Open Access. Powered by Scholars. Published by Universities.®
Cocktail method; empirical Bayes; gene-environment interaction; genome-wide study; modular approach; screening; weighted hypothesis testing
Articles 1 - 1 of 1
Full-Text Articles in Medicine and Health Sciences
Powerful Cocktail Methods For Detecting Genome-Wide Gene-Environment Interaction, Li Hsu, Shuo Jiao, James Y. Dai, Carolyn M. Hutter, Ulrike Peters, Charles Kooperberg
Powerful Cocktail Methods For Detecting Genome-Wide Gene-Environment Interaction, Li Hsu, Shuo Jiao, James Y. Dai, Carolyn M. Hutter, Ulrike Peters, Charles Kooperberg
Shuo Jiao
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 thatmost 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 …