Haplotype-Based Association Studies Under Complex Sampling

• Activity Number: 186
• Type: Invited
• Date/Time: Monday, August 1, 2011 : 10:30 AM to 12:20 PM
• Sponsor: Section on Survey Research Methods
• Author(s): Daoying Lin*+ and Yan Li
• Companies: The University of Texas at Arlington and The University of Texas at Arlington
• Keywords: Complex sampling ; Weighted EM algorithm ; Haplotype ; Genetic association studies ; Weighted logistic regression ; Case control studies

Abstract

A widely used design strategy in the study of haplotype-based genetic association is case-control studies. Numerous methods have been proposed to infer haplotypes and investigate the role of genetic variants in common diseases under simple random sampling (SRS). It is becoming common that complex sampling, which usually involves complexities like differential weighting and clustering, is utilized in genetic association studies. In this article, we have formalized a two-step prospective approach that applies to case control studies with complex sampling. At first step, we develop a weighted EM (WEM) algorithm to infer haplotype frequencies from unphased genotype data. At second step, we study the association of haplotypes and diseases by weighted logistic regression. Monte Carlo simulation studies are used to evaluate the performance of proposed method. It has been found that methods developed under SRS give biased estimates and overstate the significance level. In contrast, our method performs well, produce consistent estimates and maintain its significance level.