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dc.contributor.authorPers TH
dc.contributor.authorKarjalainen JM
dc.contributor.authorChan Y
dc.contributor.authorWestra HJ
dc.contributor.authorWood AR
dc.contributor.authorYang J
dc.contributor.authorLui JC
dc.contributor.authorVedantam S
dc.contributor.authorGustafsson S
dc.contributor.authorEsko T
dc.contributor.authorFrayling T
dc.contributor.authorSpeliotes EK
dc.contributor.authorGenetic Investigation of ANthropometric Traits (GIANT) Consortium
dc.contributor.authorBoehnke M
dc.contributor.authorRaychaudhuri S
dc.contributor.authorFehrmann RS
dc.contributor.authorHirschhorn JN
dc.contributor.authorFranke L
dc.date.accessioned2018-10-08T14:35:45Z
dc.date.available2018-10-08T14:35:45Z
dc.date.issued2015
dc.identifier.issn2041-1723
dc.identifier.urihttp://dx.doi.org/10.1038/ncomms6890
dc.identifier.urihttp://hdl.handle.net/10863/6441
dc.description.abstractThe 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.en_US
dc.language.isoenen_US
dc.rights
dc.titleBiological interpretation of genome-wide association studies using predicted gene functionsen_US
dc.typeArticleen_US
dc.date.updated2018-10-08T14:33:03Z
dc.language.isiEN-GB
dc.journal.titleNature Communications
dc.description.fulltextopenen_US


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