Rare Variant Test Based on Next-Generation Sequencing Data with Arbitrary Length

• Activity Number: 42
• Type: Contributed
• Date/Time: Sunday, July 31, 2016 : 2:00 PM to 3:50 PM
• Sponsor: IMS
• Author(s): Zheng Xu* and Yun Li
• Companies: and The University of North Carolina at Chapel Hill
• Keywords: Association study ; rare-variant test ; next generation sequencing data ; genotype calling ; generalized linear model ; score test

Abstract

With the rapid advancement of sequencing techniques and decreasing cost in the sequencing, next generation sequencing data are becoming more and more feasible and popular to use. We propose a method to conduct rare variant association test based on next-generation sequencing data, without the need of genotype calling. The new test could adjust for arbitrary sequencing depth and avoid errors induced by genotyping. Simulation studies have been performed to illustrate our method.