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Activity Number:
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136
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Type:
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Contributed
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Date/Time:
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Monday, August 4, 2008 : 10:30 AM to 12:20 PM
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Sponsor:
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Section on Statistics in Epidemiology
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| Abstract - #301042 |
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Title:
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Information Geometry, Gene-Gene, Gene-Environment Interaction, and Pathway Association
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Author(s):
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Momiao Xiong*+ and Li Luo and Gang Peng
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Companies:
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The University of Texas School of Public Health and The University of Texas School of Public Health and Fudan University
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Address:
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1200 Herman Pressler, Houston, TX, 77030,
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Keywords:
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Gene-gene interaction ; Gene-environment interaction ; Information theory ; Genetic networks ; pathway ; genome-wide association studies
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Abstract:
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Despite current enthusiasm for investigation of gene-gene, and gene-environment interactions, and pathway association, the essential issue of how to detect gene-environment interaction and identify pathway association remains unresolved. In this report, we use concept in information geometry to measure and develop novel tests for gene-environment interaction and pathway association. We validate the null distribution and calculate type 1 error rates of developed statistics using extensive simulation studies. We found that the new test statistics were much more powerful than other traditional statistics under several disease models. Finally, the developed statistics were applied to a number of real examples. The results showed that P-values of the information geometry-based statistics were much smaller than that obtained by other approaches.
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