HaploBlocks: Efficient Detection of Positive Selection in Large Population Genomic Datasets.

ABSTRACT: Genomic regions under positive selection harbor variation linked for example to adaptation. Most tools for detecting positively selected variants have computational resource requirements rendering them impractical on population genomic datasets with hundreds of thousands of individuals or more. We have developed and implemented an efficient haplotype-based approach able to scan large datasets and accurately detect positive selection. We achieve this by combining a pattern matching approach based on the positional Burrows-Wheeler transform with model-based inference which only requires the evaluation of closed-form expressions. We evaluate our approach with simulations, and find it to be both sensitive and specific. The computational resource requirements quantified using UK Biobank data in

SUBMITTER: Kirsch-Gerweck B 

PROVIDER: S-EPMC9985328 | biostudies-literature | 2023 Mar

REPOSITORIES: biostudies-literature