of genomic sequences that confer a desired function on an organism. Using only a Web browser, a participating contributor proposes a design expressed with CAD bricks that generate a relevant DNA sequence, which is then experimentally and intensively evaluated by the GenoCon organizers. The CAD bricks that comprise programs and databases as a Semantic Web are developed, executed, shared, reused, and well stocked on the secure Semantic Web platform called the Scientists' Networking System or SciNetS/SciNeS, based on which a CEM research center for synthetic biology and open innovation should be established. Copyright © 2011 Elsevier Inc. All rights reserved.

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

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 .

Immediate Dissemination of Student Discoveries to a Model Organism Database Enhances Classroom-Based Research Experiences

PubMed Central

Wiley, Emily A.; Stover, Nicholas A.

2014-01-01

Use of inquiry-based research modules in the classroom has soared over recent years, largely in response to national calls for teaching that provides experience with scientific processes and methodologies. To increase the visibility of in-class studies among interested researchers and to strengthen their impact on student learning, we have extended the typical model of inquiry-based labs to include a means for targeted dissemination of student-generated discoveries. This initiative required: 1) creating a set of research-based lab activities with the potential to yield results that a particular scientific community would find useful and 2) developing a means for immediate sharing of student-generated results. Working toward these goals, we designed guides for course-based research aimed to fulfill the need for functional annotation of the Tetrahymena thermophila genome, and developed an interactive Web database that links directly to the official Tetrahymena Genome Database for immediate, targeted dissemination of student discoveries. This combination of research via the course modules and the opportunity for students to immediately “publish” their novel results on a Web database actively used by outside scientists culminated in a motivational tool that enhanced students’ efforts to engage the scientific process and pursue additional research opportunities beyond the course. PMID:24591511

Immediate dissemination of student discoveries to a model organism database enhances classroom-based research experiences.

PubMed

Wiley, Emily A; Stover, Nicholas A

2014-01-01

Use of inquiry-based research modules in the classroom has soared over recent years, largely in response to national calls for teaching that provides experience with scientific processes and methodologies. To increase the visibility of in-class studies among interested researchers and to strengthen their impact on student learning, we have extended the typical model of inquiry-based labs to include a means for targeted dissemination of student-generated discoveries. This initiative required: 1) creating a set of research-based lab activities with the potential to yield results that a particular scientific community would find useful and 2) developing a means for immediate sharing of student-generated results. Working toward these goals, we designed guides for course-based research aimed to fulfill the need for functional annotation of the Tetrahymena thermophila genome, and developed an interactive Web database that links directly to the official Tetrahymena Genome Database for immediate, targeted dissemination of student discoveries. This combination of research via the course modules and the opportunity for students to immediately "publish" their novel results on a Web database actively used by outside scientists culminated in a motivational tool that enhanced students' efforts to engage the scientific process and pursue additional research opportunities beyond the course.

Pathway Distiller - multisource biological pathway consolidation

PubMed Central

2012-01-01

Background One method to understand and evaluate an experiment that produces a large set of genes, such as a gene expression microarray analysis, is to identify overrepresentation or enrichment for biological pathways. Because pathways are able to functionally describe the set of genes, much effort has been made to collect curated biological pathways into publicly accessible databases. When combining disparate databases, highly related or redundant pathways exist, making their consolidation into pathway concepts essential. This will facilitate unbiased, comprehensive yet streamlined analysis of experiments that result in large gene sets. Methods After gene set enrichment finds representative pathways for large gene sets, pathways are consolidated into representative pathway concepts. Three complementary, but different methods of pathway consolidation are explored. Enrichment Consolidation combines the set of the pathways enriched for the signature gene list through iterative combining of enriched pathways with other pathways with similar signature gene sets; Weighted Consolidation utilizes a Protein-Protein Interaction network based gene-weighting approach that finds clusters of both enriched and non-enriched pathways limited to the experiments' resultant gene list; and finally the de novo Consolidation method uses several measurements of pathway similarity, that finds static pathway clusters independent of any given experiment. Results We demonstrate that the three consolidation methods provide unified yet different functional insights of a resultant gene set derived from a genome-wide profiling experiment. Results from the methods are presented, demonstrating their applications in biological studies and comparing with a pathway web-based framework that also combines several pathway databases. Additionally a web-based consolidation framework that encompasses all three methods discussed in this paper, Pathway Distiller (http://cbbiweb.uthscsa.edu/PathwayDistiller), is established to allow researchers access to the methods and example microarray data described in this manuscript, and the ability to analyze their own gene list by using our unique consolidation methods. Conclusions By combining several pathway systems, implementing different, but complementary pathway consolidation methods, and providing a user-friendly web-accessible tool, we have enabled users the ability to extract functional explanations of their genome wide experiments. PMID:23134636

Pathway Distiller - multisource biological pathway consolidation.

PubMed

Doderer, Mark S; Anguiano, Zachry; Suresh, Uthra; Dashnamoorthy, Ravi; Bishop, Alexander J R; Chen, Yidong

