MouseFinder: Candidate disease genes from mouse phenotype data

Research output: Contribution to journalArticlepeer-review

Authors

  • C. K. Chen
  • C. J. Mungall
  • S. C. Doelken
  • S. Kohler
  • B. J. Ruef
  • C. Smith
  • M. Westerfield
  • P. N. Robinson
  • S. E. Lewis
  • P. N. Schofield
  • D. Smedley

Colleges, School and Institutes

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.

Details

Original languageEnglish
Pages (from-to)858-866
Number of pages9
JournalHuman Mutation
Volume33
Issue number5
Early online date16 Mar 2012
Publication statusPublished - 1 May 2012