Estimation of allele frequency and association mapping using next-generation sequencing data

Background: Estimation of allele frequency is of fundamental importance in population genetic analyses and in association mapping. In most studies using next-generation sequencing, a cost effective approach is to use medium or low-coverage data (e.g., < 15X). However, SNP calling and allele frequency estimation in such studies is associated with substantial statistical uncertainty because of varying coverage and high error rates. Results: We evaluate a new maximum likelihood method for estimating allele frequencies in low and medium coverage next-generation sequencing data. The method is based on integrating over uncertainty in the data for each individual rather than first calling genotypes. This method can be applied to directly test for associations in case/control studies. We use simulations to compare the likelihood method to methods based on genotype calling, and show that the likelihood method outperforms the genotype calling methods in terms of: (1) accuracy of allele frequ...

• Type: Journal
• Year: 2011
• Where: BMCBI
• Authors: Su Yeon Kim, Kirk E. Lohmueller, Anders Albrechtsen, Yingrui Li, Thorfinn Korneliussen, Geng Tian, Niels Grarup, Tao Jiang, Gitte Andersen, Daniel Witte, Torben Jorgensen, Torben Hansen, Oluf Pedersen, Jun Wang, Rasmus Nielsen
• Keywords: Biometrics, BMCBI 2011, Case Control Studies, Frequency Estimation, Maximum Likelihood Method