2012-01-01

One method to understand and evaluate an experiment that produces a large set of genes, such as a gene expression microarray analysis, is to identify overrepresentation or enrichment for biological pathways. Because pathways are able to functionally describe the set of genes, much effort has been made to collect curated biological pathways into publicly accessible databases. When combining disparate databases, highly related or redundant pathways exist, making their consolidation into pathway concepts essential. This will facilitate unbiased, comprehensive yet streamlined analysis of experiments that result in large gene sets. After gene set enrichment finds representative pathways for large gene sets, pathways are consolidated into representative pathway concepts. Three complementary, but different methods of pathway consolidation are explored. Enrichment Consolidation combines the set of the pathways enriched for the signature gene list through iterative combining of enriched pathways with other pathways with similar signature gene sets; Weighted Consolidation utilizes a Protein-Protein Interaction network based gene-weighting approach that finds clusters of both enriched and non-enriched pathways limited to the experiments' resultant gene list; and finally the de novo Consolidation method uses several measurements of pathway similarity, that finds static pathway clusters independent of any given experiment. We demonstrate that the three consolidation methods provide unified yet different functional insights of a resultant gene set derived from a genome-wide profiling experiment. Results from the methods are presented, demonstrating their applications in biological studies and comparing with a pathway web-based framework that also combines several pathway databases. Additionally a web-based consolidation framework that encompasses all three methods discussed in this paper, Pathway Distiller (http://cbbiweb.uthscsa.edu/PathwayDistiller), is established to allow researchers access to the methods and example microarray data described in this manuscript, and the ability to analyze their own gene list by using our unique consolidation methods. By combining several pathway systems, implementing different, but complementary pathway consolidation methods, and providing a user-friendly web-accessible tool, we have enabled users the ability to extract functional explanations of their genome wide experiments.

The cancer precision medicine knowledge base for structured clinical-grade mutations and interpretations.

PubMed

Huang, Linda; Fernandes, Helen; Zia, Hamid; Tavassoli, Peyman; Rennert, Hanna; Pisapia, David; Imielinski, Marcin; Sboner, Andrea; Rubin, Mark A; Kluk, Michael; Elemento, Olivier

2017-05-01

This paper describes the Precision Medicine Knowledge Base (PMKB; https://pmkb.weill.cornell.edu ), an interactive online application for collaborative editing, maintenance, and sharing of structured clinical-grade cancer mutation interpretations. PMKB was built using the Ruby on Rails Web application framework. Leveraging existing standards such as the Human Genome Variation Society variant description format, we implemented a data model that links variants to tumor-specific and tissue-specific interpretations. Key features of PMKB include support for all major variant types, standardized authentication, distinct user roles including high-level approvers, and detailed activity history. A REpresentational State Transfer (REST) application-programming interface (API) was implemented to query the PMKB programmatically. At the time of writing, PMKB contains 457 variant descriptions with 281 clinical-grade interpretations. The EGFR, BRAF, KRAS, and KIT genes are associated with the largest numbers of interpretable variants. PMKB's interpretations have been used in over 1500 AmpliSeq tests and 750 whole-exome sequencing tests. The interpretations are accessed either directly via the Web interface or programmatically via the existing API. An accurate and up-to-date knowledge base of genomic alterations of clinical significance is critical to the success of precision medicine programs. The open-access, programmatically accessible PMKB represents an important attempt at creating such a resource in the field of oncology. The PMKB was designed to help collect and maintain clinical-grade mutation interpretations and facilitate reporting for clinical cancer genomic testing. The PMKB was also designed to enable the creation of clinical cancer genomics automated reporting pipelines via an API. © The Author 2016. Published by Oxford University Press on behalf of the American Medical Informatics Association.

The cancer precision medicine knowledge base for structured clinical-grade mutations and interpretations

PubMed Central

Huang, Linda; Fernandes, Helen; Zia, Hamid; Tavassoli, Peyman; Rennert, Hanna; Pisapia, David; Imielinski, Marcin; Sboner, Andrea; Rubin, Mark A; Kluk, Michael

2017-01-01

Objective: This paper describes the Precision Medicine Knowledge Base (PMKB; https://pmkb.weill.cornell.edu), an interactive online application for collaborative editing, maintenance, and sharing of structured clinical-grade cancer mutation interpretations. Materials and Methods: PMKB was built using the Ruby on Rails Web application framework. Leveraging existing standards such as the Human Genome Variation Society variant description format, we implemented a data model that links variants to tumor-specific and tissue-specific interpretations. Key features of PMKB include support for all major variant types, standardized authentication, distinct user roles including high-level approvers, and detailed activity history. A REpresentational State Transfer (REST) application-programming interface (API) was implemented to query the PMKB programmatically. Results: At the time of writing, PMKB contains 457 variant descriptions with 281 clinical-grade interpretations. The EGFR, BRAF, KRAS, and KIT genes are associated with the largest numbers of interpretable variants. PMKB’s interpretations have been used in over 1500 AmpliSeq tests and 750 whole-exome sequencing tests. The interpretations are accessed either directly via the Web interface or programmatically via the existing API. Discussion: An accurate and up-to-date knowledge base of genomic alterations of clinical significance is critical to the success of precision medicine programs. The open-access, programmatically accessible PMKB represents an important attempt at creating such a resource in the field of oncology. Conclusion: The PMKB was designed to help collect and maintain clinical-grade mutation interpretations and facilitate reporting for clinical cancer genomic testing. The PMKB was also designed to enable the creation of clinical cancer genomics automated reporting pipelines via an API. PMID:27789569

Randomized, Controlled Trial of CBT Training for PTSD Providers

DTIC Science & Technology

2016-10-29

trial and comparative effectiveness study is to design, implement and evaluate a cost effective, web based self paced training program to provide skills...without web -centered supervision, may provide an effective means to train increasing numbers of mental health providers in relevant, evidence-based...in equal numbers to three parallel intervention condition: a) Web -based training plus web -centered supervision; b) Web - based training alone; and c

Databases and Web Tools for Cancer Genomics Study

PubMed Central

Yang, Yadong; Dong, Xunong; Xie, Bingbing; Ding, Nan; Chen, Juan; Li, Yongjun; Zhang, Qian; Qu, Hongzhu; Fang, Xiangdong

2015-01-01

Publicly-accessible resources have promoted the advance of scientific discovery. The era of genomics and big data has brought the need for collaboration and data sharing in order to make effective use of this new knowledge. Here, we describe the web resources for cancer genomics research and rate them on the basis of the diversity of cancer types, sample size, omics data comprehensiveness, and user experience. The resources reviewed include data repository and analysis tools; and we hope such introduction will promote the awareness and facilitate the usage of these resources in the cancer research community. PMID:25707591

SMART on FHIR Genomics: facilitating standardized clinico-genomic apps.

