Mouse Phenome Database: towards a more FAIR-compliant and TRUST-worthy data repository and tool suite for phenotypes and genotypes

The Mouse Phenome Database (MPD; https://phenome.jax.org; RRID:SCR_003212), supported by the US National Institutes of Health, is a Biomedical Data Repository listed in the Trans-NIH Biomedical Informatics Coordinating Committee registry. As an increasingly FAIR-compliant and TRUST-worthy data repos...

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Published inNucleic acids research Vol. 51; no. D1; pp. D1067 - D1074
Main Authors Bogue, Molly A, Ball, Robyn L, Philip, Vivek M, Walton, David O, Dunn, Matthew H, Kolishovski, Georgi, Lamoureux, Anna, Gerring, Matthew, Liang, Hongping, Emerson, Jake, Stearns, Tim, He, Hao, Mukherjee, Gaurab, Bluis, John, Desai, Sejal, Sundberg, Beth, Kadakkuzha, Beena, Kunde-Ramamoorthy, Govindarajan, Chesler, Elissa J
Format Journal Article
LanguageEnglish
Published England Oxford University Press 06.01.2023
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ISSN0305-1048
1362-4962
1362-4962
DOI10.1093/nar/gkac1007

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Summary:The Mouse Phenome Database (MPD; https://phenome.jax.org; RRID:SCR_003212), supported by the US National Institutes of Health, is a Biomedical Data Repository listed in the Trans-NIH Biomedical Informatics Coordinating Committee registry. As an increasingly FAIR-compliant and TRUST-worthy data repository, MPD accepts phenotype and genotype data from mouse experiments and curates, organizes, integrates, archives, and distributes those data using community standards. Data are accompanied by rich metadata, including widely used ontologies and detailed protocols. Data are from all over the world and represent genetic, behavioral, morphological, and physiological disease-related characteristics in mice at baseline or those exposed to drugs or other treatments. MPD houses data from over 6000 strains and populations, representing many reproducible strain types and heterogenous populations such as the Diversity Outbred where each mouse is unique but can be genotyped throughout the genome. A suite of analysis tools is available to aggregate, visualize, and analyze these data within and across studies and populations in an increasingly traceable and reproducible manner. We have refined existing resources and developed new tools to continue to provide users with access to consistent, high-quality data that has translational relevance in a modernized infrastructure that enables interaction with a suite of bioinformatics analytic and data services.
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The authors wish it to be known that, in their opinion, the first two authors should be regarded as Joint First Authors.
ISSN:0305-1048
1362-4962
1362-4962
DOI:10.1093/nar/gkac1007