This is the program for the 2010 Joint Statistical Meetings in Vancouver, British Columbia.

Abstract Details

Activity Number: 295
Type: Contributed
Date/Time: Tuesday, August 3, 2010 : 8:30 AM to 10:20 AM
Sponsor: Biometrics Section
Abstract - #307059
Title: Exploiting Interaction Information in Detecting Loci That Influence Complex Diseases
Author(s): Kuang-Fu Cheng*+ and Jen-Yu Lee and Jin-Hua Chen
Companies: China Medical University and National Central University, Taiwan and China Medical University
Address: shei-ji rd, taichung, taiwan,
Keywords: association test ; environment ; gene ; interaction ; main-effect ; population stratification
Abstract:

In detecting disease susceptibility loci, the traditional genetic association studies focus on the detection of the main effects of a single locus or a set of single nucleotide polymorphisms. A recent research proposed a more efficient approach by testing for main effects and interactions simultaneously. However, the test statistic is valid only when all the modifying loci and the primary locus are independent. In addition, the test may be biased in the presence of population stratification. These disadvantages limit the use of the otherwise rather powerful test. In this paper, we propose a novel test allowing for independent or dependent modifying loci and show the loss of power is small in the independent case but the test is still valid in the dependent case. We also show how to correct for the bias in the presence of population stratification.


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