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http://mouse.perlegen.com/mouse/index.html

THIS RESOURCE IS NO LONGER IN SERVICE, Documented on August 12, 2014. Data, grouped by chromosome, available as flat files for download, of identified DNA polymorphisms (SNPs) in 15 commonly used strains of inbred laboratory mice. Perlegen's SNP, genotype (empirical and imputed), haplotype, trace, and PCR primer data has been compiled with NCBI Mouse Build information to produce data files for public use. Using high-density oligonuclueotide array technology, the study identified over 8 million SNPs and other genetic differences between these strains and the previously sequenced C57BL/6J reference strains (Phase 1). By leveraging data provided by Mark Daly's research team at the Broad Institute, genotypes were also predicted for 40 other common strains (Phase 2). Under an extension to the contract, Eleazar Eskin's group at UCLA has used this data to evaluate SNP associations with phenotypes from the Mouse Phenome Project (the Mouse Phenome Database), and to construct haplotype maps for a total of 94 inbred strains (the Mouse HapMap Project). SNP and genotype positions have been mapped from their original reference coordinates to NCBI Mouse Build 37 coordinates. Note that C57BL6/J strain was not selected for re-sequencing as this data would have been almost entirely redundant with the NCBI reference sequence. Since we did not actually determine genotypes for C57BL6/J, we did not submit genotypes for this strain to dbSNP. However, implicit genotypes for C57BL6/J can be obtained from the reference sequence at each SNP position (the reference allele is the first allele in the ALLELES column). The data is available for download in two different compressed file formats. The files are saved as both PC .zip files and Unix compressed .gz files. At this website, you can: * Learn more about the goals of the Perlegen mouse resequencing project. * Learn more about the array-based resequencing technology used in the project. * Download the SNPs, genotypes, and other data generated by the project, plus sequences of the long-range PCR primers used for SNP discovery. * Browse the mouse genome for SNPs. * View the haplotype blocks within the mouse genome. Mouse Genome Browser The Mouse Genome Browser can be used to visualize genes and the SNPs discovered in this study of genome-wide DNA variation in 15 commonly used, genetically diverse strains of inbred laboratory mice. The reference genome is the C57BL/6J strain NCBI build 37 mouse sequence. In addition to the experimentally-derived genotypes for the original 15 strains, the imputed genotypes for 40 additional inbred mouse strains can also be accessed. Mouse Haplotype Analysis The sequences of 16 commonly used, genetically diverse strains of inbred laboratory mice were analyzed to determine their haplotype structure. The Ancestry Browser shows which ancestral sequence each inbred strain most resembles, along with statistics on the pairwise similarity between the ancestral strains. The Haplotype Viewer shows the haplotype block boundaries and the pairwise similarity for all 56 strains: the 15 used for SNP discovery, the reference strain (C57BL/6J), and the 40 additional strains for which the genotypes were imputed.

Proper citation: Perlegen/NIEHS National Toxicology: Mouse Genome Resequencing Project (RRID:SCR_000726) Copy   

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https://www.integromics.com/omicsoffice-for-ngs/

THIS RESOURCE IS NO LONGER IN SERVICE. Documented on August 18,2025. Software for secondary and tertiary analysis of Next Generation Sequencing (NGS) data.

Proper citation: OmicsOffice for NGS SeqSolve (RRID:SCR_001222) Copy   

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https://github.com/TGAC/RAMPART

Software for workflow management system for de novo genome assembly of DNA sequence data.Designed to exploit high performance computing environments, such as clusters and shared memory systems.

Proper citation: Rampart (RRID:SCR_016742) Copy   

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http://mus.well.ox.ac.uk/mouse/INBREDS/

THIS RESOURCE IS NO LONGER IN SERVICE. Documented on August 19,2025. Data set of genotypes available for 480 strains and 13370 successful SNP assays that are mapped to build34 of the mouse genome, including 107 SNPs that are mapped to random unanchored sequence 13374 SNPs are mapped onto Build 33 of the mouse genome. You can access the data relative to Build 33 or Build 34.

