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

THIS RESOURCE IS NO LONGER IN SERVICE. Documented on July 31,2025. Software application aiming at identifying haplotype blocks. The likelihood of the data is calculated minus the model complexity. The resulting blocks have very low diversity and the linkage disequilibrium with SNP's outside the blocks is low. (entry from Genetic Analysis Software)

Proper citation: ENTROPY BLOCKER (RRID:SCR_000123) Copy   

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http://www.homozygositymapper.org/

A web-based approach of homozygosity mapping that can handle tens of thousands markers. User can upload their own SNP genotype files to the database. Intuitive graphic interface is provided to view the homozygous stretches, with the ability of zooming into single chromosomes or user-defined chromosome regions. The underlying genotypes in all samples are displayed. The software is also integrated with our candidate gene search engine, GeneDistiller, so that users can interactively determine the most promising gene. (entry from Genetic Analysis Software)

Proper citation: HOMOZYGOSITYMAPPER (RRID:SCR_001714) Copy   

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http://analysis2.bio-x.cn/myAnalysis.php

A powerful web-based platform for analyses of linkage disequilibrium, haplotype construction, and genetic association at polymorphism loci.

Proper citation: SHEsis: Analysis Tools For Random Samples (RRID:SCR_002958) Copy   

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http://eyegene.ophthy.med.umich.edu/madeline/

Software tool designed for preparing, visualizing, and exploring human pedigree data used in genetic linkage studies. It converts pedigree and marker data into formats required by popular linkage analysis packages, provides powerful ways to query pedigree data sets, and produces Postscript pedigree drawings that are useful for rapid data review.

Proper citation: MADELINE (RRID:SCR_001979) Copy   

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http://www.depressiontools.org/

Online instrument that estimates whether a biomarker predicting outcome of depression treatment is likely to be clinically significant.

Proper citation: DepressionTools.org Clinical Significance Calculator (RRID:SCR_003873) Copy   

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http://chgr.mc.vanderbilt.edu/page/gist

Software package to test if a marker can account in part for the linkage signal in its region. There are two versions of the software: Windows and Linux/Unix.

Proper citation: Genotype-IBD Sharing Test (RRID:SCR_006257) Copy   

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http://cbl-gorilla.cs.technion.ac.il/

A tool for identifying and visualizing enriched GO terms in ranked lists of genes. It can be run in one of two modes: * Searching for enriched GO terms that appear densely at the top of a ranked list of genes or * Searching for enriched GO terms in a target list of genes compared to a background list of genes.

Proper citation: GOrilla: Gene Ontology Enrichment Analysis and Visualization Tool (RRID:SCR_006848) 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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http://wpicr.wpic.pitt.edu/WPICCompGen/newcovibd/covibd.htm

Software application that refines linkage analysis of affected sibpairs by considering attributes or environmental exposures thought to affect disease liability. This refinement utilizes a mixture model in which a disease mutation segregates in only a fraction of the sibships, with the rest of the sibships unlinked. Covariate information is used to predict membership within the two groups corresponding to the linked and unlinked sibships. The pre-clustering model uses covariate information to first form two probabilistic clusters and then tests for excess IBD-sharing in the clusters. The Cov-IBD model determines probabilistic group membership by joint consideration of covariate and IBD values. (entry from Genetic Analysis Software)

Proper citation: COVIBD (RRID:SCR_009155) Copy   

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http://www.pypop.org/

Open-source software pipeline for population genomics. Designed for processing genotype and allele data and running population genetic analyses, including conformity to Hardy-Weinberg expectations; tests for balancing or directional selection; estimates of haplotype frequencies and measures and tests of significance for linkage disequilibrium.

Proper citation: PyPop (RRID:SCR_013425) 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 to compute composite measures of linkage disequilibrium, their variances and covariances, and statistical tests, for all pairs of alleles from two loci when linkage phase is unkown. An extension of Weir and Cockerham (1989) to apply to multi-allelic loci. (entry from Genetic Analysis Software)

Proper citation: COMPOSITELD (RRID:SCR_013132) Copy   

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http://knightadrc.wustl.edu/

The Charles F. and Joanne Knight Alzheimer Disease Research Center (Knight ADRC) supports researchers and our surrounding community in their pursuit of answers that will lead to improved diagnosis and care for persons with Alzheimer disease (AD). The Center is committed to the long-term goal of finding a way to effectively treat and prevent AD. The Knight ADRC facilitates advanced research on the clinical, genetic, neuropathological, neuroanatomical, biomedical, psychosocial, and neuropsychological aspects of Alzheimer disease, as well as other related brain disorders.

