Related resources
Full-text held externally
- DOI: 10.1038/ncomms6890
- PMID: 25597830
- UKPMCID: 25597830
Search for item elsewhere
University researcher(s)
Academic department(s)
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; Franke, Lude
Nature communications. 2015;6:5890.
Access to files
Full-text and supplementary files are not available from Manchester eScholar. Full-text is available externally using the following links:
Full-text held externally
- DOI: 10.1038/ncomms6890
- PMID: 25597830
- UKPMCID: 25597830
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.