Proper citation: Wellcome-CTC Mouse Strain SNP Genotype Set (RRID:SCR_003216) Copy   

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http://www.broad.mit.edu/node/549

Genomic data set on Type 2 Diabetes in African-Americans derived via admixture mapping, a method for genome-wide association analysis based on admixture-generated linkage disequilibrium. This collaborative group has identified 1,478 African Americans with Type 2 Diabetes (T2D) from the Jackson Heart Study and Multiethnic Cohort Study, as well as 498 controls from the Jackson Heart Study who are normoglycemic despite high body mass index and older age. All samples were genotyped (using the Illumina BeadLab platform) for 1,291 polymorphic markers chosen to be extremely different in frequency between west Africans and European Americans. Evidence for association to diabetes at each marker as reported by the ANCESTRYMAP software are reported in the downloadable table. They calculate that this study has statistical power to detect loci where African or European ancestry on average confers multiplicative increased risk of 1.35-fold or more. The fact that they did not detect a statistically significant signal of association in the scan suggests that any genetic risk factors for T2D do not confer different risks due to ancestry that differ by this factor. The genome scan results are publicly available (Excel file) prior to publication so that researchers interested in the genetics of T2D can use the results of the scan to prioritize follow-up of any regions of interest.

Proper citation: A Whole Genome Admixture Scan for Type 2 Diabetes in African Americans (RRID:SCR_006984) Copy   

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http://eyebrowse.cit.nih.gov/

EyeBrowse displays expressed sequence tag (EST) cDNA clones from eye tissues (derived from NEIBank and other sources) aligned with current versions of the human, rhesus, mouse, rat, dog, cow, chicken, or zebrafish genomes, including reference sequences for known genes. This gives a simplified view of gene expression activity from different parts of the eye across the genome. The data can be interrogated in several ways. Specific gene names can be entered into the search window. Alternatively, regions of the genome can be displayed. For example, entering two STS markers separated by a semicolon (e.g. RH18061;RH80175) allows the display of the entire chromosomal region associated with the mapping of a specific disease locus. ESTs for each tissue can then be displayed to help in the selection of candidate genes. In addition, sequences can be entered into a BLAT search and rapidly aligned on the genome, again showing eye derived ESTs for the same region. EyeBrowse includes a custom track display SAGE data for human eye tissues derived from the EyeSAGE project. The track shows the normalized sum of SAGE tag counts from all published eye-related SAGE datasets centered on the position of each identifiable Unigene cluster. This indicates relative activity of each gene locus in eye. Clicking on the vertical count bar for a particular location will bring up a display listing gene details and linking to specific SAGE counts for each eye SAGE library and comparisons with normalized sums for neural and non-neural tissues. To view or alter settings for the EyeSAGE track on EyeBrowse, click on the vertical gray bar at the left of the display. Other custom tracks display known eye disease genes and mapped intervals for candidate loci for retinal disease, cataract, myopia and cornea disease. These link back to further information at NEIBank. For mouse, there is custom track data for ChIP-on-Chip of RNA-Polymerase-II during photoreceptor maturation.

Proper citation: EyeBrowse (RRID:SCR_008000) Copy   

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http://www.hgvs.org/dblist/dblist.html

A list of various databases freely available to the public, including several mutation and variation resources, such as education resources for teachers students provided by the Human Genome Variation Society. Databases listed include: * Locus Specific Mutation Databases * Disease Centered Central Mutation Databases * Central Mutation and SNP Databases * National and Ethnic Mutation Databases * Mitochondrial Mutation Databases * Chromosomal Variation Databases * Other Mutation Databases ( i.e. your round holes don''''t fit our square pegs) * Clinical and Patient Aspects Databases * Non Human Mutation Databases * Artificial Mutations Only * Other Related Databases * Education Resources for Teachers and Students

Proper citation: Human Genome Variation Society: Databases and Other Tools (RRID:SCR_006876) Copy   

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http://www.hgsc.bcm.tmc.edu/content/honey-bee-genome-project

