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

2.50
Hdl Handle:
http://hdl.handle.net/11287/618116
Title:
Biological interpretation of genome-wide association studies using predicted gene functions.
Authors:
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.
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:
Nature
Journal:
Nature communications
Issue Date:
Jan-2015
URI:
http://hdl.handle.net/11287/618116
DOI:
10.1038/ncomms6890
PubMed ID:
25597830
Additional Links:
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.
Type:
Journal Article; Research Support, N.I.H., Extramural; Research Support, N.I.H., Intramural; Research Support, Non-U.S. Gov't
Language:
en
ISSN:
2041-1723
Appears in Collections:
2015 RD&E publications; Diabetes/Endocrine Services; Honorary contracts publications

Full metadata record

DC FieldValue Language
dc.contributor.authorPers, T. H.en
dc.contributor.authorKarjalainen, J.M.en
dc.contributor.authorChan, Y.en
dc.contributor.authorWestra, H-Jen
dc.contributor.authorWood, A. R.en
dc.contributor.authorYang, Jen
dc.contributor.authorLui, J. C.en
dc.contributor.authorVedantam, S.en
dc.contributor.authorGustafsson, S.en
dc.contributor.authorEsko, T.en
dc.contributor.authorFrayling, Timothy M.en
dc.contributor.authorSpeliotes, E. K.en
dc.contributor.authorBoehnke, M.en
dc.contributor.authorRaychaudhuri, S.en
dc.contributor.authorFehrmann, R. S. N.en
dc.contributor.authorHirschhorn, J. N.en
dc.contributor.authorFranke, L.en
dc.contributor.authorHattersley, Andrew T.en
dc.date.accessioned2016-08-09T12:15:12Z-
dc.date.available2016-08-09T12:15:12Z-
dc.date.issued2015-01-
dc.identifier.citationBiological interpretation of genome-wide association studies using predicted gene functions. 2015, 6:5890 Nat Communen
dc.identifier.issn2041-1723-
dc.identifier.pmid25597830-
dc.identifier.doi10.1038/ncomms6890-
dc.identifier.urihttp://hdl.handle.net/11287/618116-
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
dc.language.isoenen
dc.publisherNatureen
dc.relation.urlhttp://www.ncbi.nlm.nih.gov/pmc/articles/pmid/25597830/en
dc.rightsArchived with thanks to Nature communicationsen
dc.subjectWessex Classification Subject Headings::Oncology. Pathology.::Geneticsen
dc.titleBiological interpretation of genome-wide association studies using predicted gene functions.en
dc.typeJournal Articleen
dc.typeResearch Support, N.I.H., Extramuralen
dc.typeResearch Support, N.I.H., Intramuralen
dc.typeResearch Support, Non-U.S. Gov'ten
dc.identifier.journalNature communicationsen
dc.description.noteThis article is freely available via Open Access. Click on the 'Additional Link' to access the full-text.en
dc.type.versionPublisheden

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