qMSAT: A Powerful Test for Multiple Rare Variants Association Studies That Incorporates Sequencing Qualities

• Activity Number: 248
• Type: Contributed
• Date/Time: Monday, July 30, 2012 : 2:00 PM to 3:50 PM
• Sponsor: ENAR
• Author(s): Z. John Daye*+ and Hongzhe Li and Zhi Wei
• Companies: University of Pennsylvania and University of Pennsylvania and New Jersey Institute of Technology
• Keywords: association test ; complex traits ; genotype error ; missing data ; rare variants ; sequencing data

Abstract

Next-generation sequencing data will soon become routinely available for association studies between complex traits and rare variants. Sequencing data, however, are characterized by the presence of sequencing errors at each individual genotype. This makes it especially challenging to perform association studies of rare variants, which, due to their low minor allele frequencies, can be easily perturbed by genotype errors. In this talk, we develop the quality-weighted multivariate score association test (qMSAT), a new procedure that allows powerful association tests between complex traits and multiple rare variants under the presence of sequencing errors. Simulation results based on quality scores from real data show that the qMSAT often dominates over current methods, that do not utilize quality information. In particular, the qMSAT can dramatically increase power over existing methods under moderate sample sizes and relatively low coverage. Due to the high cost of sequencing data, the qMSAT is especially valuable for large-scale studies involving rare variants, as it can potentially increase power without additional experimental cost.