Genetic association analysis for common variants in the Genetic Analysis Workshop 18 data: a Dirichlet regression
Osvaldo Espin-Garcia1, Xiaowei Shen1, Xin Qiu2
1Department of Biostatistics, Princess Margaret Cancer Centre, 610 University Ave., Toronto, ON, M5G 2M9, Canada ; Department of Statistics and Actuarial Science, University of Waterloo, 200 University Avenue West, Waterloo, ON, N2L 3G1, Canada.
Abstract:
We propose a genetic association analysis using Dirichlet regression to analyze the Genetic Analysis Workshop 18 data. Clinical variables, arranged in a longitudinal data structure, are employed to fit a multistate transition model in which the transition probabilities are served as a response in the proposed analysis. Furthermore, a gene-based association analysis via penalized regression is implemented using the markers at a single-nucleotide polymorphism level that we previously identified via nonpenalized Dirichlet regression.
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