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http://www.som.soton.ac.uk/research/geneticsdiv/epidemiology/chromscan/

A statistical based program for association mapping of disease genes. It utilises the Malecot model and the linkage disequilibrium (LD) map for the candidate region to analyse the genotypes derive from large sample of matched cases and controls. (entry from Genetic Analysis Software)

Proper citation: CHROMSCAN (RRID:SCR_013131) Copy   

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http://faculty.washington.edu/eathomp/Anonftp/PANGAEA/BOREL/

Software application for inference of genealogical relationships from genetic data, including sibship inference.

Proper citation: BOREL (RRID:SCR_013135) Copy   

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http://mayoresearch.mayo.edu/mayo/research/schaid_lab/software.cfm

THIS RESOURCE IS NO LONGER IN SERVICE. Documented on May 24,2023. Software application for statistical methods for disease and genetic marker associations using cases and their parents. These methods include an extension of the transmission/disequilibrium test (TDT) for multiple marker alleles, as well as additional general tests sensitive to associations that depend on dominant or recessive genetic mechanisms. (entry from Genetic Analysis Software)

Proper citation: GASSOC (RRID:SCR_013136) Copy   

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http://www.bio.unc.edu/faculty/vision/lab/mappop/

Software application that selects high resolution mapping subsamples and performs bin mapping (entry from Genetic Analysis Software)

Proper citation: MAPPOP (RRID:SCR_013490) Copy   

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http://dlin.web.unc.edu/software/SNPMStat/

A command-line program for the statistical analysis of SNP-disease association in case-control/cohort/cross-sectional studies with potentially missing genotype data. SNPMStat allows the user to estimate or test SNP effects and SNP-environment interactions by maximizing the (observed-data) likelihood that properly accounts for phase uncertainty, study design and gene-environment dependence. For SNPs without missing data, the program performs the standard association analysis. For typed SNPs with missing data or untyped SNPs, the program performs the maximum-likelihood analysis. (entry from Genetic Analysis Software)

Proper citation: SNPMSTAT (RRID:SCR_013339) Copy   

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http://www.cbil.ece.vt.edu/ResearchOngoingSNP.htm

Software application (entry from Genetic Analysis Software)

Proper citation: MECPM (RRID:SCR_013341) Copy   

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

Software application that implements valid and efficient statistical methods for meta-analysis of genomewide association studies with overlapping subjects. The current release performs logistic regression analysis of individual level data under the additive mode of inheritance. Data from genome-wide association studies are often analyzed jointly for the purposes of combining information from multiple studies of the same disease or comparing results across different disorders. In many instances, the same subjects appear in multiple studies. Failure to account for overlapping subjects can greatly inflate type I error when combining results from multiple studies of the same disease and can drastically reduce power when comparing results across different disorders. (entry from Genetic Analysis Software)

Proper citation: MAOS (RRID:SCR_013351) Copy   

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http://cardiogenomica.altervista.org/CARDIOGENOMICS/CardioGenomics%20Homepage.htm

The primary goal of the CardioGenomics PGA is to begin to link genes to structure, function, dysfunction and structural abnormalities of the cardiovascular system caused by clinically relevant genetic and environmental stimuli. The principal biological theme to be pursued is how the transcriptional network of the cardiovascular system responds to genetic and environmental stresses to maintain normal function and structure, and how this network is altered in disease. This PGA will generate a high quality, comprehensive data set for the functional genomics of structural and functional adaptation of the cardiovascular system by integrating expression data from animal models and human tissue samples, mutation screening of candidate genes in patients, and DNA polymorphisms in a well characterized general population. Such a data set will serve as a benchmark for future basic, clinical, and pharmacogenomic studies. Training and education are also a key focus of the CardioGenomics PGA. In addition to ongoing journal clubs and seminars, the PGA will be sponsoring symposia at major conferences, and developing workshops related to the areas of focus of this PGA. Information regarding upcoming events can be found in the Events section of this site, and information about training and education opportunities sponsored by CardioGenomics can be found on the Teaching and Education page. The CardioGenomics project came to a close in 2005. This server, cardiogenomics.med.harvard.edu, remains online in order to continue to distribute data that was generated by investigators under the auspices of the CardioGenomics Program for Genomic Applications (PGA). :Sponsors: This resource is supported by The National Heart, Lung and Blood Institute (NHLBI) of the NIH., THIS RESOURCE IS NO LONGER IN SERVICE. Documented on September 16,2025.

Proper citation: CardioGenomics (RRID:SCR_007248) Copy   

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https://www.mc.vanderbilt.edu/victr/dcc/projects/acc/index.php/Main_Page

A national consortium formed to develop, disseminate, and apply approaches to research that combine DNA biorepositories with electronic medical record (EMR) systems for large-scale, high-throughput genetic research. The consortium is composed of seven member sites exploring the ability and feasibility of using EMR systems to investigate gene-disease relationships. Themes of bioinformatics, genomic medicine, privacy and community engagement are of particular relevance to eMERGE. The consortium uses data from the EMR clinical systems that represent actual health care events and focuses on ethical issues such as privacy, confidentiality, and interactions with the broader community.

