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http://www.alspac.bris.ac.uk

A long-term health research project which follows pregnant women and their offspring in a continuous health and developmental study. More than 14,000 mothers enrolled during pregnancy in 1991 and 1992, and the health and development of their children has been followed in great detail. The ALSPAC families have provided a vast amount of genetic and environmental information over the years which can be made available to researchers globally.

Proper citation: ALSPAC (RRID:SCR_007260) Copy   

•   Source: SciCrunch Registry

https://cnprc.ucdavis.edu/

Center for investigators studying human health and disease, offering the opportunity to assess the causes of disease, and new treatment methods in nonhuman primate models that closely recapitulate humans. Its mission is to provide interdisciplinary programs in biomedical research on significant human health-related problems in which nonhuman primates are the models of choice.

Proper citation: California National Primate Research Center (RRID:SCR_006426) Copy   

•   Source: SciCrunch Registry

http://www.pedigree-draw.com/

THIS RESOURCE IS NO LONGER IN SERVICE. Documented on April 12,2024. Software application for pedigree drawing (entry from Genetic Analysis Software)

Proper citation: Pedigree-Draw (RRID:SCR_008302) Copy   

•   Source: SciCrunch Registry

https://www.broadinstitute.org/ccle/

A collaborative project between the Broad Institute and the Novartis Institutes for Biomedical Research and its Genomics Institute of the Novartis Research Foundation, with the goal of conducting a detailed genetic and pharmacologic characterization of a large panel of human cancer models. The CCLE also works to develop integrated computational analyses that link distinct pharmacologic vulnerabilities to genomic patterns and to translate cell line integrative genomics into cancer patient stratification. The CCLE provides public access to genomic data, analysis and visualization for about 1000 cell lines.

Proper citation: Cancer Cell Line Encyclopedia (RRID:SCR_013836) Copy   

•   Source: SciCrunch Registry

https://cran.r-project.org/web/packages/ibdreg/index.html

Software package in S-PLUS and R to test genetic linkage with covariates by regression methods with response IBD sharing for relative pairs. Account for correlations of IBD statistics and covariates for relative pairs within the same pedigree. (entry from Genetic Analysis Software)

Proper citation: IBDREG (RRID:SCR_013127) Copy   

•   Source: SciCrunch Registry

https://www.ars-grin.gov/npgs/

Cooperative effort by U.S. state and federal government and private organizations to preserve the genetic diversity of plants. The NPGS aids scientists and the need for genetic diversity by acquiring, preserving, evaluating, documenting and distributing crop germplasm. The NPGS is managed by the Agricultural Research Service (ARS), the in-house research agency of the United States Department of Agriculture (USDA). Funding for the NPGS comes primarily through appropriations from the U.S. Congress.

Proper citation: National Plant Germplasm System (NPGS) (RRID:SCR_016785) Copy   

•   Source: SciCrunch Registry

https://www.synapse.org/#!Synapse:syn4921369/wiki/235539

Portal of PsychENCODE Consortium to study role of rare genetic variants involved in several psychiatric disorders. Database of regulatory elements, epigenetic modifications, RNA and protein in brain.

Proper citation: PsychENCODE Knowledge Portal (RRID:SCR_017500) Copy   

•   Source: SciCrunch Registry

https://bitbucket.org/nicofmay/basta-bayesian-structured-coalescent-approximation/src/master/

Software package as Bayesian method to infer migration from genetic data. Implemented in BEAST2 that combines accuracy of methods based on structured coalescent with computational efficiency required to handle more than few populations.

Proper citation: BASTA (RRID:SCR_017303) Copy   

•   Source: SciCrunch Registry

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   

•   Source: SciCrunch Registry

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   

•   Source: SciCrunch Registry

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   

•   Source: SciCrunch Registry

http://cerebrovascularportal.org

Portal enables browsing, searching, and analysis of human genetic information linked to cerebrovascular disease and related traits, while protecting the integrity and confidentiality of the underlying data.

Proper citation: Cerebrovascular Disease Knowledge Portal (RRID:SCR_015628) Copy   

•   Source: SciCrunch Registry

http://www.aevol.fr/

Simulation software for experimental evolution of microorganisms. Aevol is a digital genetics model for the study of structural variations of the genome (e.g. number of genes, synteny, proportion of coding sequences).

Proper citation: Aevol (RRID:SCR_015966) Copy   

•   Source: SciCrunch Registry

http://hyphy.org/

Open source software package for comparative sequence analysis using stochastic evolutionary models. Used for analysis of genetic sequence data in particular the inference of natural selection using techniques in phylogenetics, molecular evolution, and machine learning.

Proper citation: HyPhy (RRID:SCR_016162) Copy   

•   Source: SciCrunch Registry

http://gentle.magnusmanske.de

Software for DNA and amino acid editing, database management, plasmid maps, It can also be used for restriction and ligation, alignments, sequencer data import, calculators, gel image display, PCR, and more.

Proper citation: Gentle (RRID:SCR_016127) Copy   

•   Source: SciCrunch Registry

http://biopp.univ-montp2.fr/wiki/index.php/Main_Page

Software providing a set of ready-to-use C++ libraries as re-usable tools to visualize, edit, print and output data for bioinformatics. It uses sequence analysis, phylogenetics, molecular evolution and population genetics to help to write programs., THIS RESOURCE IS NO LONGER IN SERVICE. Documented on September 16,2025.

Proper citation: Bio++ (RRID:SCR_016055) Copy   

•   Source: SciCrunch Registry

http://www.broadcvdi.org/

Platform for analysis of the genetics of cardiovascular disease.Used for searching and analysis of human genetic information linked to myocardial infarction, atrial fibrillation and related traits while protecting the integrity and confidentiality of the data.

Proper citation: Cardiovascular Disease Knowledge Portal (RRID:SCR_016536) Copy   

•   Source: SciCrunch Registry

http://www.roslin.ed.ac.uk/alan-archibald/porcine-genome-sequencing-project/

Map of identifyied genes controlling traits of economic and welfare significance in the pig. The project objectives were to produce a genetic map with markers spaced at approximately 20 centiMorgan intervals over at least 90% of the pig genome; to produce a physical map with at least one distal and one proximal landmark locus mapped on each porcine chromosome arm and also genetically mapped; to develop a flow karyotype for the pig based on FACS sorted chromosomes; to develop PCR based techniques to enable rapid genotyping for polymorphic markers; to evaluate synteny conservation between pigs, man, mice and cattle; to develop and evaluate the statistical techniques required to analyze data from QTL mapping experiments and to plan and initiate the mapping of QTLs in the pig; to map loci affecting traits of economic and biological significance in the pig; and to develop the molecular tools to allow the future identification and cloning of mapped loci. Animal breeders currently assume that economically important traits such as growth, carcass composition and reproductive performance are controlled by an infinite number of genes each of infinitessimal effect. Although this model is known to be unrealistic, it has successfully underpinned the genetic improvement of livestock, including pigs, over recent decades. A map of the pig genome would allow the development of more realistic models of the genetic control of economic traits and the ultimately the identification of the major trait genes. This would allow the development of more efficient marker assisted selection which may be of particular value for traits such as disease resistance and meat quality.

Proper citation: Pig Genome Mapping (RRID:SCR_012884) Copy   

•   Source: SciCrunch Registry

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   

•   Source: SciCrunch Registry

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   

•   Source: SciCrunch Registry