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http://depts.washington.edu/adrcweb/

Research center investigating the basic mechanisms underlying the development of Alzheimer's disease and related disorders, directing particular attention to biomarkers and experimental new treatments. They also continue to search for genetic risk factors underlying Alzheimer's disease (AD). Their main priorities are to find causes, effective treatments, and prevention strategies. Their investigators also are partnering with other Alzheimer's Centers across the country to evaluate promising new medications and other treatments for AD. The ultimate goal of their basic and clinical studies is to improve patient care and function, and improve the quality of life for both the patient and the caregiver. ADRC Cores: * Administration * Clinical Core * Satellite Core * Data Management & Biostatistics * Neuropathology Core * Education & Information Transfer * Genetics

Proper citation: University of Washington Alzheimers Disease Research Center (RRID:SCR_008814) Copy   

•   Source: SciCrunch Registry

http://rgd.mcw.edu

Database for genetic, genomic, phenotype, and disease data generated from rat research. Centralized database that collects, manages, and distributes data generated from rat genetic and genomic research and makes these data available to scientific community. Curation of mapped positions for quantitative trait loci, known mutations and other phenotypic data is provided. Facilitates investigators research efforts by providing tools to search, mine, and analyze this data. Strain reports include description of strain origin, disease, phenotype, genetics, immunology, behavior with links to related genes, QTLs, sub-strains, and strain sources.

Proper citation: Rat Genome Database (RGD) (RRID:SCR_006444) Copy   

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http://www.progenygenetics.com/

Fully customizable, comprehensive genetic pedigree and clinical data management software including a multi-user relational database with an integrated pedigree drawing component to manage genetic and pedigree data in one database. Manage Pedigrees, Individuals, SNPs, STRs, Samples, Plates, Genotypes and exports to multiple analysis platforms. (entry from Genetic Analysis Software) * LIMS software, providing advanced sample tracking and management (including functionality to generate and record barcodes) and configurable workflows for your specific environment. * Full genotype management gives users the ability to track not only family-based studies, but Whole Genome Association studies containing 1000''s of samples with large arrays.

Proper citation: PROGENY (RRID:SCR_006647) Copy   

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http://archives.niddk.nih.gov/patient/aask/aask.aspx

Clinical trial investigating whether a specific class of antihypertensive drugs (beta-adrenergic blockers, calcium channel blockers, or angiotensin converting enzyme inhibitors) and/or the level of blood pressure would influence progression of hypertensive kidney disease in African Americans. The initiative consisting of 21 clinical centers and a data-coordinating center is followed by a Continuation of AASK Cohort Study to investigate the environmental, socio-economic, genetic, physiologic, and other co-morbid factors that influence progression of kidney disease in a well-characterized cohort of African Americans with hypertensive kidney disease. Only patients who were previously in the randomized trial are eligible for the cohort study. A significant discovery was made in the treatment strategy for slowing kidney disease caused by hypertension. Angiotensin-converting enzyme (ACE) inhibitors, compared with calcium channel blockers, were found to slow kidney disease progression by 36 percent, and they drastically reduced the risk of kidney failure by 48 percent in patients who had at least one gram of protein in the urine, a sign of kidney failure. ACE inhibitors have been the preferred treatment for hypertension caused by diabetes since 1994; however, calcium channel blockers have been particularly effective in controlling blood pressure in African Americans. The AASK study now recommends ACE inhibitors to protect the kidneys from the damaging effects of hypertension. The Continuation of AASK Cohort Study will be followed at the clinical centers. The patients will be provided with the usual clinical care given to all such patients at the respective centers. Baseline demographic information, selected laboratory tests, and other studies are being obtained at the initiation of the Continuation Study. The patients will be seen quarterly at the centers, and some selected studies done at these visits. Samples will be obtained and stored for additional studies and analyses at a later date.

Proper citation: AASK Clinical Trial and Cohort Study (RRID:SCR_006985) Copy   

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http://mga.bionet.nsc.ru/soft/maia-1.0/

Software package of programs for complex segregation analysis in animal pedigrees.

Proper citation: MAIA (RRID:SCR_007153) Copy   

•   Source: SciCrunch Registry

http://wwwn.cdc.gov/dls/genetics/rmmaterials/default.aspx

The goal of the Genetic Testing Reference Materials Coordination Program (GeT-RM) is to coordinate a self-sustaining community process to improve the availability of appropriate and characterized reference materials for: Quality control (QC), Proficiency testing (PT), Test development & validation, Research. The purpose of this program is: - To help the genetic testing community obtain appropriate and characterized reference materials - To facilitate and coordinate information exchange between users and providers of QC and reference materials - To coordinate efforts for contribution, development, characterization and distribution of reference materials for genetic testing Get-RM provides information about cell lines, DNA, and other kinds of materials that could be used as reference materials for molecular genetic testing. Some of these materials have been characterized by the GeT-RM program and can be divided into three categories: - Genetic Inherited Disease & Pharmacogenetics This section includes information about cell lines, DNA, and other samples that can be used as reference materials for various inherited diseases (including cystic fibrosis, fragile X, Huntington disease, and Ashkenazi Jewish-related diseases), pharmacogenetic loci, and biochemical genetics. The GeT-RM program has confirmed the genotype of many of the genomic DNA samples through testing in multiple clinical genetic laboratories. - Molecular Oncology This section includes information about commercially available cell lines, DNA, and other kinds of materials that could be used as reference materials for various types of cancers, including leukemia/lymphoma and solid tumors. - Infectious Disease This section includes information about commercially available cell lines, DNA, and other kinds of materials that could be used as reference materials for various infectious disease pathogens including viruses, bacteria, and protozoa.

