Improved Statistical Methods for Allele Frequency Estimation in Sequencing Data

• Activity Number: 183
• Type: Contributed
• Date/Time: Monday, July 30, 2012 : 10:30 AM to 12:20 PM
• Sponsor: Section on Statistics in Epidemiology
• Author(s): Zuoheng Wang*+ and Xiangtao Liu and Bao-Zhu Yang
• Companies: Yale University and Yale University and Yale University
• Keywords: sequencing ; likelihood

Abstract

Many types of genetic analyses depend on estimates of allele frequencies, and they may be sensitive to allele frequency misspecification. Intrinsic sequencing bias and error associated with high-throughput sequencing technologies can result in incorrect base calling, thus making the estimation of allele frequency a challenge task. Naïve counting the number of times a particular type of allele had appeared in the sample based on called genotypes is not efficient for sequencing data. To improve the allele frequency estimation, we propose a likelihood-based method that directly models the aligned reads taking the read base quality scores into account. We also propose an extension to the dependence case using a weighted likelihood approach and apply it to an exomic sequencing data set collected on a sample of families with panic disorder.