Document Type

Article

Publication Date

1-6-2023

Keywords

JMG, Mice, Animals, Mice, Inbred Strains, Databases, Genetic, Phenotype, Genotype, Phenomics

JAX Source

Nucleic Acids Res. 2023;51(D1):D1067–D74.

ISSN

1362-4962

PMID

36330959

DOI

https://doi.org/10.1093/nar/gkac1007

Grant

National Institutes of Health [DA028420, AG066346 to M.A.B., DA039841, OD030187 to E.J.C. and R.L.B.]; Jackson Laboratory Director's Innovation Fund and Cube Initiative. Funding for open access charge: National Institutes of Health, NIDA.

Abstract

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.

Comments

This is an Open Access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/), which permits unrestricted reuse, distribution, and reproduction in any medium, provided the original work is properly cited.

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