Biological interpretation of genome-wide association studies using predicted gene functions.
Author
Pers, T. H.
Karjalainen, J.M.
Chan, Y.
Westra, H-J
Wood, A. R.
Yang, J
Lui, J. C.
Vedantam, S.
Gustafsson, S.
Esko, T.
Frayling, Timothy M.
Speliotes, E. K.
Boehnke, M.
Raychaudhuri, S.
Fehrmann, R. S. N.
Hirschhorn, J. N.
Franke, L.
Hattersley, Andrew T.
Date
2015-01Journal
Nature communicationsType
Journal ArticleResearch Support, N.I.H., Extramural
Research Support, N.I.H., Intramural
Research Support, Non-U.S. Gov't
Publisher
NatureDOI
10.1038/ncomms6890Rights
Archived with thanks to Nature communicationsMetadata
Show full item recordAbstract
The main challenge for gaining biological insights from genetic associations is identifying which genes and pathways explain the associations. Here we present DEPICT, an integrative tool that employs predicted gene functions to systematically prioritize the most likely causal genes at associated loci, highlight enriched pathways and identify tissues/cell types where genes from associated loci are highly expressed. DEPICT is not limited to genes with established functions and prioritizes relevant gene sets for many phenotypes.