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http://www.dpvweb.net/

DPVweb provides a central source of information about viruses, viroids and satellites of plants, fungi and protozoa. Comprehensive taxonomic information, including brief descriptions of each family and genus, and classified lists of virus sequences are provided. The database also holds detailed, curated, information for all sequences of viruses, viroids and satellites of plants, fungi and protozoa that are complete or that contain at least one complete gene. For comparative purposes, it also contains a single representative sequence of all other fully sequenced virus species with an RNA or single-stranded DNA genome. The start and end positions of each feature (gene, non-translated region and the like) have been recorded and checked for accuracy. As far as possible, nomenclature for genes and proteins are standardized within genera and families. Sequences of features (either as DNA or amino acid sequences) can be directly downloaded from the website in FASTA format. The sequence information can also be accessed via client software for PC computers (freely downloadable from the website) that enable users to make an easy selection of sequences and features of a chosen virus for further analyses. The public sequence databases contain vast amounts of data on virus genomes but accessing and comparing the data, except for relatively small sets of related viruses can be very time consuming. The procedure is made difficult because some of the sequences on these databases are incorrectly named, poorly annotated or redundant. The NCBI Reference Sequence project (1) provides a comprehensive, integrated, non-redundant set of sequences, including genomic DNA, transcript (RNA) and protein products, for major research organisms. This now includes curated information for a single sequence of each fully sequenced virus species. While this is a welcome development, it can only deal with complete sequences. An important feature of DPV is the opportunity to access genes (and other features) of multiple sequences quickly and accurately. Thus, for example, it is easy to obtain the nucleotide or amino acid sequences of all the available accessions of the coat protein gene of a given virus species or for a group of viruses. To increase its usefulness further, DPVweb also contains a single representative sequence of all other fully sequenced virus species with an RNA or single-stranded DNA (ssDNA) genome. Sponsors: This site is supported by the Association of Applied Biologists and the Zhejiang Academy of Agricultural Sciences, Hangzhou, People''s Republic of China.

Proper citation: Descriptions of Plant Viruses (RRID:SCR_006656) Copy   

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http://bioconductor.org/packages/bioc/html/GeneAnswers.html

GeneAnswers provide an integrated tool for given genes biological or medical interpretation. It includes statistical test of given genes and specified categories. Microarray techniques have been widely employed in genomic scale studies for more than one decade. The standard analysis of microarray data is to filter out a group of genes from thousands of probes by certain statistical criteria. These genes are usually called significantly differentially expressed genes. Recently, next generation sequencing (NGS) is gradually adopted to explore gene transcription, methylation, etc. Also a gene list can be obtained by NGS preliminary data analysis. However, this type of information is not enough to understand the potential linkage between identified genes and interested functions. The integrated functional and pathway analysis with gene expression data would be very helpful for researchers to interpret the relationship between the identified genes and proposed biological or medical functions and pathways. The GeneAnswers package provides an integrated solution for a group of genes and specified categories (biological or medical functions, such as Gene Ontology, Disease Ontology, KEGG, etc) to reveal the potential relationship between them by means of statistical methods, and make user-friendly network visualization to interpret the results. Besides the package has a function to combine gene expression profile and category analysis together by outputting concept-gene cross tables, keywords query on NCBI Entrez Gene and application of human based Disease ontology analysis of given genes from other species can help people to understand or discover potential connection between genes and functions. Sponsors: This project was supported in part by Award Number UL1RR025741 from the National Center for Research Resources.

Proper citation: GeneAnswers (RRID:SCR_006498) Copy   

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http://www.molecularevolution.org/software/genomics/velvet

THIS RESOURCE IS NO LONGER IN SERVICE. Documented on February 28,2023. Software package as de novo genomic assembler for short read sequencing technologies using de Bruijn graphs. Takes in short read sequences, removes errors, then produces high quality unique contigs, retrieves repeated areas between contigs. Can leverage very short reads in combination with read pairs to produce useful assemblies. Operating system Unix/Linux., THIS RESOURCE IS NO LONGER IN SERVICE. Documented on September 16,2025.

Proper citation: Velvet (RRID:SCR_010755) Copy   

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http://homer.ucsd.edu/

Software tools for Motif Discovery and next-gen sequencing analysis. Used for analyzing ChIP-Seq, GRO-Seq, RNA-Seq, DNase-Seq, Hi-C and numerous other types of functional genomics sequencing data sets. Collection of command line programs for unix style operating systems written in Perl and C++.

Proper citation: HOMER (RRID:SCR_010881) Copy   

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http://tagcleaner.sourceforge.net/

A software tool which can automatically detect and efficiently remove tag sequences from genomic and metagenomic datasets.

