A novel random effect model for GWAS meta-analysis and its application to trans-ethnic meta-analysis.

ABSTRACT: Meta-analysis of trans-ethnic genome-wide association studies (GWAS) has proven to be a practical and profitable approach for identifying loci that contribute to the risk of complex diseases. However, the expected genetic effect heterogeneity cannot easily be accommodated through existing fixed-effects and random-effects methods. In response, we propose a novel random effect model for trans-ethnic meta-analysis with flexible modeling of the expected genetic effect heterogeneity across diverse populations. Specifically, we adopt a modified random effect model from the kernel regression framework, in which genetic effect coefficients are random variables whose correlation structure reflects the genetic distances across ancestry groups. In addition, we use the adaptive variance component test

SUBMITTER: Shi J 

PROVIDER: S-EPMC4996751 | biostudies-literature | 2016 Sep

REPOSITORIES: biostudies-literature