Meta-analysis of gene-environment interaction exploiting gene-environment independence across multiple case-control studies.

ABSTRACT: Multiple papers have studied the use of gene-environment (G-E) independence to enhance power for testing gene-environment interaction in case-control studies. However, studies that evaluate the role of G-E independence in a meta-analysis framework are limited. In this paper, we extend the single-study empirical Bayes type shrinkage estimators proposed by Mukherjee and Chatterjee (2008) to a meta-analysis setting that adjusts for uncertainty regarding the assumption of G-E independence across studies. We use the retrospective likelihood framework to derive an adaptive combination of estimators obtained under the constrained model (assuming G-E independence) and unconstrained model (without assumptions of G-E independence) with weights determined by measures of G-E association derived from m

SUBMITTER: Estes JP 

PROVIDER: S-EPMC5624850 | biostudies-literature | 2017 Oct

REPOSITORIES: biostudies-literature