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http://www.broadinstitute.org/pubs/MitoCarta/

Collection of genes encoding proteins with strong support of mitochondrial localization. Inventory of genes encoding mitochondrial-localized proteins and their expression across 14 mouse tissues. Database is based on human and mouse RefSeq proteins that are mapped to NCBI Gene loci. MitoCarta 2.0 inventory provides molecular framework for system-level analysis of mammalian mitochondria.

Proper citation: MitoCarta (RRID:SCR_018165) Copy   

•   Source: SciCrunch Registry

http://diabetes.wisc.edu/index.php

Interactive database of gene expression and diabetes related clinical phenotypes. Allows to search gene expression in tissues as a function of obesity, strain, and age, in a mouse.

Proper citation: Attie Lab Diabetes Database (RRID:SCR_016639) Copy   

•   Source: SciCrunch Registry

http://mousebrain.org/

Atlas of brain cell types, derived from single cell RNA-Seq data from Linnarsson Lab. Can be browsed by taxon, cell type, tissue, and gene, with information on enriched genes, specific markers, anatomical location and more. Single cell gene expression atlas of mouse nervous system.

Proper citation: mousebrain.org (RRID:SCR_016999) Copy   

•   Source: SciCrunch Registry

https://resistomedb.com

Web tool to explore and visualize Antibiotic Resistance Genes found on Tara Oceans samples. Can be explored by individual ARG or grouped by antibiotic class.

Proper citation: ResistomeDB (RRID:SCR_018305) Copy   

•   Source: SciCrunch Registry

http://software.broadinstitute.org/gsea/msigdb/index.jsp

Collection of annotated gene sets for use with Gene Set Enrichment Analysis (GSEA) software.

Proper citation: Molecular Signatures Database (RRID:SCR_016863) Copy   

•   Source: SciCrunch Registry

http://sourceforge.net/projects/phenofam/

A web-based application that performs gene set enrichment analysis (GSEA) by employing structural and functional information on families of protein domains as annotation terms.

Proper citation: PhenoFam (RRID:SCR_000640) Copy   

•   Source: SciCrunch Registry

http://www.ms-research.dk/genetics.htm

THIS RESOURCE IS NO LONGER IN SERVICE. Documented on July 31,2025. We have collected DNA for more than 15 years, and today we have DNA from more than 1,800 Danish MS patients and 1,200 controls, all kept in the Danish Multiple Sclerosis Biobank in DMSC. In order to increase the sample size for genetic testing, we have participated in the Nordic MS Genetic Network since 1994, and today the Nordic material consists of more than 6,000 MS cases and 6,000 controls. The research in DMSC is focused on the candidate gene approaches and the genetic influence on the differences in treatment response. We are part of the IMSGC (International Multiple Sclerosis Genetic Consortium) and the Wellcome Trust Case Control Consortium (WTCCC), where 23 research groups from 15 countries are performing the largest set of MS genome-wide association study (GWAS), genotyping 11,000 cases and 11,000 controls using 500,000 SNP chip. Primary results have elucidated associations to more than 100 gene variations (SNPs). Following this collaboration we are joining the Immunochip Consortium, where 1,000 Danish cases and 1,000 Danish controls participate in a large scale genetic analysis, investigating best genes/regions/SNPs in MS together with other international MS research groups and 9 other autoimmune diseases research groups, looking for shared autoimmune genes. The risk of MS has been increasing over the last 50 years, especially among women older than 40 years. On this background we have initiated a project looking at aspects of gender differences, including different treatment responses. Furthermore, we have initiated a large-scale vitamin D project, investigating gene variations within the vitamin D pathway, and the importance of vitamin D in clinical and immunological disease activity. In addition, we have collected more than 800 questionnaires from MS patients dealing in detail with lifestyle and environmental exposure for a project studying gene-environmental interactions.

Proper citation: Danish Multiple Sclerosis Biobank (RRID:SCR_000089) Copy   

•   Source: SciCrunch Registry

https://github.com/wtsi-npg/Illuminus

A fast and accurate algorithm for assigning single nucleotide polymorphism (SNP) genotypes to microarray data from the Illumina BeadArray technology.

Proper citation: ILLUMINUS (RRID:SCR_000388) Copy   

•   Source: SciCrunch Registry

http://harvard.eagle-i.net/i/0000012e-6dc5-7b04-55da-381e80000000

A lab facility that provides viral vectors with custom-designed promoters and reporter genes and capacity for gene regulation. Services include DNA packaging and purification and titering and allocation of viral vectors.