Proper citation: Washington University School of Medicine Knight Alzheimers Disease Research Center (RRID:SCR_000210) Copy   

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http://www.bioconductor.org/packages/release/bioc/html/CGEN.html

Software R package for analysis of case-control studies in genetic epidemiology.

Proper citation: CGEN (RRID:SCR_001251) Copy   

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http://www.morpholinodatabase.org/

Central database to house data on morpholino screens currently containing over 700 morpholinos including control and multiple morpholinos against the same target. A publicly accessible sequence-based search opens this database for morpholinos against a particular target for the zebrafish community. Morpholino Screens: They set out to identify all cotranslationally translocated genes in the zebrafish genome (Secretome/CTT-ome). Morpholinos were designed against putative secreted/CTT targets and injected into 1-4 cell stage zebrafish embryos. The embryos were observed over a 5 day period for defects in several different systems. The first screen examined 184 gene targets of which 26 demonstrated defects of interest (Pickart et al. 2006). A collaboration with the Verfaillie laboratory examined the knockdown of targets identified in a comparative microarray analysis of hematopoietic stem cells demonstrating how microarray and morpholino technologies can be used in conjunction to enrich for defects in specific developmental processes. Currently, many collaborations are underway to identify genes involved in morphological, kidney, skin, eye, pigment, vascular and hematopoietic development, lipid metabolism and more. The screen types referred to in the search functions are the specific areas of development that were examined during the various screens, which include behavior, general morphology, pigmentation, toxicity, Pax2 expression, and development of the craniofacial structures, eyes, kidneys, pituitary, and skin. Only data pertaining to specific tests performed are presented. Due to the complexity of this international collaboration and time constraints, not all morpholinos were subjected to all screen types. They are currently expanding public access to the database. In the future we will provide: * Mortality curves and dose range for each morpholino * Preliminary data regarding the effectiveness of each morpholino * Expanded annotation for each morpholino * External linkage of our morpholino sequences to ZFIN and Ensembl. To submit morpholino-knockdown results to MODB please contact the administrator for a user name and password.

Proper citation: Morpholino Database (RRID:SCR_001378) Copy   

•   Source: SciCrunch Registry

http://www.genome.jp/kegg/expression/

Database for mapping gene expression profiles to pathways and genomes. Repository of microarray gene expression profile data for Synechocystis PCC6803 (syn), Bacillus subtilis (bsu), Escherichia coli W3110 (ecj), Anabaena PCC7120 (ana), and other species contributed by the Japanese research community.

Proper citation: Kyoto Encyclopedia of Genes and Genomes Expression Database (RRID:SCR_001120) Copy   

•   Source: SciCrunch Registry

http://neuronalarchitects.com/ibiofind.html

THIS RESOURCE IS NO LONGER IN SERVICE, documented August 17, 2016. C#.NET 4.0 WPF / OWL / REST / JSON / SPARQL multi-threaded, parallel desktop application enables the construction of biomedical knowledge through PubMed, ScienceDirect, EndNote and NIH Grant repositories for tracking the work of medical researchers for ranking and recommendations. Users can crawl web sites, build latent semantic indices to generate literature searches for both Clinical Translation Science Award and non-CTSA institutions, examine publications, build Bayesian networks for neural correlates, gene to gene interactions, protein to protein interactions and as well drug treatment hypotheses. Furthermore, one can easily access potential researcher information, monitor and evolve their networks and search for possible collaborators and software tools for creating biomedical informatics products. The application is designed to work with the ModelMaker, R, Neural Maestro, Lucene, EndNote and MindGenius applications to improve the quality and quantity of medical research. iBIOFind interfaces with both eNeoTutor and ModelMaker 2013 Web Services Implementation in .NET for eNeoTutor to aid instructors to build neuroscience courses as well as rare diseases. Added: Rare Disease Explorer: The Visualization of Rare Disease, Gene and Protein Networks application module. Cinematics for the Image Finder from Yale. The ability to automatically generate and update websites for rare diseases. Cytoscape integration for the construction and visualization of pathways for Molecular targets of Model Organisms. Productivity metrics for medical researchers in rare diseases. iBIOFind 2013 database now includes over 150 medical schools in the US along with Clinical Translational Science Award Institutions for the generation of biomedical knowledge, biomedical informatics and Researcher Profiles.