Proper citation: eMERGE Network: electronic Medical Records and Genomics (RRID:SCR_007428) Copy   

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http://www.oege.org/software/hwe-mr-calc.shtml

This portal leads to the Chi-sq Hardy-Weinberg equilibrium test calculator for biallelic markers (SNPs, indels etc), including analysis for ascertainment bias for dominant/recessive models (due to biological or technical causes.) The purpose of this web program is for estimating possible missingness and an approach to evaluating missingness under different genetic models. Mendelian randomization (MR) permits causal inference between exposures and a disease. It can be compared with randomized controlled trials. Whereas in a randomized controlled trial the randomization occurs at entry into the trial, in MR the randomization occurs during gamete formation and conception. Several factors, including time since conception and sampling variation, are relevant to the interpretation of an MR test. Particularly important is consideration of the missingness of genotypes that can be originated by chance, genotyping errors, or clinical ascertainment. Testing for Hardy-Weinberg equilibrium (HWE) is a genetic approach that permits evaluation of missingness. Through this tool, the authors demonstrate evidence of nonconformity with HWE in real data. They also perform simulations to characterize the sensitivity of HWE tests to missingness. Unresolved missingness could lead to a false rejection of causality in an MR investigation of trait-disease association. These results indicate that large-scale studies, very high quality genotyping data, and detailed knowledge of the life-course genetics of the alleles/genotypes studied will largely mitigate this risk. Sponsors: This resource is supported by an Intermediate Fellowship (grant FS/05/065/19497) from the British Heart Foundation.

Proper citation: Hardy-Weinberg Equilibrium Calculator (RRID:SCR_008371) Copy   

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http://cgems.cancer.gov

The project began as a pilot study to identify inherited genetic susceptibility to prostate and breast cancer. CGEMS has developed into a robust research program involving genome-wide association studies (GWASs) for a number of cancers to identify common genetic variants that affect a person''s risk of developing cancer. In collaboration with extramural scientists, NCI''s Division of Cancer Epidemiology and Genetics (DCEG) has carried out genome-wide scans for breast, prostate, pancreatic, and lung cancers, while a GWAS of bladder cancer is currently underway. By making the data available to both intramural and extramural research scientists, as well as those in the private sector through rapid posting, NIH can leverage its resources to ensure that the dramatic advances in genomics are incorporated into rigorous population-based studies. Ultimately, findings from these studies may yield new preventive, diagnostic, and therapeutic interventions for cancer. Sponsors: This resource is supported by the U.S. National Institues Of Health.

Proper citation: CGEMS (RRID:SCR_008445) Copy   

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http://www.snprc.org/

Center that supports studies of nonhuman primate models of human diseases, including common chronic diseases and infectious diseases and the effects that genetics and the environment have on physiological processes and disease susceptibility. SNPRC encourages the use of its resources by investigators from the national and international biomedical research communities.

Proper citation: Southwest National Primate Research Center (RRID:SCR_008292) Copy   

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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   

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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   

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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://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   

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https://www.broadinstitute.org/scientific-community/software/cancer-therapeutics-response-portal

Cancer Therapeutics Response Portal (CTRP) links genetic, lineage, and other cellular features of cancer cell lines to small-molecule sensitivity with the goal of accelerating discovery of patient-matched cancer therapeutics. CTRP can be mined to develop insights into small-molecule mechanisms of action and novel therapeutic hypotheses, and to support future discovery of drugs matched to patients based on predictive biomarkers.

Proper citation: Cancer Therapeutics Response Portal (CTRP) (RRID:SCR_026293) Copy   

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http://www.oege.org/

Portal for researchers to locate information relevant to interpretation and follow-up of human genetic epidemiological discoveries, including: a range of population and case and family genetic epidemiological studies, relevant gene and sequence databases, genetic variation databases, trait measurement, resource labs, journals, software, general information, disease genes and genetic diversity.

Proper citation: Online Encyclopedia for Genetic Epidemiology studies (RRID:SCR_001825) Copy   

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http://www.well.ox.ac.uk/happy/

THIS RESOURCE IS NO LONGER IN SERVICE. Documented on February 28,2023. Software package for Multipoint QTL Mapping in Genetically Heterogeneous Animals (entry from Genetic Analysis Software) The method is implemented in a C-program and there is now an R version of HAPPY. You can run HAPPY remotely from their web server using your own data (or try it out on the data provided for download).

Proper citation: Happy (RRID:SCR_001395) Copy   

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

Software application where GC implements the genomic control models. GCF implements the basic Genomic Control approach, but adjusts the p-values for uncertainty in the estimated effect of substructure. This approach is preferable if a large number of tests will be evaluated because it provides a more accurrate assessment of the significance level for small p-values. (entry from Genetic Analysis Software)

Proper citation: GC/GCF (RRID:SCR_009075) Copy   

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