Powerful cocktail methods for detecting genome-wide gene-environment interaction.

ABSTRACT: Identifying gene and environment interaction (G × E) can provide insights into biological networks of complex diseases, identify novel genes that act synergistically with environmental factors, and inform risk prediction. However, despite the fact that hundreds of novel disease-associated loci have been identified from genome-wide association studies (GWAS), few G × Es have been discovered. One reason is that most studies are underpowered for detecting these interactions. Several new methods have been proposed to improve power for G × E analysis, but performance varies with scenario. In this article, we present a module-based approach to integrating various methods that exploits each method's most appealing aspects. There are three modules in our approach: (1) a screening module for priori

SUBMITTER: Hsu L 

PROVIDER: S-EPMC3654520 | biostudies-literature | 2012 Apr

REPOSITORIES: biostudies-literature