Fast and Memory-Efficient Dynamic Programming Approach for Large-Scale EHH-Based Selection Scans.

ABSTRACT: Haplotype-based statistics are widely used for finding genomic regions under positive selection. At the heart of many such statistics is the computation of extended haplotype homozygosity (EHH), which captures the decay of homozygosity away from a focal site. This computation, repeated for potentially millions of sites, is computationally demanding, as it involves tracking counts of unique haplotypes iteratively over long genomic distances and across many individuals. Because of these computational challenges, existing tools do not scale well when applied to large-scale population datasets, such as the 1,000 Genomes Project, or the UK Biobank with 500,000 individuals. Optimizing computation becomes crucial when data sets grow large, especially when handling large sample sizes or generating

SUBMITTER: Rahman A 

PROVIDER: S-EPMC12659807 | biostudies-literature | 2025 Oct

REPOSITORIES: biostudies-literature