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Found 18 result(s)
The NCBI database of Genotypes and Phenotypes archives and distributes the results of studies that have investigated the interaction of genotype and phenotype, including genome-wide association studies, medical sequencing, molecular diagnostic assays, and association between genotype and non-clinical traits. The database provides summaries of studies, the contents of measured variables, and original study document text. dbGaP provides two types of access for users, open and controlled. Through the controlled access, users may access individual-level data such as phenotypic data tables and genotypes.
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DisGeNET is a discovery platform containing one of the largest publicly available collections of genes and variants associated to human diseases. DisGeNET integrates data from expert curated repositories, GWAS catalogues, animal models and the scientific literature. DisGeNET data are homogeneously annotated with controlled vocabularies and community-driven ontologies. Additionally, several original metrics are provided to assist the prioritization of genotype–phenotype relationships.
The Drosophila Genetic Reference Panel (DGRP) is a population consisting of more than 200 inbred lines derived from the Raleigh, USA population. The DGRP is a living library of common polymorphisms affecting complex traits, and a community resource for whole genome association mapping of quantitative trait loci.
The HomoloGene database provides a system for the automated detection of homologs among annotated genes of genomes across multiple species. These homologs are fully documented and organized by homology group. HomoloGene processing uses proteins from input organisms to compare and sequence homologs, mapping back to corresponding DNA sequences.
MalaCards is an integrated database of human maladies and their annotations, modeled on the architecture and richness of the popular GeneCards database of human genes. MalaCards mines and merges varied web data sources to generate a computerized web card for each human disease. Each MalaCard contains disease specific prioritized annotative information, as well as links between associated diseases, leveraging the GeneCards relational database, search engine, and GeneDecks set-distillation tool. As proofs of concept of the search/distill/infer pipeline we find expected elucidations, as well as potentially novel ones.
CorrDB has data of cattle, relating to meat production, milk production, growth, health, and others. This database is designed to collect all published livestock genetic/phenotypic trait correlation data, aimed at facilitating genetic network analysis or systems biology studies.
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The Cystic Fibrosis Mutation Database (CFTR1) was initiated by the Cystic Fibrosis Genetic Analysis Consortium in 1989 to increase and facilitate communications among CF researchers, and is maintained by the Cystic Fibrosis Centre at the Hospital for Sick Children in Toronto. The specific aim of the database is to provide up to date information about individual mutations in the CFTR gene. In a major upgrade in 2010, all known CFTR mutations and sequence variants have been converted to the standard nomenclature recommended by the Human Genome Variation Society.
The Drosophila Synthetic Population Resource (DSPR) consists of a new panel of over 1700 recombinant inbred lines (RILs) of Drosophila melanogaster, derived from two highly recombined synthetic populations, each created by intercrossing a different set of 8 inbred founder lines (with one founder line common to both populations). Complete genome sequence data for the founder lines are available, and in addition, there is a high resolution genetic map for each RIL. The DSPR has been developed as a community resource for high-resolution QTL mapping and is intended to be used widely by the Drosophila community.
The dbVar is a database of genomic structural variation containing data from multiple gene studies. Users can browse data containing the number of variant cells from each study, and filter studies by organism, study type, method and genomic variant. Organisms include human, mouse, cattle and several additional animals. ***NCBI will phase out support for non-human organism data in dbSNP and dbVar beginning on September 1, 2017 ***
OMIM is a comprehensive, authoritative compendium of human genes and genetic phenotypes that is freely available and updated daily. OMIM is authored and edited at the McKusick-Nathans Institute of Genetic Medicine, Johns Hopkins University School of Medicine, under the direction of Dr. Ada Hamosh. Its official home is omim.org.
The HUGO Gene Nomenclature Committee (HGNC) assigned unique gene symbols and names to over 35,000 human loci, of which around 19,000 are protein coding. This curated online repository of HGNC-approved gene nomenclature and associated resources includes links to genomic, proteomic and phenotypic information, as well as dedicated gene family pages.
ClinVar is a freely accessible, public archive of reports of the relationships among human variations and phenotypes, with supporting evidence. ClinVar thus facilitates access to and communication about the relationships asserted between human variation and observed health status, and the history of that interpretation. ClinVar processes submissions reporting variants found in patient samples, assertions made regarding their clinical significance, information about the submitter, and other supporting data. The alleles described in submissions are mapped to reference sequences, and reported according to the HGVS standard. ClinVar then presents the data for interactive users as well as those wishing to use ClinVar in daily workflows and other local applications. ClinVar works in collaboration with interested organizations to meet the needs of the medical genetics community as efficiently and effectively as possible
The IMPC is a confederation of international mouse phenotyping projects working towards the agreed goals of the consortium: To undertake the phenotyping of 20,000 mouse mutants over a ten year period, providing the first functional annotation of a mammalian genome. Maintain and expand a world-wide consortium of institutions with capacity and expertise to produce germ line transmission of targeted knockout mutations in embryonic stem cells for 20,000 known and predicted mouse genes. Test each mutant mouse line through a broad based primary phenotyping pipeline in all the major adult organ systems and most areas of major human disease. Through this activity and employing data annotation tools, systematically aim to discover and ascribe biological function to each gene, driving new ideas and underpinning future research into biological systems; Maintain and expand collaborative “networks” with specialist phenotyping consortia or laboratories, providing standardized secondary level phenotyping that enriches the primary dataset, and end-user, project specific tertiary level phenotyping that adds value to the mammalian gene functional annotation and fosters hypothesis driven research; and Provide a centralized data centre and portal for free, unrestricted access to primary and secondary data by the scientific community, promoting sharing of data, genotype-phenotype annotation, standard operating protocols, and the development of open source data analysis tools. Members of the IMPC may include research centers, funding organizations and corporations.
As with most biomedical databases, the first step is to identify relevant data from the research community. The Monarch Initiative is focused primarily on phenotype-related resources. We bring in data associated with those phenotypes so that our users can begin to make connections among other biological entities of interest. We import data from a variety of data sources. With many resources integrated into a single database, we can join across the various data sources to produce integrated views. We have started with the big players including ClinVar and OMIM, but are equally interested in boutique databases. You can learn more about the sources of data that populate our system from our data sources page https://monarchinitiative.org/about/sources.