Document Type
Article
Publication Date
12-1-2023
Original Citation
Bogue MA,
Ball R,
Walton D,
Dunn M,
Kolishovski G,
Berger A,
Lamoureux A,
Grubb SC,
Gerring M,
Kim M,
Liang H,
Emerson J,
Stearns T,
He H,
Mukherjee G,
Bluis J,
Davis S,
Desai S,
Sundberg BA,
Kadakkuzha B,
Kunde-Ramamoorthy G,
Philip VM,
Chesler E.
Mouse phenome database: curated data repository with interactive multi-population and multi-trait analyses. Mamm Genome. 2023;34(4):509-19.
Keywords
JMG, SS1, Mice, Animals, Mice, Inbred Strains, Phenotype, Phenomics
JAX Source
Mamm Genome. 2023;34(4):509-19.
ISSN
1432-1777
PMID
37581698
DOI
https://doi.org/10.1007/s00335-023-10014-3
Grant
This work was supported by the National Institutes of Health [DA028420, AG066346 to MAB; DA039841, OD030187 to EJC and RLB].
Abstract
The Mouse Phenome Database continues to serve as a curated repository and analysis suite for measured attributes of members of diverse mouse populations. The repository includes annotation to community standard ontologies and guidelines, a database of allelic states for 657 mouse strains, a collection of protocols, and analysis tools for flexible, interactive, user directed analyses that increasingly integrates data across traits and populations. The database has grown from its initial focus on a standard set of inbred strains to include heterogeneous mouse populations such as the Diversity Outbred and mapping crosses and well as Collaborative Cross, Hybrid Mouse Diversity Panel, and recombinant inbred strains. Most recently the system has expanded to include data from the International Mouse Phenotyping Consortium. Collectively these data are accessible by API and provided with an interactive tool suite that enables users' persistent selection, storage, and operation on collections of measures. The tool suite allows basic analyses, advanced functions with dynamic visualization including multi-population meta-analysis, multivariate outlier detection, trait pattern matching, correlation analyses and other functions. The data resources and analysis suite provide users a flexible environment in which to explore the basis of phenotypic variation in health and disease across the lifespan.
Comments
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