Estimating allele frequencies, ancestry proportions and genotype likelihoods in the presence of mapping bias.

ABSTRACT: Population genomic analyses rely on an accurate and unbiased characterization of the genetic composition of the studied population. For short-read, high-throughput sequencing data, mapping sequencing reads to a linear reference genome can bias population genetic inference due to mismatches in reads carrying non-reference alleles. In this study, we investigate the impact of mapping bias on allele frequency estimates from pseudohaploid data and genotype likelihoods, 2 approaches commonly used in ultra-low to medium coverage sequencing. To mitigate mapping bias, we propose an empirical adjustment to genotype likelihoods. Using data from the 1000 Genomes Project, we find that our new method improves allele frequency estimation. To test a downstream application, we simulate ancient DNA data wit

SUBMITTER: Gunther T 

PROVIDER: S-EPMC12506655 | biostudies-literature | 2025 Oct

REPOSITORIES: biostudies-literature