Proper citation: TagCleaner (RRID:SCR_011846) Copy   

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https://www.q2labsolutions.com/genomics-laboratories

Core provides whole genome to focused set gene expression and genotyping assays along with DNA sequencings services, sequence enrichment technologies and bioinformatics support. Platforms utilized include Affymetrix GeneChip, Agilent Sure Select, Fluidigm Access Arrays, Illumina BeadChip, iScan, Genome Analyzer and Hi-Seq, RainDance Technologies RDT 1000 and, the Pacific Biosciences PacBio RS. Expression Analysis offers solutions for challenging specimens such as whole blood and FFPE tissues, as well as nucleic acid isolation and data analysis services.

Proper citation: Q Squared Solutions Expression Analysis (RRID:SCR_012497) Copy   

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http://www.viprbrc.org/brc/home.do?decorator=vipr

Provides searchable public repository of genomic, proteomic and other research data for different strains of pathogenic viruses along with suite of tools for analyzing data. Data can be shared, aggregated, analyzed using ViPR tools, and downloaded for local analysis. ViPR is an NIAID-funded resource that support the research of viral pathogens in the NIAID Category A-C Priority Pathogen lists and those causing (re)emerging infectious diseases. It provides a dedicated gateway to SARS-CoV-2 data that integrates data from external sources (GenBank, UniProt, Immune Epitope Database, Protein Data Bank), direct submissions, analysis pipelines and expert curation, and provides a suite of bioinformatics analysis and visualization tools for virology research.

Proper citation: Virus Pathogen Resource (ViPR) (RRID:SCR_012983) Copy   

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http://www.dkfz.de/en/epidemiologie-krebserkrankungen/software/software.html

THIS RESOURCE IS NO LONGER IN SERVICE. Documented on May 24,2023. Software program that performs estimation of power and sample sizes required to detect genetic and environmental main, as well as gene-environment interaction (GxE) effects in indirect matched case-control studies (1:1 matching). When the hypothesis of GxE is tested, power/sample size will be estimated for the detection of GxE, as well as for the detection of genetic and environmental marginal effects. Furthermore, power estimation is implemented for the joint test of genetic marginal and GxE effects (Kraft P et al., 2007). Power and sample size estimations are based on Gauderman''s (2002) asymptotic approach for power and sample size estimations in direct studies of GxE. Hardy-Weinberg equilibrium and independence of genotypes and environmental exposures in the population are assumed. The estimates are based on genotypic codes (G=1 (G=0) for individuals who carry a (non-) risk genotype), which depend on the mode of inheritance (dominant, recessive, or multiplicative). A conditional logistic regression approach is used, which employs a likelihood-ratio test with respect to a biallelic candidate SNP, a binary environmental factor (E=1 (E=0) in (un)exposed individuals), and the interaction between these components. (entry from Genetic Analysis Software)

Proper citation: PIAGE (RRID:SCR_013124) Copy   

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http://bioinformatics.ust.hk/BOOST.html

Software application (entry from Genetic Analysis Software) for a method for detecting gene-gene interactions. It allows examining all pairwise interactions in genome-wide case-control studies.

Proper citation: BOOST (RRID:SCR_013133) Copy   

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http://PlasmoDB.org

Functional genomic database for malaria parasites. Database for Plasmodium spp. Provides resource for data analysis and visualization in gene-by-gene or genome-wide scale. PlasmoDB 5.5 contains annotated genomes, evidence of transcription, proteomics evidence, protein function evidence, population biology and evolution data. Data can be queried by selecting from query grid or drop down menus. Results can be combined with each other on query history page. Search results can be downloaded with associated functional data and registered users can store their query history for future retrieval or analysis.Key community database for malaria researchers, intersecting many types of laboratory and computational data, aggregated by gene.

Proper citation: PlasmoDB (RRID:SCR_013331) Copy   

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http://folk.uio.no/thoree/FEST/

An R package for simulations and likelihood calculations of pair-wise family relationships using DNA marker data. (entry from Genetic Analysis Software)

Proper citation: R/FEST (RRID:SCR_013347) Copy   

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http://discover.nci.nih.gov/gominer/

GoMiner is a tool for biological interpretation of "omic" data including data from gene expression microarrays. Omic experiments often generate lists of dozens or hundreds of genes that differ in expression between samples, raising the question, What does it all mean biologically? To answer this question, GoMiner leverages the Gene Ontology (GO) to identify the biological processes, functions and components represented in these lists. Instead of analyzing microarray results with a gene-by-gene approach, GoMiner classifies the genes into biologically coherent categories and assesses these categories. The insights gained through GoMiner can generate hypotheses to guide additional research. GoMiner displays the genes within the framework of the Gene Ontology hierarchy in two ways: * In the form of a tree, similar to that in AmiGO * In the form of a "Directed Acyclic Graph" (DAG) The program also provides: * Quantitative and statistical analysis * Seamless integration with important public databases GoMiner uses the databases provided by the GO Consortium. These databases combine information from a number of different consortium participants, include information from many different organisms and data sources, and are referenced using a variety of different gene product identification approaches.

