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Mouse Phenome Database: a data repository and analysis suite for curated primary mouse phenotype data

The Mouse Phenome Database (MPD; https://phenome.jax.org) is a widely accessed and highly functional data repository housing primary phenotype data for the laboratory mouse accessible via APIs and providing tools to analyze and visualize those data. Data come from investigators around the world and...

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Detalles Bibliográficos
Autores principales: Bogue, Molly A, Philip, Vivek M, Walton, David O, Grubb, Stephen C, Dunn, Matthew H, Kolishovski, Georgi, Emerson, Jake, Mukherjee, Gaurab, Stearns, Timothy, He, Hao, Sinha, Vinita, Kadakkuzha, Beena, Kunde-Ramamoorthy, Govindarajan, Chesler, Elissa J
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Oxford University Press 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7145612/
https://www.ncbi.nlm.nih.gov/pubmed/31696236
http://dx.doi.org/10.1093/nar/gkz1032
Descripción
Sumario:The Mouse Phenome Database (MPD; https://phenome.jax.org) is a widely accessed and highly functional data repository housing primary phenotype data for the laboratory mouse accessible via APIs and providing tools to analyze and visualize those data. Data come from investigators around the world and represent a broad scope of phenotyping endpoints and disease-related traits in naïve mice and those exposed to drugs, environmental agents or other treatments. MPD houses rigorously curated per-animal data with detailed protocols. Public ontologies and controlled vocabularies are used for annotation. In addition to phenotype tools, genetic analysis tools enable users to integrate and interpret genome–phenome relations across the database. Strain types and populations include inbred, recombinant inbred, F1 hybrid, transgenic, targeted mutants, chromosome substitution, Collaborative Cross, Diversity Outbred and other mapping populations. Our new analysis tools allow users to apply selected data in an integrated fashion to address problems in trait associations, reproducibility, polygenic syndrome model selection and multi-trait modeling. As we refine these tools and approaches, we will continue to provide users a means to identify consistent, quality studies that have high translational relevance.