PubMed

Alterovitz, Gil; Warner, Jeremy; Zhang, Peijin; Chen, Yishen; Ullman-Cullere, Mollie; Kreda, David; Kohane, Isaac S

2015-11-01

Supporting clinical decision support for personalized medicine will require linking genome and phenome variants to a patient's electronic health record (EHR), at times on a vast scale. Clinico-genomic data standards will be needed to unify how genomic variant data are accessed from different sequencing systems. A specification for the basis of a clinic-genomic standard, building upon the current Health Level Seven International Fast Healthcare Interoperability Resources (FHIR®) standard, was developed. An FHIR application protocol interface (API) layer was attached to proprietary sequencing platforms and EHRs in order to expose gene variant data for presentation to the end-user. Three representative apps based on the SMART platform were built to test end-to-end feasibility, including integration of genomic and clinical data. Successful design, deployment, and use of the API was demonstrated and adopted by HL7 Clinical Genomics Workgroup. Feasibility was shown through development of three apps by various types of users with background levels and locations. This prototyping work suggests that an entirely data (and web) standards-based approach could prove both effective and efficient for advancing personalized medicine. © The Author 2015. Published by Oxford University Press on behalf of the American Medical Informatics Association. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

The emergence of commercial genomics: analysis of the rise of a biotechnology subsector during the Human Genome Project, 1990 to 2004.

PubMed

Wiechers, Ilse R; Perin, Noah C; Cook-Deegan, Robert

2013-01-01

Development of the commercial genomics sector within the biotechnology industry relied heavily on the scientific commons, public funding, and technology transfer between academic and industrial research. This study tracks financial and intellectual property data on genomics firms from 1990 through 2004, thus following these firms as they emerged in the era of the Human Genome Project and through the 2000 to 2001 market bubble. A database was created based on an early survey of genomics firms, which was expanded using three web-based biotechnology services, scientific journals, and biotechnology trade and technical publications. Financial data for publicly traded firms was collected through the use of four databases specializing in firm financials. Patent searches were conducted using firm names in the US Patent and Trademark Office website search engine and the DNA Patent Database. A biotechnology subsector of genomics firms emerged in parallel to the publicly funded Human Genome Project. Trends among top firms show that hiring, capital improvement, and research and development expenditures continued to grow after a 2000 to 2001 bubble. The majority of firms are small businesses with great diversity in type of research and development, products, and services provided. Over half the public firms holding patents have the majority of their intellectual property portfolio in DNA-based patents. These data allow estimates of investment, research and development expenditures, and jobs that paralleled the rise of genomics as a sector within biotechnology between 1990 and 2004.

Low-Bandwidth and Non-Compute Intensive Remote Identification of Microbes from Raw Sequencing Reads

PubMed Central

Gautier, Laurent; Lund, Ole

2013-01-01

Cheap DNA sequencing may soon become routine not only for human genomes but also for practically anything requiring the identification of living organisms from their DNA: tracking of infectious agents, control of food products, bioreactors, or environmental samples. We propose a novel general approach to the analysis of sequencing data where a reference genome does not have to be specified. Using a distributed architecture we are able to query a remote server for hints about what the reference might be, transferring a relatively small amount of data. Our system consists of a server with known reference DNA indexed, and a client with raw sequencing reads. The client sends a sample of unidentified reads, and in return receives a list of matching references. Sequences for the references can be retrieved and used for exhaustive computation on the reads, such as alignment. To demonstrate this approach we have implemented a web server, indexing tens of thousands of publicly available genomes and genomic regions from various organisms and returning lists of matching hits from query sequencing reads. We have also implemented two clients: one running in a web browser, and one as a python script. Both are able to handle a large number of sequencing reads and from portable devices (the browser-based running on a tablet), perform its task within seconds, and consume an amount of bandwidth compatible with mobile broadband networks. Such client-server approaches could develop in the future, allowing a fully automated processing of sequencing data and routine instant quality check of sequencing runs from desktop sequencers. A web access is available at http://tapir.cbs.dtu.dk. The source code for a python command-line client, a server, and supplementary data are available at http://bit.ly/1aURxkc. PMID:24391826

Low-bandwidth and non-compute intensive remote identification of microbes from raw sequencing reads.

PubMed

Gautier, Laurent; Lund, Ole

2013-01-01

Cheap DNA sequencing may soon become routine not only for human genomes but also for practically anything requiring the identification of living organisms from their DNA: tracking of infectious agents, control of food products, bioreactors, or environmental samples. We propose a novel general approach to the analysis of sequencing data where a reference genome does not have to be specified. Using a distributed architecture we are able to query a remote server for hints about what the reference might be, transferring a relatively small amount of data. Our system consists of a server with known reference DNA indexed, and a client with raw sequencing reads. The client sends a sample of unidentified reads, and in return receives a list of matching references. Sequences for the references can be retrieved and used for exhaustive computation on the reads, such as alignment. To demonstrate this approach we have implemented a web server, indexing tens of thousands of publicly available genomes and genomic regions from various organisms and returning lists of matching hits from query sequencing reads. We have also implemented two clients: one running in a web browser, and one as a python script. Both are able to handle a large number of sequencing reads and from portable devices (the browser-based running on a tablet), perform its task within seconds, and consume an amount of bandwidth compatible with mobile broadband networks. Such client-server approaches could develop in the future, allowing a fully automated processing of sequencing data and routine instant quality check of sequencing runs from desktop sequencers. A web access is available at http://tapir.cbs.dtu.dk. The source code for a python command-line client, a server, and supplementary data are available at http://bit.ly/1aURxkc.

Introduction to the fathead minnow genome browser and ...