The HGSC has sequenced the honey bee, Apis mellifera. The version 4.0 assembly was released in March 2006 and published in October 2006. The genome sequence is being upgraded with additional sequence coverage. The honey bee is important in the agricultural community as a producer of honey and as a facilitator of pollination. It is a model organism for studying the following human health issues: immunity, allergic reaction, antibiotic resistance, development, mental health, longevity and diseases of the X chromosome. In addition, biologists are interested in the honey bee's social organization and behavioral traits. This project was proposed to the HGSC by a group of dedicated insect biologists, headed by Gene Robinson. Following a workshop at the HGSC and a honey bee white paper, the HGSC began the project in 2002. A 6-fold coverage WGS, BAC sequence from pooled arrays, and an initial genome assembly (Amel_v1.0) were released beginning in 2003. This has been a challenging project with difficulty in recovering AT-rich regions. The WGS data had lower coverage in AT-rich regions and BAC data from clones showed evidence of internal deletions. Additional reads from AT enriched DNA addressed these underrepresented regions. The current assembly Amel_4.0 was produced with Atlas and includes 2.7 million reads (1.8 Gb) or 7.5x coverage of the (clonable) genome. About 97% of STSs, 98% of ESTs, and 96% of cDNAs are represented in the 231 Mb assembly. About 2,500 reads were also produced from a strain of Africanized honey bee and SNPs were extracted. These were released in dbSNP and the NCBI Trace Archive. Analysis of the genome by a consortium of 20 labs has been completed. This produced a gene list derived from five different methods melded through the GLEAN software. Publications include a main paper in Nature and up to forty companion papers in Genome Research and Insect Molecular Biology. Sponsors: Sequencing of the honey bee is jointly funded by National Human Genome Research Institute (NHGRI) and the Department of Agriculture (USDA). Multiple drones from the same queen (strain DH4) were obtained from Danny Weaver of B. Weaver Apiaries. All libraries were made from DNA isolated from these drones. The honey bee BAC library (CHORI-224) was prepared by Pieter de Jong and Katzutoyo Osoegawa at the Children's Hospital Oakland Research Institute.

Proper citation: Honey Bee Genome Project (RRID:SCR_002890) Copy   

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http://rana.lbl.gov/drosophila

A single source for sequences, assemblies, annotations and analyses of the genomes of members of the fruitfly genus Drosophlia. It is meant as resource for Drosophilists and other researchers interested in comparative analysis of these species and their genomes. There are pages for each species, as well as pages for different types of multi-species resources (e.g. alignments). If you have a public resource that will help this project, please consider making it available through this page by emailing multiple_at_fruitfly.org.

Proper citation: Assembly/Alignment/Annotation of 12 Related Drosophila Species (RRID:SCR_002921) Copy   

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http://www.gramene.org

Curated, open-source, integrated data resource for comparative functional genomics in crops and model plant species to facilitate the study of cross-species comparisons using information generated from projects supported by public funds. It currently hosts annotated whole genomes in over two dozen plant species and partial assemblies for almost a dozen wild rice species in the Ensembl browser, genetic and physical maps with genes, ESTs and QTLs locations, genetic diversity data sets, structure-function analysis of proteins, plant pathways databases (BioCyc and Plant Reactome platforms), and descriptions of phenotypic traits and mutations. The web-based displays for phenotypes include the Genes and Quantitative Trait Loci (QTL) modules. Sequence based relationships are displayed in the Genomes module using the genome browser adapted from Ensembl, in the Maps module using the comparative map viewer (CMap) from GMOD, and in the Proteins module displays. BLAST is used to search for similar sequences. Literature supporting all the above data is organized in the Literature database. In addition, Gramene now hosts a variety of web services including a Distributed Annotation Server (DAS), BLAST and a public MySQL database. Twice a year, Gramene releases a major build of the database and makes interim releases to correct errors or to make important updates to software and/or data. Additionally you can access Gramene through an FTP site.

