This is the program for the 2010 Joint Statistical Meetings in Vancouver, British Columbia.

Abstract Details

Activity Number: 28
Type: Contributed
Date/Time: Sunday, August 1, 2010 : 2:00 PM to 3:50 PM
Sponsor: Section on Statistics in Epidemiology
Abstract - #309002
Title: Multiple Testing Correction Method in Genetic Association Studies with Related Individuals
Author(s): Zuoheng Wang*+
Companies: Yale University
Address: 60 College St, New Haven, CT, 06510,
Keywords: multiple testing ; association studies

With the rapid advances in high-throughput genotyping technology, genome-wide association studies have become an important approach to searching for genetic basis of human complex disease. Test of association may be based on individual SNPs or haplotypes of multiple SNPs. Multiple hypothesis testing is a common problem encountered in genome-wide association studies. Failure to account for the effects of multiple comparison may result in false positive results. We propose a new approach to correct for multiple hypothesis testing based on the multivariate normal distribution. This method accounts for two sources of correlations of test statistics: (1) linkage disequilibrium among genetic markers (2) dependence among genotypes across related individuals. We validate the new method in simulation studies and apply it to an association study with obesity.

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