Abstract Details
Activity Number:
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550
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Type:
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Contributed
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Date/Time:
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Wednesday, August 7, 2013 : 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 - #310433 |
Title:
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Genetic Association Test with Multiple Longitudinal Traits
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Author(s):
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Weiqiang Wang*+ and Zeny Feng and Zuoheng Wang
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Companies:
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University of Guelph and University of Guelph and Yale University
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Keywords:
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Abstract:
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In the genetic association study, researchers are interested in testing the association between genetic variants such as single nucleotide polymorphisms (SNPs) with longitudinal traits. Performing genetic association testing on longitudinal traits is challenge and has its own interest in both biology and statistics. The problem becomes more complicated when more than one longitudinal trait involved in the study. Particularly, when we are interested in a common genetic factor that is associated with multiple longitudinal traits simultaneously. Mixed effects model has been widely used in longitudinal data analysis but more or less focusing on the estimation of the fixed effects. In this paper, in the mixed effects model, we pay our attention to the random effect estimate that accounts the total genetic contribution of an individual to the traits of interest. When there are multiple longitudinal traits, a simultaneous genetic association test on multiple random effects was performed. Simulation study is conducted to valid the method and evaluate the performance of the method. We also apply our method to analyze the GAW 16 Framingham heart study data.
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Authors who are presenting talks have a * after their name.
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