Proper citation: iBIOFind (RRID:SCR_001587) Copy   

•   Source: SciCrunch Registry

http://www.norcomm.org/index.htm

Large-scale research initiative focused on developing and distributing a library of mouse embryonic stem (ES) cell lines carrying single gene trapped or targeted mutations across the mouse genome. NorCOMM's large and growing archive of ES cells is publicly available on a cost-recovery basis from the Canadian Mouse Mutant Repository. As an international public resource, access to clones is unrestricted and nonexclusive. Through NorCOMM's affiliation with the Canadian Mouse Consortium (CMC), NorCOMM also provides clients with a single point of access to regional mouse derivation, phenotyping, genetic and archiving services across Canada. These value-added services can help your company harness NorCOMM's resources for drug discovery, target discovery and preclinical validation.

Proper citation: North American Conditional Mouse Mutagenesis Project (RRID:SCR_001614) Copy   

•   Source: SciCrunch Registry

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   

•   Source: SciCrunch Registry

https://www.drugabuse.gov/publications/drugfacts/genetics-epigenetics-addiction

THIS RESOURCE IS NO LONGER IN SERVICE, documented on July 17, 2013. An archived video on the web providing comprehensive and hands-on training in genetics and epigenetic methodology. The purpose of the course is to provide an introduction to approaches and tools for identifying genes that confer vulnerability to addiction and individual differences in responses to treatments. The course is targeted to those who are new to the field of addiction genetics. The course was held over 5 days with lectures and hands-on demonstrations given each day. Viewers of the course will gain familiarity with conceptual and practical approaches to complex disorders using relevant genetic and epigenetic databases, and appropriate statistical and empirical approaches. Topics covered Behavioral genetics, genetic epidemiology, twin and adoption studies, statistical genetic concepts and approaches for mapping complex traits, haplotype based approaches for association mapping, genome-wide scans for addictive disorders, application of linkage for mapping genes and genetic loci for addictive disorders, pharmacogenomics of treatment of addictive disorders, Baysian Methods for identifying gene-gene interactions, analysis of copy number variation, practical use of genetic databases, mapping of complex traits in mice, methods for analyzing gene expression, and methods for doing epigenetic analysis are covered. The course was held April 4, 2008, at the Bethesda North Marriott Hotel and Conference Center, 5701 Marinelli Road, Bethesda, MD 20852.

Proper citation: Short Course on the Genetics and Epigenetics of Addiction National Institute on Drug Abuse: Archived Video (RRID:SCR_002783) Copy   

•   Source: SciCrunch Registry

https://www.ddbj.nig.ac.jp/jga/index-e.html

A service for permanent archiving and sharing of all types of personally identifiable genetic and phenotypic data resulting from biomedical research projects. The JGA contains exclusive data collected from individuals whose consent agreements authorize data release only for specific research use or to bona fide researchers. Strict protocols govern how information is managed, stored and distributed by the JGA. Once processed, all data are encrypted. The JGA accepts only de-identified data approved by JST-NBDC. The JGA implements access-granting policy whereby the decisions of who will be granted access to the data resides with the JST-NBDC. After data submission the JGA team will process the data into databases and archive the original data files. The accepted data types include manufacturer-specific raw data formats from the array-based and new sequencing platforms. The processed data such as the genotype and structural variants or any summary level statistical analyses from the original study authors are stored in databases. The JGA also accepts and distributes any phenotype data associated with the samples. For other human biological data, please contact the NBDC human data ethical committee.

Proper citation: Japanese Genotype-phenotype Archive (JGA) (RRID:SCR_003118) Copy   

•   Source: SciCrunch Registry