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

Pers, Tune H., Karjalainen, Juha M., Chan, Yingleong, Westra, Harm-Jan, Wood, Andrew R., Yang, Jian, Lui, Julian C., Vedantam, Sailaja, Gustafsson, Stefan, Esko, Tonu, Frayling, Tim, Speliotes, Elizabeth K., Boehnke, Michael, Raychaudhuri, Soumya, Fehrmann, Rudolf S. N., Hirschhorn, Joel N. and Franke, Lude (2015) Biological interpretation of genome-wide association studies using predicted gene functions. Nature Communications, 6 Art No.: 5890: 5890-5890. doi:10.1038/ncomms6890

Attached Files (Some files may be inaccessible until you login with your UQ eSpace credentials)
Name Description MIMEType Size Downloads
UQ352662_OA.pdf Open access application/pdf 632.92KB 0

Author Pers, Tune H.
Karjalainen, Juha M.
Chan, Yingleong
Westra, Harm-Jan
Wood, Andrew R.
Yang, Jian
Lui, Julian C.
Vedantam, Sailaja
Gustafsson, Stefan
Esko, Tonu
Frayling, Tim
Speliotes, Elizabeth K.
Boehnke, Michael
Raychaudhuri, Soumya
Fehrmann, Rudolf S. N.
Hirschhorn, Joel N.
Franke, Lude
Title Biological interpretation of genome-wide association studies using predicted gene functions
Journal name Nature Communications   Check publisher's open access policy
ISSN 2041-1723
Publication date 2015-01-01
Year available 2015
Sub-type Article (original research)
DOI 10.1038/ncomms6890
Open Access Status File (Publisher version)
Volume 6
Issue Art No.: 5890
Start page 5890
End page 5890
Total pages 9
Place of publication London, United Kingdom
Publisher Nature Publishing Group
Language eng
Subject 1600 Chemistry
1300 Biochemistry, Genetics and Molecular Biology
3100 Physics and Astronomy
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.
Formatted 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.
Keyword Biological sciences
Genetics
Q-Index Code C1
Q-Index Status Confirmed Code
Grant ID G1001799
CZB/4/672
R01 DK075787
U01 GM092691
MR/N01104X/1
098395
R01 AR063759
2R01DK075787
UH2 AR067677
MR/K006584/1
MR/K013351/1
P30 DK020572
R01 HL117078
P30 CA071789
Institutional Status UQ

Document type: Journal Article
Sub-type: Article (original research)
Collections: Queensland Brain Institute Publications
Official 2016 Collection
UQ Diamantina Institute Publications
 
Versions
Version Filter Type
Citation counts: TR Web of Science Citation Count  Cited 129 times in Thomson Reuters Web of Science Article | Citations
Scopus Citation Count Cited 131 times in Scopus Article | Citations
Google Scholar Search Google Scholar
Created: Sun, 01 Mar 2015, 10:16:28 EST by System User on behalf of Queensland Brain Institute