EPA Pesticide Factsheets

Ab initio gene prediction and evidence alignment were used to produce the first annotations for the fathead minnow SOAPdenovo genome assembly. Additionally, a genome browser hosted at genome.setac.org provides simplified access to the annotation data in context with fathead minnow genomic sequence. This work is meant to extend the utility of fathead minnow genome as a resource and enable the continued development of this species as a model organism. The fathead minnow (Pimephales promelas) is a laboratory model organism widely used in regulatory toxicity testing and ecotoxicology research. Despite, the wealth of toxicological data for this organism, until recently genome scale information was lacking for the species, which limited the utility of the species for pathway-based toxicity testing and research. As part of a EPA Pathfinder Innovation Project, next generation sequencing was applied to generate a draft genome assembly, which was published in 2016. However, application of those genome-scale sequencing resources was still limited by the lack of available gene annotations for fathead minnow. Here we report on development of a first generation genome annotation for fathead minnow and the dissemination of that information through a web-based browser that makes it easy to search for genes of interest, extract the corresponding sequence, identify intron and exon boundaries and regulatory regions, and align the computationally predicted genes with other supporti

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

DoOPSearch: a web-based tool for finding and analysing common conserved motifs in the promoter regions of different chordate and plant genes

PubMed Central

Sebestyén, Endre; Nagy, Tibor; Suhai, Sándor; Barta, Endre

2009-01-01

Background The comparative genomic analysis of a large number of orthologous promoter regions of the chordate and plant genes from the DoOP databases shows thousands of conserved motifs. Most of these motifs differ from any known transcription factor binding site (TFBS). To identify common conserved motifs, we need a specific tool to be able to search amongst them. Since conserved motifs from the DoOP databases are linked to genes, the result of such a search can give a list of genes that are potentially regulated by the same transcription factor(s). Results We have developed a new tool called DoOPSearch for the analysis of the conserved motifs in the promoter regions of chordate or plant genes. We used the orthologous promoters of the DoOP database to extract thousands of conserved motifs from different taxonomic groups. The advantage of this approach is that different sets of conserved motifs might be found depending on how broad the taxonomic coverage of the underlying orthologous promoter sequence collection is (consider e.g. primates vs. mammals or Brassicaceae vs. Viridiplantae). The DoOPSearch tool allows the users to search these motif collections or the promoter regions of DoOP with user supplied query sequences or any of the conserved motifs from the DoOP database. To find overrepresented gene ontologies, the gene lists obtained can be analysed further using a modified version of the GeneMerge program. Conclusion We present here a comparative genomics based promoter analysis tool. Our system is based on a unique collection of conserved promoter motifs characteristic of different taxonomic groups. We offer both a command line and a web-based tool for searching in these motif collections using user specified queries. These can be either short promoter sequences or consensus sequences of known transcription factor binding sites. The GeneMerge analysis of the search results allows the user to identify statistically overrepresented Gene Ontology terms that might provide a clue on the function of the motifs and genes. PMID:19534755

Refinement of light-responsive transcript lists using rice oligonucleotide arrays: evaluation of gene-redundancy.

PubMed

Jung, Ki-Hong; Dardick, Christopher; Bartley, Laura E; Cao, Peijian; Phetsom, Jirapa; Canlas, Patrick; Seo, Young-Su; Shultz, Michael; Ouyang, Shu; Yuan, Qiaoping; Frank, Bryan C; Ly, Eugene; Zheng, Li; Jia, Yi; Hsia, An-Ping; An, Kyungsook; Chou, Hui-Hsien; Rocke, David; Lee, Geun Cheol; Schnable, Patrick S; An, Gynheung; Buell, C Robin; Ronald, Pamela C

2008-10-06

Studies of gene function are often hampered by gene-redundancy, especially in organisms with large genomes such as rice (Oryza sativa). We present an approach for using transcriptomics data to focus functional studies and address redundancy. To this end, we have constructed and validated an inexpensive and publicly available rice oligonucleotide near-whole genome array, called the rice NSF45K array. We generated expression profiles for light- vs. dark-grown rice leaf tissue and validated the biological significance of the data by analyzing sources of variation and confirming expression trends with reverse transcription polymerase chain reaction. We examined trends in the data by evaluating enrichment of gene ontology terms at multiple false discovery rate thresholds. To compare data generated with the NSF45K array with published results, we developed publicly available, web-based tools (www.ricearray.org). The Oligo and EST Anatomy Viewer enables visualization of EST-based expression profiling data for all genes on the array. The Rice Multi-platform Microarray Search Tool facilitates comparison of gene expression profiles across multiple rice microarray platforms. Finally, we incorporated gene expression and biochemical pathway data to reduce the number of candidate gene products putatively participating in the eight steps of the photorespiration pathway from 52 to 10, based on expression levels of putatively functionally redundant genes. We confirmed the efficacy of this method to cope with redundancy by correctly predicting participation in photorespiration of a gene with five paralogs. Applying these methods will accelerate rice functional genomics.

A Multipurpose Toolkit to Enable Advanced Genome Engineering in Plants[OPEN

PubMed Central

Gil-Humanes, Javier; Čegan, Radim; Kono, Thomas J.Y.; Konečná, Eva; Belanto, Joseph J.; Starker, Colby G.