Proper citation: Gramene (RRID:SCR_002829) Copy   

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http://www.hgsc.bcm.tmc.edu/content/red-flour-beetle-genome-project

This portal provides information about the Tribolium castabeum Genome Project. The Tribolium castaneum genome sequence and its analysis has been published in Nature, two companion journal issues (IBMB and DGE) and numerous other publications listed below. The red flour beetle, Tribolium castaneum, a common pest that is also a genetic model for the Coleoptera. The genome has been sequenced to 7-fold coverage using a whole genome shotgun approach and assembled using the HGSC's assembly engine, Atlas, with methods employed for the Drosophila pseudoobscura genome assembly. Approximately 90% of the genome sequence has been mapped to chromosomes in collaboration with Dick Beeman (USDA ARS) and Sue Brown (Kansas State University). Access to the Data :- Genome Assembly: The long term home of the Tribolium genome is Beetlebase. Tcas 3.0 is now available in GenBank and on our FTP site. Note there are no restrictions of any kind on the Tribolium data as it has been published. Version 2 of the assembly, Tcas_2.0 is available for download using the FTP Data link in the sidebar. The assembly is described in detail in the README in that directory. T.cas_1.0 was a preliminary genome assembly that did not include large insert paired end information and has been moved to a previous assemblies folder. A genboree browser of the Tcas2.0 sequence is available here: There are also links to the genboree browser from the blast results (at the bottom of each reported HSP) if you use the blast server on this page. The original linear scaffold file, Tcas2.0/linearScaffolds/Tcas20050914-genome, posted on the ftp site did not include singleton contigs from the assembly and thus did not fully reflect the tribolium genome sequence, missing ~4.4Mb of sequence in 1860 contigs and reptigs or approximately 2.5% of the assembled sequence. A corrected Tcas20051011-genome file containing these missing sequences is now available on the ftp site. The blast databases have also been updated to reflect this change. All other data is correct, and not affected by this change. :- BLAST Searches: The BLAST link is located in the sidebar. :* Linearized chromosome and unplaced scaffold sequences :* Assembled contigs :* Bin0 unassembled reads and Repeat reads Traces are available from the NCBI Trace Archive by using the link in the sidebar, or by using NCBI MegaBLAST with a same species or cross species query. Sponsors: Funding for this project has been provided by the National Human Genome Research Institute (NHGRI U54 HG003273), which is part of the National Institutes of Health (NIH), and the U.S. Department of Agriculture's Agricultural Research Service (USDA ARS Agreement No. 58-5430-3-338).

Proper citation: Tribolium castaneum Genome Project (RRID:SCR_002848) Copy   

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http://hapmap.ncbi.nlm.nih.gov/

THIS RESOURCE IS NO LONGER IN SERVICE, documented August 22, 2016. A multi-country collaboration among scientists and funding agencies to develop a public resource where genetic similarities and differences in human beings are identified and catalogued. Using this information, researchers will be able to find genes that affect health, disease, and individual responses to medications and environmental factors. All of the information generated by the Project will be released into the public domain. Their goal is to compare the genetic sequences of different individuals to identify chromosomal regions where genetic variants are shared. Public and private organizations in six countries are participating in the International HapMap Project. Data generated by the Project can be downloaded with minimal constraints. HapMap project related data, software, and documentation include: bulk data on genotypes, frequencies, LD data, phasing data, allocated SNPs, recombination rates and hotspots, SNP assays, Perlegen amplicons, raw data, inferred genotypes, and mitochondrial and chrY haplogroups; Generic Genome Browser software; protocols and information on assay design, genotyping and other protocols used in the project; and documentation of samples/individuals and the XML format used in the project.

Proper citation: International HapMap Project (RRID:SCR_002846) Copy   

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http://hembase.niddk.nih.gov/

Database designed for web-based examination of the human erythroid transcriptome. The database is organized to provide a cytogenetic band position, a unique name as well as a concise annotation for each entry. Search queries may be performed by name, keyword or cytogenetic location. Search results are linked to primary sequence data and three major human genome browsers for access to information considered current at the time of each search. Hembase provides interested scientists and clinical hematologists with a genome-based approach toward the study of erythroid biology. Red blood cells in the circulation arise from hematopoietic stem cells that proliferate as erythroid progenitors and differentiate into erythroid precursor cells in response to the hormone erythropoietin. Messenger RNA was isolated from those cells and used to generate gene libraries. Sequencing several thousand expressed sequence tags (EST) from those libraries was then performed. Those EST and sequences encoding several hundred additional genes with known expression in erythroid cells are compiled here as a database of human erythroid gene activity. The database is organized and linked according to the location of these sequences within the human genome., THIS RESOURCE IS NO LONGER IN SERVICE. Documented on January 15,2026.