Proper citation: Center for Disease Control and Prevention: Genetic Testing Reference Materials Coordination Program (RRID:SCR_013029) Copy   

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http://www.ornl.gov/sci/techresources/Human_Genome/home.shtml

This resource gives information about the U.S. Human Genome Project, which was was a 13-year effort to to discover all the estimated 20,000-25,000 human genes and make them accessible for further biological study. The primary project goals were to: - identify all the approximately 20,000-25,000 genes in human DNA, - determine the sequences of the 3 billion chemical base pairs that make up human DNA, - store this information in databases, - improve tools for data analysis, - transfer related technologies to the private sector, and - address the ethical, legal, and social issues (ELSI) that may arise from the project. To help achieve these goals, researchers also studied the genetic makeup of several nonhuman organisms. These include the common human gut bacterium Escherichia coli, the fruit fly, and the laboratory mouse. These parallel studies helped to develop technology and interpret human gene function. Sponsors: The DOE Human Genome Program and the NIH National Human Genome Research Institute (NHGRI) together sponsored the U.S. Human Genome Project.

Proper citation: Human Genome Project Information (RRID:SCR_013028) Copy   

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http://sift.bii.a-star.edu.sg/

Data analysis service to predict whether an amino acid substitution affects protein function based on sequence homology and the physical properties of amino acids. SIFT can be applied to naturally occurring nonsynonymous polymorphisms and laboratory-induced missense mutations. (entry from Genetic Analysis Software) Web service is also available.

Proper citation: SIFT (RRID:SCR_012813) Copy   

•   Source: SciCrunch Registry

http://web.bioinformatics.ic.ac.uk/eqtlexplorer/

THIS RESOURCE IS NO LONGER IN SERVICE. Documented on June 1,2023. eQTL Explorer was developed as a computational resource to visualize and explore data from combined genome-wide expression and linkage studies is essential for the development of testable hypotheses. This visualization tool stores expression profiles, linkage data and information from external sources in a relational database and enables simultaneous visualization and intuitive interpretation of the combined data via a Java graphical interface. eQTL Explorer also provides a new and powerful tool to interrogate these very large and complex datasets. eQTLexplorer allows users to mine and understand data from a repository of genetical genomics experiments. It will graphically display eQTL information based on a certain number of selection criteria, including: tissue type, p-value, cis/trans, probeset Affymetrix id and PQTL type. Sponsors: This work was funded by the MRC Clinical Sciences Centre and the Wellcome Trust programme for Cardiovascular Functional Genomics.

Proper citation: eQTL Visualization Tool (RRID:SCR_013413) Copy   

•   Source: SciCrunch Registry

http://www.jurgott.org/linkage/ListSoftware.html

THIS RESOURCE IS NO LONGER IN SERVICE. Documented on May 4th,2023. Listing of computer software for the gene mapping community on the following topics: genetic linkage analysis for human pedigree data, QTL analysis for animal/plant breeding data, genetic marker ordering, genetic association analysis, haplotype construction, pedigree drawing, and population genetics. The inclusion of a program should not be interpreted as an endorsement to that program from us. In the last few years, new technology produces new types of genetic data, and the scope of genetic analyses change dramatically. It is no longer obvious whether a program should be included or excluded from this list. Topics such as next-generation-sequencing (NGS), gene expression, genomics annotation, etc. can all be relevant to a genetic study, yet be specialized topics by themselves. Though programs on variance calling from NSG can be in, those can sequence alignment might be out; programs on eQTL can be in, those on differential expression might be out. This page was created by Dr. Wentian Li, when he was at Columbia University (1995-1996). It was later moved to Rockefeller University (1996-2002), and now takes its new home at North Shore LIJ Research Institute (2002-now). The present copy is maintained by Jurg Ott as a single file. More than 240 programs have been listed by December 2004, more than 350 programs by August 2005, close to 400 programs by December 2006, and close to 480 programs by November 2008, and over 600 programs by October 2012. A version of the searchable database was developed by Zhiliang Hu of Iowa State University, and a recent round of updating was assisted by Wei JIANG of Harbin Medical School. Some earlier software can be downloaded from EBI: ftp://ftp.ebi.ac.uk/pub/software/linkage_and_mapping/ (Linkage and Mapping Software Repository), and http://genamics.com/software/index.htm may contain archived copy of some programs.