2017-01-01

We report a comprehensive toolkit that enables targeted, specific modification of monocot and dicot genomes using a variety of genome engineering approaches. Our reagents, based on transcription activator-like effector nucleases (TALENs) and the clustered regularly interspaced short palindromic repeats (CRISPR)/Cas9 system, are systematized for fast, modular cloning and accommodate diverse regulatory sequences to drive reagent expression. Vectors are optimized to create either single or multiple gene knockouts and large chromosomal deletions. Moreover, integration of geminivirus-based vectors enables precise gene editing through homologous recombination. Regulation of transcription is also possible. A Web-based tool streamlines vector selection and construction. One advantage of our platform is the use of the Csy-type (CRISPR system yersinia) ribonuclease 4 (Csy4) and tRNA processing enzymes to simultaneously express multiple guide RNAs (gRNAs). For example, we demonstrate targeted deletions in up to six genes by expressing 12 gRNAs from a single transcript. Csy4 and tRNA expression systems are almost twice as effective in inducing mutations as gRNAs expressed from individual RNA polymerase III promoters. Mutagenesis can be further enhanced 2.5-fold by incorporating the Trex2 exonuclease. Finally, we demonstrate that Cas9 nickases induce gene targeting at frequencies comparable to native Cas9 when they are delivered on geminivirus replicons. The reagents have been successfully validated in tomato (Solanum lycopersicum), tobacco (Nicotiana tabacum), Medicago truncatula, wheat (Triticum aestivum), and barley (Hordeum vulgare). PMID:28522548

A multi-purpose toolkit to enable advanced genome engineering in plants

DOE PAGES

Cermak, Tomas; Curtin, Shaun J.; Gil-Humanes, Javier; ...

2017-05-18

Here, we report a comprehensive toolkit that enables targeted, specific modification of monocot and dicot genomes using a variety of genome engineering approaches. Our reagents, based on Transcription Activator-Like Effector Nucleases TALENs and the Clustered Regularly Interspaced Short Palindromic Repeats (CRISPR)/Cas9 system, are systematized for fast, modular cloning and accommodate diverse regulatory sequences to drive reagent expression. Vectors are optimized to create either single or multiple gene knockouts and large chromosomal deletions. Moreover, integration of geminivirus-based vectors enables precise gene editing through homologous recombination. Regulation of transcription is also possible. A web-based tool streamlines vector selection and construction. One advantagemore » of our platform is the use of the Csy-type (CRISPR system yersinia) ribonuclease 4 Csy4 and tRNA processing enzymes to simultaneously express multiple guide RNAs (gRNAs). For example, we demonstrate targeted deletions in up to six genes by expressing twelve gRNAs from a single transcript. Csy4 and tRNA expression systems are almost twice as effective in inducing mutations as gRNAs expressed from individual RNA polymerase III promoters. Mutagenesis can be further enhanced 2.5-fold by incorporating the Trex2 exonuclease. Finally, we demonstrate that Cas9 nickases induce gene targeting at frequencies comparable to native Cas9 when they are delivered on geminivirus replicons. The reagents have been successfully validated in tomato (Solanum lycopersicum), tobacco (Nicotiana tabacum), Medicago truncatula, wheat (Triticum aestivum), and barley (Hordeum vulgare).« less

A multi-purpose toolkit to enable advanced genome engineering in plants

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

Cermak, Tomas; Curtin, Shaun J.; Gil-Humanes, Javier

Here, we report a comprehensive toolkit that enables targeted, specific modification of monocot and dicot genomes using a variety of genome engineering approaches. Our reagents, based on Transcription Activator-Like Effector Nucleases TALENs and the Clustered Regularly Interspaced Short Palindromic Repeats (CRISPR)/Cas9 system, are systematized for fast, modular cloning and accommodate diverse regulatory sequences to drive reagent expression. Vectors are optimized to create either single or multiple gene knockouts and large chromosomal deletions. Moreover, integration of geminivirus-based vectors enables precise gene editing through homologous recombination. Regulation of transcription is also possible. A web-based tool streamlines vector selection and construction. One advantagemore » of our platform is the use of the Csy-type (CRISPR system yersinia) ribonuclease 4 Csy4 and tRNA processing enzymes to simultaneously express multiple guide RNAs (gRNAs). For example, we demonstrate targeted deletions in up to six genes by expressing twelve gRNAs from a single transcript. Csy4 and tRNA expression systems are almost twice as effective in inducing mutations as gRNAs expressed from individual RNA polymerase III promoters. Mutagenesis can be further enhanced 2.5-fold by incorporating the Trex2 exonuclease. Finally, we demonstrate that Cas9 nickases induce gene targeting at frequencies comparable to native Cas9 when they are delivered on geminivirus replicons. The reagents have been successfully validated in tomato (Solanum lycopersicum), tobacco (Nicotiana tabacum), Medicago truncatula, wheat (Triticum aestivum), and barley (Hordeum vulgare).« less

Genomics Virtual Laboratory: A Practical Bioinformatics Workbench for the Cloud

PubMed Central

Afgan, Enis; Sloggett, Clare; Goonasekera, Nuwan; Makunin, Igor; Benson, Derek; Crowe, Mark; Gladman, Simon; Kowsar, Yousef; Pheasant, Michael; Horst, Ron; Lonie, Andrew

2015-01-01

Background Analyzing high throughput genomics data is a complex and compute intensive task, generally requiring numerous software tools and large reference data sets, tied together in successive stages of data transformation and visualisation. A computational platform enabling best practice genomics analysis ideally meets a number of requirements, including: a wide range of analysis and visualisation tools, closely linked to large user and reference data sets; workflow platform(s) enabling accessible, reproducible, portable analyses, through a flexible set of interfaces; highly available, scalable computational resources; and flexibility and versatility in the use of these resources to meet demands and expertise of a variety of users. Access to an appropriate computational platform can be a significant barrier to researchers, as establishing such a platform requires a large upfront investment in hardware, experience, and expertise. Results We designed and implemented the Genomics Virtual Laboratory (GVL) as a middleware layer of machine images, cloud management tools, and online services that enable researchers to build arbitrarily sized compute clusters on demand, pre-populated with fully configured bioinformatics tools, reference datasets and workflow and visualisation options. The platform is flexible in that users can conduct analyses through web-based (Galaxy, RStudio, IPython Notebook) or command-line interfaces, and add/remove compute nodes and data resources as required. Best-practice tutorials and protocols provide a path from introductory training to practice. The GVL is available on the OpenStack-based Australian Research Cloud (http://nectar.org.au) and the Amazon Web Services cloud. The principles, implementation and build process are designed to be cloud-agnostic. Conclusions This paper provides a blueprint for the design and implementation of a cloud-based Genomics Virtual Laboratory. We discuss scope, design considerations and technical and logistical constraints, and explore the value added to the research community through the suite of services and resources provided by our implementation. PMID:26501966

Genomics Virtual Laboratory: A Practical Bioinformatics Workbench for the Cloud.

