MouseFinder: Candidate disease genes from mouse phenotype data.

Authors

Chao-Kung Chen
Christopher J Mungall
Georgios V Gkoutos
Sandra C Doelken
Sebastian Köhler
Barbara J Ruef
Cynthia Smith
Monte Westerfield
Peter N Robinson
Suzanna E Lewis
Paul N Schofield
Damian Smedley

Document Type

Article

Publication Date

5-2012

JAX Source

Hum Mutat 2012 May; 33(5):858-66.

PMID

22331800

Volume

33

Issue

5

First Page

858

Last Page

866

ISSN

1098-1004

Abstract

Mouse phenotype data represents a valuable resource for the identification of disease-associated genes, especially where the molecular basis is unknown and there is no clue to the candidate gene's function, pathway involvement or expression pattern. However, until recently these data have not been systematically used due to difficulties in mapping between clinical features observed in humans and mouse phenotype annotations. Here, we describe a semantic approach to solve this problem and demonstrate highly significant recall of known disease-gene associations and orthology relationships. A Web application (MouseFinder; www.mousemodels.org) has been developed to allow users to search the results of our whole-phenome comparison of human and mouse. We demonstrate its use in identifying ARTN as a strong candidate gene within the 1p34.1-p32 mapped locus for a hereditary form of ptosis.

Recommended Citation

Chen C, Mungall C, Gkoutos G, Doelken S, Köhler S, Ruef B, Smith C, Westerfield M, Robinson P, Lewis S, Schofield P, Smedley D. MouseFinder: Candidate disease genes from mouse phenotype data. Hum Mutat 2012 May; 33(5):858-66.