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http://bmerc.bu.edu/projects/wdrepeat/

THIS RESOURCE IS NO LONGER IN SERVICE, documented on August 26, 2016. This website contains a library of WD-repeat containing proteins in which the repeats appear as multi-aligned sets. WD-repeat-containing proteins are those that contain 4 or more copies of the WD-repeat (tryptophan-aspartate repeat), a sequence motif approximately 31 amino acids long, that encodes a structural repeat. This repeat is described by the following profile, where x is ANY amino acid. By clicking on each high-lighted character you will obtain the distribution of amino acids found at that position of the repeat among an aligned set of WD-repeat containing proteins. The tertiary structure of only one member of this family has been determined, that of the G protein beta subunit, which contains 7 WD-repeats. Each of the 7 repeats folds into a small antiparallel beta-sheet. The over-lines above indicate the position of these strands, with a being the strand closest to the central pore and d at the external surface of the folded protein. These sheets are arranged around a central pseudosymmetry axis into a beta propeller. The WD-repeat-containing proteins form a very large family that is diverse in both its function and domain structure. Within all these proteins the WD-repeat domains are thought to have two common features: the domain folds into a beta propeller; and the domains form a platform without any catalytic activity on which multiple protein complexes assemble reversibly. The fact that these proteins play such key roles in the formation of protein-protein complexes in nearly all the major pathways and organelles unique to eukaryotic cells has two important implications. It supports both their ancient and proto eukaryotic origins and supports a likely association with many genetic diseases.

Proper citation: WD repeat Family of Proteins (RRID:SCR_002160) Copy   

•   Source: SciCrunch Registry

http://irefindex.org

An index of protein interactions available in a number of primary interaction databases including BIND, BioGRID, CORUM, DIP, HPRD, IntAct, MINT, MPact, MPPI and OPHID. This index includes multiple interaction types including physical and genetic (mapped to their corresponding protein products) as determined by a multitude of methods. This index allows the user to search for a protein and retrieve a non-redundant list of interactors for that protein. iRefIndex uses the Sequence Global Unique Identifier (SEGUID) to group proteins and interactions into redundant groups. This method allows users to integrate their own data with the iRefIndex in a way that ensures proteins with the exact same sequence will be represented only once. iRefIndex project has three long term objectives: # to facilitate exchange of interaction data between interaction databases. # to consolidate interaction data from multiple sources. # to provide feedback to source interaction databases. iRefIndex is made available in a number of formats: MITAB tab-delimited text files, iRefWeb interface, iRefScape plugin for Cytoscape, PSICQUIC Web services, and an interface for the R programming language environment.

Proper citation: Interaction Reference Index (RRID:SCR_002085) Copy   

•   Source: SciCrunch Registry

http://genecards.org

Database of human genes that provides concise genomic, proteomic, transcriptomic, genetic and functional information on all known and predicted human genes. Information featured in GeneCards includes orthologies, disease relationships, mutations and SNPs, gene expression, gene function, pathways, protein-protein interactions, related drugs and compounds and direct links to cutting edge research reagents and tools such as antibodies, recombinant proteins, clones, expression assays and RNAi reagents.

