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Abstract Details
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Activity Number:
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233
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Type:
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Contributed
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Date/Time:
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Monday, August 1, 2011 : 2:00 PM to 3:50 PM
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Sponsor:
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Biometrics Section
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| Abstract - #301969 |
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Title:
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A New Robust Method for Testing Single SNP Association in GWA Studies
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Author(s):
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Zhongxue Chen*+ and Tony Ng
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Companies:
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The University of Texas Health Science Center at Houston and Southern Methodist University
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Address:
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, , 77030, USA
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Keywords:
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SNP ;
GWA ;
trend test ;
Chi-square test
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Abstract:
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In genetic association studies, due to the varying underlying genetic models, there exists no single statistical test that is most powerful under all situations. Current studies show that if the underlying genetic models are known, trend-based tests, which outperform the classical Pearson's chi-square test, can be constructed. However, when the underlying genetic models are unknown, chi-square test is usually more robust than trend-based tests. In this paper, we propose a new statistical testing procedure which is based directly on the disease relative risks, which are order-restricted. Through a Monte Carlo simulation study, we show that this new method is generally more powerful than the chi-square test, and more robust than trend test. The proposed methodologies are illustrated by some real datasets.
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