PubMed

Afgan, Enis; Sloggett, Clare; Goonasekera, Nuwan; Makunin, Igor; Benson, Derek; Crowe, Mark; Gladman, Simon; Kowsar, Yousef; Pheasant, Michael; Horst, Ron; Lonie, Andrew

2015-01-01

Analyzing high throughput genomics data is a complex and compute intensive task, generally requiring numerous software tools and large reference data sets, tied together in successive stages of data transformation and visualisation. A computational platform enabling best practice genomics analysis ideally meets a number of requirements, including: a wide range of analysis and visualisation tools, closely linked to large user and reference data sets; workflow platform(s) enabling accessible, reproducible, portable analyses, through a flexible set of interfaces; highly available, scalable computational resources; and flexibility and versatility in the use of these resources to meet demands and expertise of a variety of users. Access to an appropriate computational platform can be a significant barrier to researchers, as establishing such a platform requires a large upfront investment in hardware, experience, and expertise. We designed and implemented the Genomics Virtual Laboratory (GVL) as a middleware layer of machine images, cloud management tools, and online services that enable researchers to build arbitrarily sized compute clusters on demand, pre-populated with fully configured bioinformatics tools, reference datasets and workflow and visualisation options. The platform is flexible in that users can conduct analyses through web-based (Galaxy, RStudio, IPython Notebook) or command-line interfaces, and add/remove compute nodes and data resources as required. Best-practice tutorials and protocols provide a path from introductory training to practice. The GVL is available on the OpenStack-based Australian Research Cloud (http://nectar.org.au) and the Amazon Web Services cloud. The principles, implementation and build process are designed to be cloud-agnostic. This paper provides a blueprint for the design and implementation of a cloud-based Genomics Virtual Laboratory. We discuss scope, design considerations and technical and logistical constraints, and explore the value added to the research community through the suite of services and resources provided by our implementation.

ABrowse--a customizable next-generation genome browser framework.

PubMed

Kong, Lei; Wang, Jun; Zhao, Shuqi; Gu, Xiaocheng; Luo, Jingchu; Gao, Ge

2012-01-05

With the rapid growth of genome sequencing projects, genome browser is becoming indispensable, not only as a visualization system but also as an interactive platform to support open data access and collaborative work. Thus a customizable genome browser framework with rich functions and flexible configuration is needed to facilitate various genome research projects. Based on next-generation web technologies, we have developed a general-purpose genome browser framework ABrowse which provides interactive browsing experience, open data access and collaborative work support. By supporting Google-map-like smooth navigation, ABrowse offers end users highly interactive browsing experience. To facilitate further data analysis, multiple data access approaches are supported for external platforms to retrieve data from ABrowse. To promote collaborative work, an online user-space is provided for end users to create, store and share comments, annotations and landmarks. For data providers, ABrowse is highly customizable and configurable. The framework provides a set of utilities to import annotation data conveniently. To build ABrowse on existing annotation databases, data providers could specify SQL statements according to database schema. And customized pages for detailed information display of annotation entries could be easily plugged in. For developers, new drawing strategies could be integrated into ABrowse for new types of annotation data. In addition, standard web service is provided for data retrieval remotely, providing underlying machine-oriented programming interface for open data access. ABrowse framework is valuable for end users, data providers and developers by providing rich user functions and flexible customization approaches. The source code is published under GNU Lesser General Public License v3.0 and is accessible at http://www.abrowse.org/. To demonstrate all the features of ABrowse, a live demo for Arabidopsis thaliana genome has been built at http://arabidopsis.cbi.edu.cn/.

Metagenomes of the Picoalga Bathycoccus from the Chile Coastal Upwelling

PubMed Central

Vaulot, Daniel; Lepère, Cécile; Toulza, Eve; De la Iglesia, Rodrigo; Poulain, Julie; Gaboyer, Frédéric; Moreau, Hervé; Vandepoele, Klaas; Ulloa, Osvaldo; Gavory, Frederick; Piganeau, Gwenael

2012-01-01

Among small photosynthetic eukaryotes that play a key role in oceanic food webs, picoplanktonic Mamiellophyceae such as Bathycoccus, Micromonas, and Ostreococcus are particularly important in coastal regions. By using a combination of cell sorting by flow cytometry, whole genome amplification (WGA), and 454 pyrosequencing, we obtained metagenomic data for two natural picophytoplankton populations from the coastal upwelling waters off central Chile. About 60% of the reads of each sample could be mapped to the genome of Bathycoccus strain from the Mediterranean Sea (RCC1105), representing a total of 9 Mbp (sample T142) and 13 Mbp (sample T149) of non-redundant Bathycoccus genome sequences. WGA did not amplify all regions uniformly, resulting in unequal coverage along a given chromosome and between chromosomes. The identity at the DNA level between the metagenomes and the cultured genome was very high (96.3% identical bases for the three larger chromosomes over a 360 kbp alignment). At least two to three different genotypes seemed to be present in each natural sample based on read mapping to Bathycoccus RCC1105 genome. PMID:22745802

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.

TRFolder-W: a web server for telomerase RNA structure prediction in yeast genomes.

