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

Tune H. Pers (Lead / Corresponding author), Juha M. Karjalainen, Yingleong Chan, Harm-Jan Westra, Andrew R. Wood, Jian Yang, Julian C. Lui, Sailaja Vedantam, Stefan Gustafsson, Tonu Esko, Tim Frayling, Elizabeth K. Speliotes, Genetic Investigation of ANthropometric Traits (GIANT) Consortium, Michael Boehnke, Soumya Raychaudhuri, Rudolf S. N. Fehrmann, Joel N. Hirschhorn (Lead / Corresponding author), Lude Franke (Lead / Corresponding author)

    Research output: Contribution to journalArticlepeer-review

    524 Citations (Scopus)


    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.

    Original languageEnglish
    Article number5890
    Pages (from-to)1-9
    Number of pages9
    JournalNature Communications
    Publication statusPublished - 19 Jan 2015


    Dive into the research topics of 'Biological interpretation of genome-wide association studies using predicted gene functions'. Together they form a unique fingerprint.

    Cite this