Proper citation: GeneCards (RRID:SCR_002773) Copy   

•   Source: SciCrunch Registry

http://www.cdc.gov/genomics/hugenet/default.htm

Human Genome Epidemiology Network, or HuGENet, 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. Its goals include: establishing an information exchange that promotes global collaboration in developing peer-reviewed information on the relationship between human genomic variation and health and on the quality of genetic tests for screening and prevention; providing training and technical assistance to researchers and practitioners interested in assessing the role of human genomic variation on population health and how such information can be used in practice; developing an updated and accessible knowledge base on the World Wide Web; and promoting the use of this knowledge base by health care providers, researchers, industry, government, and the public for making decisions involving the use of genetic information for disease prevention and health promotion. HuGENet collaborators come from multiple disciplines such as epidemiology, genetics, clinical medicine, policy, public health, education, and biomedical sciences. Currently, there are 4 HuGENet Coordinating Centers for the implementation of HuGENet activities: CDC''s Office of Public Health Genomics, Atlanta, Georgia; HuGENet UK Coordinating Center, Cambridge, UK; University of Ioannina, Greece; University of Ottawa , Ottawa, Canada. HuGENet includes: HuGE e-Journal Club: The HuGE e-Journal Club is an electronic discussion forum where new human genome epidemiologic (HuGE) findings, published in the scientific literature in the CDC''s Office of Public Health Genomics Weekly Update, will be abstracted, summarized, presented, and discussed via a newly created HuGENet listserv. HuGE Reviews: A HuGE Review identifies human genetic variations at one or more loci, and describes what is known about the frequency of these variants in different populations, identifies diseases that these variants are associated with and summarizes the magnitude of risks and associated risk factors, and evaluates associated genetic tests. Reviews point to gaps in existing epidemiologic and clinical knowledge, thus stimulating further research in these areas. HuGE Fact Sheets: HuGE Fact Sheets summarize information about a particular gene, its variants, and associated diseases. HuGE Case Studies: An on-line presentation designed to sharpen your epidemiological skills and enhance your knowledge on genomic variation and human diseases. Its purpose is to train health professionals in the practical application of human genome epidemiology (HuGE), which translates gene discoveries to disease prevention by integrating population-based data on gene-disease relationships and interventions. Students will acquire conceptual and practical tools for critically evaluating the growing scientific literature in specific disease areas. HUGENet Publications: Articles related to the HuGENet movement written by our HuGENet collaborators. HuGE Navigator: An integrated, searchable 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. HuGE Workshops: HuGENet has sponsored meetings and workshops with national and international partners since 2001. Available are detailed summaries, agendas or the ability to download speaker slides. HuGE Book: Human Genome Epidemiology: A Scientific Foundation for Using Genetic Information to Improve Health and Prevent Disease. (The findings and conclusions in this book are those of the author(s) and do not necessarily represent the views of the funding agency.) HuGENet Collaborators: HuGENet is interested in establishing collaborations with individuals and organizations working on population based research involving genetic information. HuGE Funding: Funding opportunities for specific population-based genetic epidemiology research projects are available. Research initiatives whose aims include assessing the prevalence of human genetic variation, the association between genetic variants and human diseases, the measurement of gene-gene or gene-environment interaction, and the evaluation of genetic tests for screening and prevention are compiled to create a posted listing. Additional information and application details can be found by clicking on the respective links.

Proper citation: Human Genome Epidemiology Network (RRID:SCR_013117) Copy   

•   Source: SciCrunch Registry

https://www.drugabuse.gov

Portal provides list of genetic resources such as Brain Atlases and genomes for various species provided by National Institute of Drug Abuse.

Proper citation: Compilation of Genetics Resource Databases (RRID:SCR_017501) 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://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://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

http://www-rcf.usc.edu/~gqian/software.htm (not available)

THIS RESOURCE IS NO LONGER IN SERVICE. Documented on September 23,2022. Software application (entry from Genetic Analysis Software)

Proper citation: MRH (RRID:SCR_000841) Copy   

•   Source: SciCrunch Registry

http://www.biosciences-labs.bham.ac.uk/Kearsey/

Software application providing a user freiendly way to perform QTL analysis. The software currently allows 3 types of QTL analysis: (1) single marker ANOVA. (2) marker regression. (3) interval mapping by regression. (entry from Genetic Analysis Software)

Proper citation: QTL CAFE (RRID:SCR_000844) Copy   

•   Source: SciCrunch Registry

https://sites.google.com/site/fdudbridge/software/pelican

Software utility for graphically editing the pedigree data files used by programs such as FASTLINK, VITESSE, GENEHUNTER and MERLIN. It can read in and write out pedigree files, saving changes that have been made to the structure of the pedigree. Changes are made to the pedigree via a graphical display interface. The resulting display can be saved as a pedigree file and as a graphical image file.

Proper citation: PELICAN (RRID:SCR_001695) Copy   

•   Source: SciCrunch Registry

http://wwwchg.duhs.duke.edu/research/osa.html

THIS RESOURCE IS NO LONGER IN SERVICE. Documented on August 19,2025. Software application that allows the researcher to evaluate evidence for linkage even when heterogeneity is present in a data set. This is not an unusual occurrence when studying diseases of complex origin. Families are ranked by covariate values in order to test evidence for linkage among homogeneous subsets of families. Because families are ranked, a priori covariate cutpoints are not necessary. Covariates may include linkage evidence at other genes, environmental exposures, or biological trait values such as cholesterol, age at onset, and so on.

Proper citation: OSA (RRID:SCR_002016) Copy   

•   Source: SciCrunch Registry

http://csg.sph.umich.edu//abecasis/Metal/

Software application designed to facilitate meta-analysis of large datasets (such as several whole genome scans) in a convenient, rapid and memory efficient manner. (entry from Genetic Analysis Software)

Proper citation: METAL (RRID:SCR_002013) Copy   

•   Source: SciCrunch Registry