PubMed

Zhang, Dong; Xue, Xingran; Malmberg, Russell L; Cai, Liming

2012-10-15

TRFolder-W is a web server capable of predicting core structures of telomerase RNA (TR) in yeast genomes. TRFolder is a command-line Python toolkit for TR-specific structure prediction. We developed a web-version built on the django web framework, leveraging the work done previously, to include enhancements to increase flexibility of usage. To date, there are five core sub-structures commonly found in TR of fungal species, which are the template region, downstream pseudoknot, boundary element, core-closing stem and triple helix. The aim of TRFolder-W is to use the five core structures as fundamental units to predict potential TR genes for yeast, and to provide a user-friendly interface. Moreover, the application of TRFolder-W can be extended to predict the characteristic structure on species other than fungal species. The web server TRFolder-W is available at http://rna-informatics.uga.edu/?f=software&p=TRFolder-w.

Do online prognostication tools represent a valid alternative to genomic profiling in the context of adjuvant treatment of early breast cancer? A systematic review of the literature.

PubMed

El Hage Chehade, Hiba; Wazir, Umar; Mokbel, Kinan; Kasem, Abdul; Mokbel, Kefah

2018-01-01

Decision-making regarding adjuvant chemotherapy has been based on clinical and pathological features. However, such decisions are seldom consistent. Web-based predictive models have been developed using data from cancer registries to help determine the need for adjuvant therapy. More recently, with the recognition of the heterogenous nature of breast cancer, genomic assays have been developed to aid in the therapeutic decision-making. We have carried out a comprehensive literature review regarding online prognostication tools and genomic assays to assess whether online tools could be used as valid alternatives to genomic profiling in decision-making regarding adjuvant therapy in early breast cancer. Breast cancer has been recently recognized as a heterogenous disease based on variations in molecular characteristics. Online tools are valuable in guiding adjuvant treatment, especially in resource constrained countries. However, in the era of personalized therapy, molecular profiling appears to be superior in predicting clinical outcome and guiding therapy. Copyright © 2017 Elsevier Inc. All rights reserved.

Genomic resources for songbird research and their use in characterizing gene expression during brain development

PubMed Central

Li, XiaoChing; Wang, Xiu-Jie; Tannenhauser, Jonathan; Podell, Sheila; Mukherjee, Piali; Hertel, Moritz; Biane, Jeremy; Masuda, Shoko; Nottebohm, Fernando; Gaasterland, Terry

2007-01-01

Vocal learning and neuronal replacement have been studied extensively in songbirds, but until recently, few molecular and genomic tools for songbird research existed. Here we describe new molecular/genomic resources developed in our laboratory. We made cDNA libraries from zebra finch (Taeniopygia guttata) brains at different developmental stages. A total of 11,000 cDNA clones from these libraries, representing 5,866 unique gene transcripts, were randomly picked and sequenced from the 3′ ends. A web-based database was established for clone tracking, sequence analysis, and functional annotations. Our cDNA libraries were not normalized. Sequencing ESTs without normalization produced many developmental stage-specific sequences, yielding insights into patterns of gene expression at different stages of brain development. In particular, the cDNA library made from brains at posthatching day 30–50, corresponding to the period of rapid song system development and song learning, has the most diverse and richest set of genes expressed. We also identified five microRNAs whose sequences are highly conserved between zebra finch and other species. We printed cDNA microarrays and profiled gene expression in the high vocal center of both adult male zebra finches and canaries (Serinus canaria). Genes differentially expressed in the high vocal center were identified from the microarray hybridization results. Selected genes were validated by in situ hybridization. Networks among the regulated genes were also identified. These resources provide songbird biologists with tools for genome annotation, comparative genomics, and microarray gene expression analysis. PMID:17426146

Whole-genome-based Mycobacterium tuberculosis surveillance: a standardized, portable, and expandable approach.

PubMed

Kohl, Thomas A; Diel, Roland; Harmsen, Dag; Rothgänger, Jörg; Walter, Karen Meywald; Merker, Matthias; Weniger, Thomas; Niemann, Stefan

2014-07-01

Whole-genome sequencing (WGS) allows for effective tracing of Mycobacterium tuberculosis complex (MTBC) (tuberculosis pathogens) transmission. However, it is difficult to standardize and, therefore, is not yet employed for interlaboratory prospective surveillance. To allow its widespread application, solutions for data standardization and storage in an easily expandable database are urgently needed. To address this question, we developed a core genome multilocus sequence typing (cgMLST) scheme for clinical MTBC isolates using the Ridom SeqSphere(+) software, which transfers the genome-wide single nucleotide polymorphism (SNP) diversity into an allele numbering system that is standardized, portable, and not computationally intensive. To test its performance, we performed WGS analysis of 26 isolates with identical IS6110 DNA fingerprints and spoligotyping patterns from a longitudinal outbreak in the federal state of Hamburg, Germany (notified between 2001 and 2010). The cgMLST approach (3,041 genes) discriminated the 26 strains with a resolution comparable to that of SNP-based WGS typing (one major cluster of 22 identical or closely related and four outlier isolates with at least 97 distinct SNPs or 63 allelic variants). Resulting tree topologies are highly congruent and grouped the isolates in both cases analogously. Our data show that SNP- and cgMLST-based WGS analyses facilitate high-resolution discrimination of longitudinal MTBC outbreaks. cgMLST allows for a meaningful epidemiological interpretation of the WGS genotyping data. It enables standardized WGS genotyping for epidemiological investigations, e.g., on the regional public health office level, and the creation of web-accessible databases for global TB surveillance with an integrated early warning system. Copyright © 2014, American Society for Microbiology. All Rights Reserved.

Practice and effectiveness of web-based problem-based learning approach in a large class-size system: A comparative study.

