Abstract Details
Activity Number:
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210
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Type:
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Invited
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Date/Time:
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Monday, August 4, 2014 : 2:00 PM to 3:50 PM
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Sponsor:
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Section on Statistics in Epidemiology
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Abstract #310649
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View Presentation
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Title:
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A Unified Framework for Two-Stage Gene-Environment Interaction Tests with Adaptive Filtering
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Author(s):
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Lin Chen*+
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Companies:
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University of Chicago
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Keywords:
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two-stage ;
gene-environment interaction ;
adaptive filtering
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Abstract:
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Complex diseases arise as the consequences of genetic, environmental risk factors and their interactions. Despite the established role of gene-environment interactions (GxE) in disease etiology, there are only a limited number of GxE effects being identified via genome-wide searches, due to power issues. To detect GxE effects with genome-wide association or whole-genome sequencing data, we propose a gene-based test with two unified steps -- filtering and testing. We propose to first conduct a filtering test on each genetic variant in the genome, apply an adaptive filtering to each gene and perform a gene-based interaction test only with the retaining variants. By employing an asymptotically independent filtering to the interaction test, we can obtain the exact distribution of the overall test statistics, and approximate its power function. We calculate the optimal filtering threshold for each gene adaptively to maximize the power, with considerations of potential linkage disequilibrium. The proposed two-stage testing frame also has a natural Bayesian interpretation. We demonstrate with simulations and examples that our test outperforms existing methods in the literature.
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Authors who are presenting talks have a * after their name.
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