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Activity Number: 110
Type: Topic Contributed
Date/Time: Monday, July 30, 2012 : 8:30 AM to 10:20 AM
Sponsor: Biometrics Section
Abstract - #305075
Title: Simultaneously Testing for Marginal Genetic Association and Gene-Environment Interaction
Author(s): Benjamin Logsdon*+ and James Dai and Ying Huang and Li Hsu and Alexander P. Reiner and Ross Prentice and Charles L Kooperberg
Companies: Fred Hutchinson Cancer Research Center and Fred Hutchinson Cancer Research Center and Fred Hutchinson Cancer Research Center and Fred Hutchinson Cancer Research Center and Fred Hutchinson Cancer Research Center and Fred Hutchinson Cancer Research Center and Fred Hutchinson Cancer Research Center
Address: 1100 Fairview Ave N, Seattle, WA, 98109, United States
Keywords: case-only ; empirical Bayes ; gene-environment independence ; 2-df test ; two-stage procedures
Abstract:

We propose to simultaneously test for marginal genetic association and gene-environment interaction to discover SNPs that may be involved in gene-environment or gene-treatment interaction. The asymptotic independence of the estimated marginal association and various interaction estimators leads to a simple and flexible way of combining two independent tests, whether gene-environment independence is exploited in estimating gene-environment interaction. The proposed test differs from the 2-df test proposed in Kraft et al. (2007) in two aspects: First, in one component it tests for marginal genetic association, that is often the primary objective in inference, rather than the genetic main effect in a model with gene-environment interaction. Second, the other testing component can easily exploit putative gene-environment independence using either the case-only estimator or the empirical Bayes estimator, depending on whether the goal is gene-treatment interaction in a randomized trial or gene-environment interaction in an observational study. The usage of the proposed joint test is illustrated by simulations and a genetic study in the Women's Health Initiative


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