Proper citation: MGH Vector Development and Production Core Facility (RRID:SCR_000886) Copy   

•   Source: SciCrunch Registry

http://ccr.coriell.org/Sections/Collections/ADA/?SsId=12

The purpose of the American Diabetes Association (ADA), GENNID Study (Genetics of non-insulin dependent diabetes mellitus, NIDDM) is to establish a national database and cell repository consisting of information and genetic material from families with well-documented NIDDM. The GENNID Study will provide investigators with the information and samples necessary to conduct genetic linkage studies and locate the genes for NIDDM. Non-Hispanic white, Hispanic, African-American, and Japanese-American multiplex NIDDM families, with a minimum of one affected sib-pair, are being collected by the eight Harold Rifkin Family Acquisition Centers. Detailed family and medical histories are obtained from all participants. Family members with diabetes have fasting blood samples drawn, while nondiabetic family members have an oral glucose tolerance test and, when possible, insulin sensitivity and insulin secretion measurements by frequently sampled intravenous glucose tolerance testing or euglycemic insulin clamp. Lymphoblastoid cell lines are established for all participants. DNA samples and extensive phenotypic data are available from the American Diabetes Association's GENNID study (Genetics of NIDDM). GENNID has collected detailed family histories and a broad array of data on 170 large pedigrees, all of which contain at least one affected sib pair, with a total of 650 affected individuals and approximately 1,200 total subjects. Included are approximately 65 Caucasian, 60 Hispanic, 25 African American, and 20 Japanese American pedigrees. In addition, GENNID also contains DNA and data on 1,000 additional affected sib pairs in each of three groups, African American, Caucasian, and Hispanic. DNA and phenotypic data, including race, gender and age, are available for all members of the pedigrees. The data set includes multiple metabolic factors, including carbohydrate metabolism, lipid metabolism, and body size measures, as well as lifestyle variables obtained by questionnaire (e.g., employment, exercise, etc.). The GENNID resource is ideally suited for genetic linkage and association studies as well as SNP discovery and typing. Investigators interested in obtaining the DNA samples and/or data will need to submit a proposal to the Association that addresses the genetics of type 2 diabetes.

Proper citation: ADA GENNID Study (RRID:SCR_000527) Copy   

•   Source: SciCrunch Registry

http://cedar.genetics.soton.ac.uk/pub/PROGRAMS/ldb;

THIS RESOURCE IS NO LONGER IN SERVICE. Documented on September 23,2022. Software application that integrate genetic linkage map and physical map (entry from Genetic Analysis Software)

Proper citation: LDB/LDB+ (RRID:SCR_000839) Copy   

•   Source: SciCrunch Registry

http://research.calit2.net/hap/

Software application (entry from Genetic Analysis Software)

Proper citation: HAP 1 (RRID:SCR_000837) Copy   

•   Source: SciCrunch Registry

http://www.biostat.harvard.edu/complab/dchip/snp.htm

THIS RESOURCE IS NO LONGER IN SERVCE, documented September 22, 2016.

Proper citation: DCHIP LINKAGE (RRID:SCR_000835) Copy   

•   Source: SciCrunch Registry

http://faculty.washington.edu/browning/floss/floss.htm

Software application that performs ordered subset analysis using MERLIN's ouput .lod file created with the --perFamily option. Ordered subset analysis uses covariate information to identify a more homogenous subset of families for linkage analysis. The homogeneous subset of families does not need to be specified a priori, and the covariates can include environmental exposures, quantitative traits, or linkage scores at another locus in the genome. The evidence for linkage is evaluated with a permutation test. (entry from Genetic Analysis Software)

Proper citation: FLOSS (RRID:SCR_000836) Copy   

•   Source: SciCrunch Registry

http://null

Software application for calculating the heterozygosity, PIC, and LIC values for polymorphic markers (entry from Genetic Analysis Software), THIS RESOURCE IS NO LONGER IN SERVICE. Documented on September 16,2025.

Proper citation: POLYMORPHISM (RRID:SCR_000828) Copy   

•   Source: SciCrunch Registry

https://github.com/gaow/genetic-analysis-software/blob/master/pages/EDAC.md

THIS RESOURCE IS NO LONGER IN SERVCE, documented September 22, 2016.

Proper citation: EDAC (RRID:SCR_000829) Copy   

•   Source: SciCrunch Registry

https://github.com/gaow/genetic-analysis-software/blob/master/pages/2LD.md

Software program for calculating linkage disequilibrium (LD) measures between two polymorphic markers.

Proper citation: 2LD (RRID:SCR_000826) Copy   

•   Source: SciCrunch Registry

http://www.bios.unc.edu/~lin/software/SQTL/

Software application (entry from Genetic Analysis Software)

Proper citation: SQTL (RRID:SCR_000827) Copy   

•   Source: SciCrunch Registry

http://ki.se/ki/jsp/polopoly.jsp?d=29350&a=24030&l=en

THIS RESOURCE IS NO LONGER IN SERVICE, documented August 29, 2016. Aims to investigate the relation between specific genetic variations, personality factors and pain experience in healthy subjects.

Proper citation: KI Biobank - PAIN (RRID:SCR_000610) Copy   

•   Source: SciCrunch Registry

http://solar-eclipse-genetics.org

A flexible and extensive software package for genetic variance components analysis, including linkage analysis, quantitative genetic analysis, and covariate screening. Operations are included for calculation of marker-specific or multipoint identity-by-descent (IBD) matrices in pedigrees of arbitrary size and complexity, and for linkage analysis of quantitative traits which may involve multiple loci (oligogenic analysis), dominance effects, and epistasis. (entry from Genetic Analysis Software)

Proper citation: SOLAR (RRID:SCR_000850) Copy   

•   Source: SciCrunch Registry