Proper citation: HemBase (RRID:SCR_002880) Copy   

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http://www.atgc-montpellier.fr/

A bioinformatics platform that is a joint project of several South of France laboratories with available services based on their expertise, issued from their research activities which involve phylogenetics, population genetics, molecular evolution, genome dynamics, comparative and functional genomics, and transcriptome analysis. Most of the software and databases on ATGC are (co)authored by researchers from South of France teams. Some are widely used and highly cited. South of France laboratories: * CRBM (transcriptomes and stem cells). * IBC (computational biology). * MiVEGEC (evolution and phylogeny). * LGDP (plant genomics). * LIRMM (computer science). * South Green (plant genomics).

Proper citation: ATGC: Montpellier bioinformatics platform (RRID:SCR_002917) Copy   

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http://www.broadinstitute.org/gsea/

Software package for interpreting gene expression data. Used for interpretation of a large-scale experiment by identifying pathways and processes.

Proper citation: Gene Set Enrichment Analysis (RRID:SCR_003199) Copy   

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http://www.eucomm.org

Generate, archive, and distribute world-wide up to 12.000 conditional mutations across the mouse genome in mouse embryonic stem (ES) cells and Establish a limited number of mouse mutants from this resource. EUCOMM contributes the largest fraction of conditionally trapped and targeted genes in mouse C57BL/6N embryonic stem (ES) cells to the IKMC. EUCOMM vectors, mutant ES cells and mutant mice are distributed worldwide, enabling functional genomics research in a standardized and cost-effective manner by a much wider biomedical research community than has been possible previously. EUCOMM mutant ES cells and vectors can be obtained from the European Mouse Mutant Cell Repository (EuMMCR). EUCOMM mutant mice are archived and distributed by the European Mouse Mutant Archive (EMMA). Mutagenesis Strategies * Conditional gene trapping - random approach for expressed genes * Conditional targeted trapping - directed approach, used for expressed genes * Conditional gene targeting - directed approach, used for non-expressed genes

Proper citation: European Conditional Mouse Mutagenesis Program (RRID:SCR_003104) Copy   

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http://jaspar.genereg.net

Open source database of curated, non-redundant set of profiles derived from published collections of experimentally defined transcription factor binding sites for multicellular eukaryotes. Consists of open data access, non-redundancy and quality. JASPAR CORE is smaller set that is non-redundant and curated. Collection of transcription factor DNA-binding preferences, modeled as matrices. These can be converted into Position Weight Matrices (PWMs or PSSMs), used for scanning genomic sequences. Web interface for browsing, searching and subset selection, online sequence analysis utility and suite of programming tools for genome-wide and comparative genomic analysis of regulatory regions. New functions include clustering of matrix models by similarity, generation of random matrices by sampling from selected sets of existing models and a language-independent Web Service applications programming interface for matrix retrieval.