PubMed

Ding, Yongxia; Zhang, Peili

2018-06-12

Problem-based learning (PBL) is an effective and highly efficient teaching approach that is extensively applied in education systems across a variety of countries. This study aimed to investigate the effectiveness of web-based PBL teaching pedagogies in large classes. The cluster sampling method was used to separate two college-level nursing student classes (graduating class of 2013) into two groups. The experimental group (n = 162) was taught using a web-based PBL teaching approach, while the control group (n = 166) was taught using conventional teaching methods. We subsequently assessed the satisfaction of the experimental group in relation to the web-based PBL teaching mode. This assessment was performed following comparison of teaching activity outcomes pertaining to exams and self-learning capacity between the two groups. When compared with the control group, the examination scores and self-learning capabilities were significantly higher in the experimental group (P < 0.01) compared with the control group. In addition, 92.6% of students in the experimental group expressed satisfaction with the new web-based PBL teaching approach. In a large class-size teaching environment, the web-based PBL teaching approach appears to be more optimal than traditional teaching methods. These results demonstrate the effectiveness of web-based teaching technologies in problem-based learning. Copyright © 2018. Published by Elsevier Ltd.

D-GENIES: dot plot large genomes in an interactive, efficient and simple way.

PubMed

Cabanettes, Floréal; Klopp, Christophe

2018-01-01

Dot plots are widely used to quickly compare sequence sets. They provide a synthetic similarity overview, highlighting repetitions, breaks and inversions. Different tools have been developed to easily generated genomic alignment dot plots, but they are often limited in the input sequence size. D-GENIES is a standalone and web application performing large genome alignments using minimap2 software package and generating interactive dot plots. It enables users to sort query sequences along the reference, zoom in the plot and download several image, alignment or sequence files. D-GENIES is an easy-to-install, open-source software package (GPL) developed in Python and JavaScript. The source code is available at https://github.com/genotoul-bioinfo/dgenies and it can be tested at http://dgenies.toulouse.inra.fr/.

A SNP panel and online tool for checking genotype concordance through comparing QR codes.

PubMed

Du, Yonghong; Martin, Joshua S; McGee, John; Yang, Yuchen; Liu, Eric Yi; Sun, Yingrui; Geihs, Matthias; Kong, Xuejun; Zhou, Eric Lingfeng; Li, Yun; Huang, Jie

2017-01-01

In the current precision medicine era, more and more samples get genotyped and sequenced. Both researchers and commercial companies expend significant time and resources to reduce the error rate. However, it has been reported that there is a sample mix-up rate of between 0.1% and 1%, not to mention the possibly higher mix-up rate during the down-stream genetic reporting processes. Even on the low end of this estimate, this translates to a significant number of mislabeled samples, especially over the projected one billion people that will be sequenced within the next decade. Here, we first describe a method to identify a small set of Single nucleotide polymorphisms (SNPs) that can uniquely identify a personal genome, which utilizes allele frequencies of five major continental populations reported in the 1000 genomes project and the ExAC Consortium. To make this panel more informative, we added four SNPs that are commonly used to predict ABO blood type, and another two SNPs that are capable of predicting sex. We then implement a web interface (http://qrcme.tech), nicknamed QRC (for QR code based Concordance check), which is capable of extracting the relevant ID SNPs from a raw genetic data, coding its genotype as a quick response (QR) code, and comparing QR codes to report the concordance of underlying genetic datasets. The resulting 80 fingerprinting SNPs represent a significant decrease in complexity and the number of markers used for genetic data labelling and tracking. Our method and web tool is easily accessible to both researchers and the general public who consider the accuracy of complex genetic data as a prerequisite towards precision medicine.

A SNP panel and online tool for checking genotype concordance through comparing QR codes

PubMed Central

Du, Yonghong; Martin, Joshua S.; McGee, John; Yang, Yuchen; Liu, Eric Yi; Sun, Yingrui; Geihs, Matthias; Kong, Xuejun; Zhou, Eric Lingfeng; Li, Yun

2017-01-01

In the current precision medicine era, more and more samples get genotyped and sequenced. Both researchers and commercial companies expend significant time and resources to reduce the error rate. However, it has been reported that there is a sample mix-up rate of between 0.1% and 1%, not to mention the possibly higher mix-up rate during the down-stream genetic reporting processes. Even on the low end of this estimate, this translates to a significant number of mislabeled samples, especially over the projected one billion people that will be sequenced within the next decade. Here, we first describe a method to identify a small set of Single nucleotide polymorphisms (SNPs) that can uniquely identify a personal genome, which utilizes allele frequencies of five major continental populations reported in the 1000 genomes project and the ExAC Consortium. To make this panel more informative, we added four SNPs that are commonly used to predict ABO blood type, and another two SNPs that are capable of predicting sex. We then implement a web interface (http://qrcme.tech), nicknamed QRC (for QR code based Concordance check), which is capable of extracting the relevant ID SNPs from a raw genetic data, coding its genotype as a quick response (QR) code, and comparing QR codes to report the concordance of underlying genetic datasets. The resulting 80 fingerprinting SNPs represent a significant decrease in complexity and the number of markers used for genetic data labelling and tracking. Our method and web tool is easily accessible to both researchers and the general public who consider the accuracy of complex genetic data as a prerequisite towards precision medicine. PMID:28926565

Surveying ourselves: examining the use of a web-based approach for a physician survey.

PubMed

Matteson, Kristen A; Anderson, Britta L; Pinto, Stephanie B; Lopes, Vrishali; Schulkin, Jay; Clark, Melissa A

2011-12-01

A survey was distributed, using a sequential mixed-mode approach, to a national sample of obstetrician-gynecologists. Differences between responses to the web-based mode and the on-paper mode were compared to determine if there were systematic differences between respondents. Only two differences in respondents between the two modes were identified. University-based physicians were more likely to complete the web-based mode than private practice physicians. Mail respondents reported a greater volume of endometrial ablations compared to online respondents. The web-based mode had better data quality than the paper-based mailed mode in terms of less missing and inappropriate responses. Together, these findings suggest that, although a few differences were identified, the web-based survey mode attained adequate representativeness and improved data quality. Given the metrics examined for this study, exclusive use of web-based data collection may be appropriate for physician surveys with a minimal reduction in sample coverage and without a reduction in data quality.