Proper citation: Genetic Analysis Software (RRID:SCR_013155) Copy   

•   Source: SciCrunch Registry

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

THIS RESOURCE IS NO LONGER IN SERVICE. Documented on May 24,2023. Software application that simultaneously estimates a trait-locus position and its genetic effects for affected relative pairs (ARP) by one of two methods. Either allow a different trait-locus effect for each ARP type, or constrain the trait-locus effects according to the marginal effect of a single susceptibility locus. We include a goodness of fit statistic for the constrained model. (entry from Genetic Analysis Software)

Proper citation: ARP.GEE (RRID:SCR_013134) Copy   

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http://genetics.bwh.harvard.edu/pph2/

Software tool which predicts possible impact of amino acid substitution on structure and function of human protein using straightforward physical and comparative considerations. PolyPhen-2 is new development of PolyPhen tool for annotating coding nonsynonymous SNPs.

Proper citation: PolyPhen: Polymorphism Phenotyping (RRID:SCR_013189) Copy   

•   Source: SciCrunch Registry

http://marrvel.org/

Web tool to search multiple public variant databases simultaneously and provide a unified interface to facilitate the search process. Used for integration of human and model organism genetic resources to facilitate functional annotation of the human genome. Used for analysis of human genes and variants by cross-disciplinary integration of records available in public databases to facilitate clinical diagnosis and basic research.

Proper citation: MARRVEL (RRID:SCR_016871) Copy   

•   Source: SciCrunch Registry

https://www.iigm.it/site/index.php?l=ENG

Private research institute in Turin, Italy. Research programs in immunogenetics, functional genomics, genomic epidemiology, tumour diagnostic and prognostic biomarker research, epigenetic modifications in disease, quantitative biology and computational neuroscience.

Proper citation: Italian Institute for Genomic Medicine; Turin; Italy (RRID:SCR_017062) Copy   

•   Source: SciCrunch Registry

https://cmmt.ubc.ca/

Center is part of University of British Columbia Faculty of Medicine, located at British Columbia Children Hospital Research Institute (BCCHR) in Vancouver, British Columbia, Canada. Research at CMMT is focused on discovering genetic susceptibility to illnesses such as Huntington Disease, Type 2 diabetes and bipolar disorder.

Proper citation: University of British Columbia Centre for Molecular Medicine and Therapeutics (RRID:SCR_017241) Copy   

•   Source: SciCrunch Registry

https://www.beast2.org/

Software package for advanced Bayesian evolutionary analysis by sampling trees. Used for phylogenetics, population genetics and phylodynamics. Program for Bayesian phylogenetic analysis of molecular sequences. Estimates rooted, time measured phylogenies using strict or relaxed molecular clock models. Framework can be extended by third parties. Comprised of standalone programs including BEAUti, BEAST, MASTER, RBS, SNAPP, MultiTypeTree, BDSKY, LogAnalyser, LogCombiner, TreeAnnotator, DensiTree and package manager.

Proper citation: BEAST2 (RRID:SCR_017307) Copy   

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https://deepblue.mpi-inf.mpg.de/

Central data access hub for large collections of epigenomic data. It organizes data from different sources using controlled vocabularies and ontologies. Data Server for storing, organizing, searching, and retrieving genomic and epigenomic data, handling associated metadata, and to perform different types of analysis.

Proper citation: Deep Blue Epigenomic Data Server (RRID:SCR_017490) Copy   

•   Source: SciCrunch Registry

http://taylor0.biology.ucla.edu/structureHarvester/

Web based program for collating results generated by program STRUCTURE. Provides assess and visualize likelihood values across multiple values of K and hundreds of iterations for easier detection of number of genetic groups that best fit data. Reformats data for use in downstream programs, such as CLUMPP.It is complement for using software Structure in genetics population. Website and program for visualizing STRUCTURE output and implementing Evanno method., THIS RESOURCE IS NO LONGER IN SERVICE. Documented on September 16,2025.

Proper citation: Structure Harvester (RRID:SCR_017636) Copy   

•   Source: SciCrunch Registry

http://chemrich.fiehnlab.ucdavis.edu/

Software tool for chemical similarity enrichment analysis of metabolomics datasets. Used in studies to uncover biological mechanisms in organisms under genetic or environmental stress in system biology manner or finding risk factors for chronic diseases in exposome wise association studies using blood specimens. Allows users to realize pathway analysis.

Proper citation: ChemRICH (RRID:SCR_017609) Copy   

•   Source: SciCrunch Registry

https://depmap.org/portal/

Portal for identifying genetic and pharmacologic dependencies and biomarkers that predicts them by providing access to datasets, visualizations, and analysis tools that are being used by Cancer Dependency Map Project at Broad Institute. Project to systematically identify genes and small molecule dependencies and to determine markers that predict sensitivity. All data generated by DepMap Project are available to public under CC BY 4.0 license on quarterly basis and pre-publication.

Proper citation: Cancer Dependency Map Portal (RRID:SCR_017655) Copy   

•   Source: SciCrunch Registry