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