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    Biological interpretation of genome-wide association studies using predicted gene functions.

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    URI
    http://hdl.handle.net/11287/618116
    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
    2015-01
    Journal
    Nature communications
    Type
    Journal Article
    Research Support, N.I.H., Extramural
    Research Support, N.I.H., Intramural
    Research Support, Non-U.S. Gov't
    Publisher
    Nature
    DOI
    10.1038/ncomms6890
    Rights
    Archived with thanks to Nature communications
    Metadata
    Show full item record
    Abstract
    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.
    Citation
    Biological interpretation of genome-wide association studies using predicted gene functions. 2015, 6:5890 Nat Commun
    Publisher URL
    http://www.ncbi.nlm.nih.gov/pmc/articles/pmid/25597830/
    Note
    This article is freely available via Open Access. Click on the 'Additional Link' to access the full-text.
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    • 2015 RD&E publications
    • Diabetes/Endocrine Services
    • Honorary contracts publications

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