Efficient Two-Stage Association Analysis with Arbitrary Depth Sequencing-Based Studies

• Activity Number: 455
• Type: Topic Contributed
• Date/Time: Wednesday, August 1, 2012 : 8:30 AM to 10:20 AM
• Sponsor: Biometrics Section
• Author(s): Li Yun*+
• Companies: The University of North Carolina at Chapel Hill
• Keywords: sequencing ; genetic association ; linkage disequilibrium

Abstract

Massively parallel sequencing, having resulted in the successful identification of causal variants for several rare Mendelian disorders, hold the promise to explain some of the missing heritability from genomewide association studies of complex human traits. We have previously developed a unified statistical framework for SNP discovery and genotype calling from a combination of arbitrary depth sequencing and genotyping data, which leverages linkage disequilibrium (LD) with surrounding genetic markers to generate highly accurate calls. However, such LD-based methods tend to be computationally intensive when applied to studies where several thousand individuals are sequenced. We develop a two-stage method where we screen for regions potentially harboring trait-associated genetic variant(s) first and then apply LD-based method for these regions only. The method generates promising results from simulated and real datasets.