Proper citation: JASPAR (RRID:SCR_003030) Copy   

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http://hugenavigator.net/

THIS RESOURCE IS NO LONGER IN SERVICE. Documented on January 5, 2023. Knowledge base of genetic associations and human genome epidemiology including information on population prevalence of genetic variants, gene-disease associations, gene-gene and gene- environment interactions, and evaluation of genetic tests. This tool explores HuGENet, the Human Genome Epidemiology Network, which is a global collaboration of individuals and organizations committed to the assessment of the impact of human genome variation on population health and how genetic information can be used to improve health and prevent disease. What does HuGE Navigator offer? *HuGEpedia - an encyclopedia of human genetic variation in health and disease, includes, Phenopedia and Genopedia. Phenopedia allows you to look up gene-disease association summaries by disease, and Genopedia allows you to look up gene-disease association summaries by gene. In general, HuGEpedia is a searchable database that summarizes published articles about human disease and genetic variation, including primary studies, reviews, and meta-analyses. It provides links to Pubmed abstracts, researcher contact info, trends, and more. *HuGEtools - searching and mining the literature in human genome epidemiology, includes, HuGE Literature Finder, HuGE Investigator Browser, Gene Prospector, HuGE Watch, Variant Name Mapper, and HuGE Risk Translator. *HuGE Literature Finder finds published articles in human genome epidemiology since 2001. The search query can include genes, disease, outcome, environmental factors, author, etc. Results can be filtered by these categories. It is also possible to see all articles in the database for a particular topic, such as genotype prevalence, pharmacogenomics, or clinical trial. *HuGE Investigator Browser finds investigators in a particular field of human genome epidemiology. This info is obtained using a behind-the-scenes tool that automatically parses PubMed affiliation data. *Gene Prospector is a gateway for evaluating genes in relation to disease and risk factors. This tool allows you to enter a disease or risk factor and then supplies you with a table of genes associated w/your query that are ranked based on strength of evidence from the literature. This evidence is culled from the HuGE Literature Finder and NCBI Entrez Gene - And you're given the scoring formula. The Gene Prospector results table provides access to the Genopedia entry for each gene in the list, general info including links to other resources, SNP info, and associated literature from HuGE, PubMed, GWAS, and more. It is a great place to locate a lot of info about your disease/gene of interest very quickly. *HuGE Watch tracks the evolution of published literature, HuGE investigators, genes studied, or diseases studied in human genome epidemiology. For example, if you search Trend/Pattern for Diseases Studied you'll initially get a graph and chart of the number of diseases studied per year since 1997. You can refine these results by limiting the temporal trend to a category or study type such as Gene-gene Interaction or HuGE Review. *Variant Name Mapper maps common names and rs numbers of genetic variants using information from SNP500Cancer, SNPedia, pharmGKB, ALFRED, AlzGene, PDGene, SZgene, HuGE Navigator, LSDBs, and user submissions. *HuGE Risk Translator calculates the predictive value of genetic markers for disease risk. To do so, users must enter the frequency of risk variant, the population disease risk, and the odds ratio between the gene and disease. This information is necessary in order to yield a useful predictive result. *HuGEmix - a series of HuGE related informatics utilities and projects, includes, GAPscreener, HuGE Track, Open Source. GAPscreener is a screening tool for published literature on human genetic associations; HuGE Track is a custom track built for HuGE data in the UCSC Genome Browser; and Open Source is infrastructure for managing knowledge and information from PubMed.

Proper citation: HuGE Navigator - Human Genome Epidemiology Navigator (RRID:SCR_003172) Copy   

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http://www.brenda-enzymes.org/

Database for functional enzyme and ligand-related information maintained as part of the German ELIXIR Node. Provides advanced query systems, evaluation tools, and various visualization options for the detailed assessment of enzyme properties. Enzyme data in BRENDA are classified according to the Enzyme Commission (EC) nomenclature of IUBMB.

Proper citation: BRENDA (RRID:SCR_002997) Copy   

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http://www.coriell.org/

Non-profit research center dedicated to the study of the human genome. Expert staff and pioneering programs in the fields of personalized medicine, cell biology, cytogenetics, genotyping, and biobanking drive our mission. The emerging field of personalized medicine draws upon a person's genomic information to tailor treatments and prescription drug dosing to optimize health outcomes. The Coriell Personalized Medicine Collaborative (CPMC) research study is seeking to understand the usefulness of genetic risk and pharmacogenomics in clinical decision-making and healthcare management. Coriell has a distinguished history in cell biology. We are building upon this expertise by playing an important role in induced pluripotent stem (iPS) cell research. These powerful cells, which can be made from skin cells or blood, are revolutionizing the way human disease is studied and how drugs are developed. The decline of neurons afflicted with Alzheimer's disease or pancreatic cells fighting diabetes can be studied in a Petri dish. By proving efficacy within the diseased environment prior to clinical trial, drugs can move through the pipeline quicker to reach patients sooner. In addition to pioneering cutting-edge research initiatives, Coriell offers custom research services including cell culture, cytogenetic analyses, and molecular biology to the scientific community. Furthermore, Coriell's Genotyping and Microarray Center is one of the nation's largest centers, with high-throughput DNA analysis systems from Illumina and Affymetrix. The Center is CLIA-certified in 48 states.

Proper citation: Coriell Institute for Medical Research (RRID:SCR_003043) Copy   

•   Source: SciCrunch Registry