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Abstract Details

Activity Number: 110
Type: Topic Contributed
Date/Time: Monday, July 30, 2012 : 8:30 AM to 10:20 AM
Sponsor: Biometrics Section
Abstract - #304562
Title: Powerful Cocktail Methods for Detecting Genome-Wide GxE Interaction
Author(s): Li Hsu*+
Companies: Fred Hutchinson Cancer Research Center
Address: , , 98109,
Keywords: GxE interaction ; screening ; Empirical Bayes ; weighted hypothesis testing ; GWAS

It is well recognized the importance of identifying GxE interactions. However, despite the fact that hundreds of novel disease-associated loci have been identified from genome-wide association studies (GWAS), few GxEs 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 GxE analysis, but performance varies with scenario. We propose a module-based approach to integrating various methods that exploits each method's most appealing aspects. This includes screening for prioritizing SNPs, multiple comparison and GxE testing modules. We combine all three of these modules and develop two novel ``cocktail" methods. Simulations show the power tracks well with the best existing methods, despite that the best methods may be different under various scenarios/interaction models. Broadly speaking, the modular approach is conceptually straightforward and can be easily implemented. It also allows for an easy incorporation of new methods as they are developed. Our work provides a comprehensive and powerful tool for devising effective strategies for genome-wide search of GxE.

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