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An integrated genome-wide association analysis on rheumatoid arthritis data
Jun Zhang1, Xiaofeng Zhu, Richard S Cooper
1Department of Statistics, University of Chicago, 5734 South University Avenue, Chicago, Illinois 60637, USA. junzhang@galton.uchicago.edu
Abstract:
We propose a nonparametric association analysis combining both family and unrelated case-control genotype data. Under the assumption of Hardy-Weinberg equilibrium, we formed an affected group to compare with a group of unaffecteds.Comparison with traditional case-control chi-square test and transmission-disequilibrium test shows that this new approach has noticeably improved power. All analysis was based on the simulated rheumatoid arthritis data provided by Genetic Analysis Workshop 15. In the situation of population stratification, we also suggest an approach to update the genotype data using principal components. However, the Genetic Analysis Workshop 15 simulation data does not simulate population stratification. All analysis was done without knowledge of the answers.
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