A New Method for Detecting Associations with Rare Variants for Complex Disease

• Activity Number: 186
• Type: Invited
• Date/Time: Monday, August 1, 2011 : 10:30 AM to 12:20 PM
• Sponsor: Section on Statistics in Epidemiology
• Author(s): Huann-Sheng Chen and Shunpu Zhang*+
• Companies: National Cancer Institute and University of Nebraska at Lincoln
• Keywords: genetics ; complex disease ; association ; rare variant ; next generation sequencing ; epidemiology

Abstract

Recent studies show that rare variants play an important role in complex disease etiology. New technologies now allow generating exome sequencing data to detect association between common disease and rare variant mutations. Methods for association studies using common SNPs have low power when being used to to identify rare disease-causing variants due to their low frequency. Most current strategies proposed for detecting rare variants either group or collapse the variants within a region, such as genes or pathways. Although such methods have reasonable power in detecting causal variants, we find that they often have biased control of the Type I error rate. In this paper, we propose a new method to analyze rare variant association data for complex traits.The control of the Type I error rate and the power of the proposed method will be compared to the existing methods for a variety of underlying genetic models.