Proper citation: GoMiner (RRID:SCR_002360) Copy   

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http://www.euratrans.eu/

The European large-scale functional genomics in the rat for translational research (EURATRANS) consortium brings together investigators who will use next-generation sequencing technologies to generate genomic, transcriptomic and epigenomic datasets. The goal is to create quantitative metabonomic and proteomic datasets to give significant depth of coverage, at multiple levels, across pathophysiological phenotypes. The aim is to enable insights into disease mechanisms, through an integrative, cross-disciplinary approach to understanding large-scale functional genomic datasets in rats and humans.

Proper citation: European large-scale functional genomics in the rat for translational research (EURATRANS) (RRID:SCR_013697) Copy   

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http://www.i2b2.org

i2b2 (Informatics for Integrating Biology and the Bedside) is an NIH-funded National Center for Biomedical Computing based at Partners HealthCare System. The i2b2 Center is developing a scalable informatics framework that will enable clinical researchers to use existing clinical data for discovery research and, when combined with IRB-approved genomic data, facilitate the design of targeted therapies for individual patients with diseases having genetic origin. For some resources (e.g. software) the use of the resource requires accepting a specific (e.g. OpenSource) license.

Proper citation: Informatics for Integrating Biology and the Bedside (RRID:SCR_013629) Copy   

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https://kona.nhgri.nih.gov/mnemiopsis/

Portal to obtain genomic information on Mnemiopsis. Data available provide annotations and other key biological information not available elsewhere. Used to advance research projects aimed at understanding phylogenetic diversity and evolution of proteins that play fundamental role in metazoan development. Collection of sequenced, assembled, annotated, and performed preliminary analysis of genome of Mnemiopsis.

Proper citation: Mnemiopsis Genome Project Portal (RRID:SCR_018293) Copy   

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http://wpicr.wpic.pitt.edu/WPICCompGen/blocks.htm

THIS RESOURCE IS NO LONGER IN SERVICE. Documented on July 31,2025. Software application aiming at identifying haplotype blocks. The likelihood of the data is calculated minus the model complexity. The resulting blocks have very low diversity and the linkage disequilibrium with SNP's outside the blocks is low. (entry from Genetic Analysis Software)

Proper citation: ENTROPY BLOCKER (RRID:SCR_000123) Copy   

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http://www.homozygositymapper.org/

A web-based approach of homozygosity mapping that can handle tens of thousands markers. User can upload their own SNP genotype files to the database. Intuitive graphic interface is provided to view the homozygous stretches, with the ability of zooming into single chromosomes or user-defined chromosome regions. The underlying genotypes in all samples are displayed. The software is also integrated with our candidate gene search engine, GeneDistiller, so that users can interactively determine the most promising gene. (entry from Genetic Analysis Software)

Proper citation: HOMOZYGOSITYMAPPER (RRID:SCR_001714) Copy   

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http://weatherby.genetics.utah.edu/cgi-bin/Phevor/PhevorWeb.html

THIS RESOURCE IS NO LONGER IN SERVICE. Documented on October 28,2025. Tool that integrates phenotype, gene function, and disease information with personal genomic data for improved power to identify disease-causing alleles. It works by combining knowledge resident in multiple biomedical ontologies with the outputs of variant prioritization tools. It does so using an algorithm that propagates information across and between ontologies. This process enables Phevor to accurately reprioritize potentially damaging alleles identified by variant prioritization tools in light of gene function, disease, and phenotype knowledge. Phevor is especially useful for single exome and family trio-based diagnostic analyses, the most commonly occurring clinical scenarios, and ones for which existing personal-genomes diagnostic tools are most inaccurate and underpowered. Phevor not only improves diagnostic accuracy for individuals presenting with established disease phenotypes, but also for those with previously undescribed and atypical disease presentations. Importantly, Phevor is not limited to known diseases, or known disease-causing alleles.

Proper citation: Phevor (RRID:SCR_002273) Copy   

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https://genomecenter.ucdavis.edu/core-facilities/

Genome Center uses technologies to understand how heritable genetic information of diverse organisms functions in health and disease. Provides research facilities, service cores, and staff for genomics research and training. Core facilities for Bioinformatics,DNA Technologies and Expression Analysis, Metabolomics, Proteomics,TILLING Core,Yeast One Hybrid Services Core.

Proper citation: UC Davis Genome Center Labs and Facilities (RRID:SCR_012480) Copy   

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http://www.daimi.au.dk/%7Emailund/SNPFile/

Software library and API for manipulating large SNP datasets with associated meta-data, such as marker names, marker locations, individuals'' phenotypes, etc. in an I/O efficient binary file format. In its core, SNPFile assumes very little about the metadata associated with markers and individuals, but leaves this up to application program protocols. (entry from Genetic Analysis Software)

Proper citation: SNPFILE (RRID:SCR_009402) Copy   

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