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http://www.mds.qmw.ac.uk/statgen/dcurtis/software.html

THIS RESOURCE IS NO LONGER IN SERVICE. Documented on May 16,2023. Software application to detect genetically abnormal subjects in a case-control sample based on genotypes at multiple marker loci. (entry from Genetic Analysis Software)

Proper citation: CHECKHET (RRID:SCR_009147) Copy   

•   Source: SciCrunch Registry

http://www.gene.ucl.ac.uk/public-files/packages/linkage_utils/ceph2cri/

THIS RESOURCE IS NO LONGER IN SERVCE, documented September 22, 2016. Software application to convert output from CEPH DBMS to CRIMAP format.

Proper citation: CEPH2CRI (RRID:SCR_009143) Copy   

•   Source: SciCrunch Registry

http://www.stat.uchicago.edu/~mcpeek/software/CCQLSpackage1.3/

Software application (entry from Genetic Analysis Software)

Proper citation: CC-QLS (RRID:SCR_009140) Copy   

•   Source: SciCrunch Registry

http://www.sanger.ac.uk/resources/software/rarevariant/

THIS RESOURCE IS NO LONGER IN SERVICE. Documented on May 16,2026. Software application for enabling the analysis of rare variants in large-scale case control and quantitative trait association studies. CCRaVAT (Case-Control Rare Variant Analysis Tool) and QuTie (Quantitative Trait) are software packages that enable efficient large-scale analysis of rare variants across specific regions or genome-wide. These programs implement a rare variant super-locus or collapsing method that investigates the accumulation of rare variant alleles in either a case-control or quantitative trait study design. (entry from Genetic Analysis Software)

Proper citation: CCRAVAT (RRID:SCR_009141) Copy   

•   Source: SciCrunch Registry

http://www.cbs.dtu.dk/services/HMMgene/

Data analysis service for prediction of vertebrate and C. elegans genes.

Proper citation: HMMgene (RRID:SCR_011933) Copy   

•   Source: SciCrunch Registry

https://bmcbioinformatics.biomedcentral.com/articles/10.1186/1471-2105-8-S1-S21

A microarray platform that uses the Illumina and Affymetrix GeneChip microarray technology for genome and transcriptome analyses and a web-based database that consists exclusively of high quality Affymetrix data from immunological experiments hosted by a public, non-profit consortium of three scientific public institutions aimed to develop, integrate and disseminate Functional Genomics.

Proper citation: Genopolis (RRID:SCR_010975) Copy   

•   Source: SciCrunch Registry

http://biome.ewha.ac.kr:8080/GSEAWebApp/

An integrative platform for diverse types of gene set analysis with annotation network navigation. It includes tools for statistical analysis, visualization of annotation relationships, retrieval of genes from annotation database, and set operation for gene sets. In an effort to allow access to a full spectrum of amassed biological knowledge, they have integrated a variety of annotation data that include the GO, domain, disease, drug, chromosomal location, and custom-defined annotations. Diverse types of molecular networks (pathways, transcription and microRNA regulations, protein-protein interaction) are also included. The pair-wise relationship between annotation gene sets was calculated using kappa statistics. GARNET consists of three modules--gene set manager, gene set analysis and gene set retrieval, which are tightly integrated to provide virtually automatic analysis for gene sets. A dedicated viewer for annotation network has been developed to facilitate exploration of the related annotations.

Proper citation: GARNET (RRID:SCR_012033) Copy   

•   Source: SciCrunch Registry

http://www.informatics.jax.org/humanDisease.shtml

Collection of published and potential mouse models of human disease, discovery of candidate genes and investigation of phenotypic similarity between mouse models and human patients. Mouse mutation, and phenotype and disease model data from Mouse Genome Informatics database are integrated with human gene to disease relationships from the National Center for Biotechnology Information and Online Mendelian Inheritance in Man and human disease to phenotype relationships from the Human Phenotype Ontology.

Proper citation: Human Mouse Disease Connection (RRID:SCR_017522) Copy   

•   Source: SciCrunch Registry

http://catlas.org/mousebrain/#!/

Atlas of gene regulatory elements in adult mouse cerebrum. Atlas of CIS elements, providing information on accessible chromatin in individual cells from regions of adult mouse isocortex, olfactory bulb, hippocampus and cerebral nuclei. Uses resulting data to define candidate cis-regulatory DNA elements in distinct cell groups. Many are linked to putative target genes expressed in diverse cerebral cell types and uncover transcriptional regulators involved in broad spectrum of molecular and cellular pathways in different neuronal and glial cell populations. Used for analysis of gene regulatory programs of mammalian brain and interpretation of non-coding risk variants associated with various neurological disease and traits in humans.

Proper citation: CATlas (RRID:SCR_018690) Copy   

•   Source: SciCrunch Registry

http://cometa.tigem.it/

Interactive database of miRNA targets and miRNA-regulated gene networks to integrate expression data from hundreds of cellular and tissue conditions. Website includes CoMeTa corank lists and additional targets for all of human miRNAs, their associated pathways resulting from COOL analysis, and miRNA communities with their corresponding enriched functional categories. Website is searchable by miRNA, target gene, or biological function of interest, and represents unique resource to gain insight into miRNA-controlled gene networks and functions.

Proper citation: CoMeTa Website (RRID:SCR_017357) Copy   

•   Source: SciCrunch Registry

http://mouse.brain-map.org/

Genome wide database of gene expression in mouse brain. Genome-wide atlas of gene expression in the adult mouse brain.

Proper citation: ABA Mouse Brain: Atlas (RRID:SCR_017479) 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://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://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

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://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://vortex.cs.wayne.edu/projects.htm#Onto-Design

THIS RESOURCE IS NO LONGER IN SERVICE. Documented on September 6,2023. Many Laboratories chose to design and print their own microarrays. At present, the choice of the genes to include on a certain microarray is a very laborious process requiring a high level of expertise. Onto-Design database is able to assist the designers of custom microarrays by providing the means to select genes based on their experiment. Design custom microarrays based on GO terms of interest. User account required. Platform: Online tool

Proper citation: Onto-Design (RRID:SCR_000601) Copy   

•   Source: SciCrunch Registry