Meta-analysis of correlated traits via summary statistics from GWASs with an application in hypertension.

ABSTRACT: Genome-wide association studies (GWASs) have identified many genetic variants underlying complex traits. Many detected genetic loci harbor variants that associate with multiple-even distinct-traits. Most current analysis approaches focus on single traits, even though the final results from multiple traits are evaluated together. Such approaches miss the opportunity to systemically integrate the phenome-wide data available for genetic association analysis. In this study, we propose a general approach that can integrate association evidence from summary statistics of multiple traits, either correlated, independent, continuous, or binary traits, which might come from the same or different studies. We allow for trait heterogeneity effects. Population structure and cryptic relatedness can also

SUBMITTER: Zhu X 

PROVIDER: S-EPMC4289691 | biostudies-literature | 2015 Jan

REPOSITORIES: biostudies-literature