A Novel Genome Continuum Model for Sequence-Based Association Studies

• Activity Number: 623
• Type: Contributed
• Date/Time: Thursday, August 5, 2010 : 8:30 AM to 10:20 AM
• Sponsor: Biometrics Section
• Author(s): Li Luo* and Momiao Xiong+
• Companies: The University of Texas School of Public Health and The University of Texas School of Public Health
• Keywords: GWAS ; next-generation sequencing ; functional data analysis ; high dimensional data reduction ; stochastic calculus ; genetic epidemiology

Abstract

Next-generation sequencing technologies will detect millions of common and rare variants, which leads to a dense SNP map. The current paradigm of individual test is designed for common variants and difficult to be applied to rare variants. To meet great challenge raised by sequence-based GWAS, instead of modeling the genome as a few separated individual loci, we model the genome as a continuum and a genetic variant profile of each individual as a realization of the stochastic process in the genome. Instead of testing association of SNP individually, we developed a novel statistic for testing association of the whole genome region with the disease. Extensive type 1 error rate and power studies as well as its application to cardiovascular disease strongly demonstrated that the new statistic has much better performance than the current statistics and may shift the current paradigm of GWAS.