ReSkmer: modeling repeats allows k-mer-based alignment-free methods to calculate population genomic distances
Year: 2026
Type: article
Abstract: Understanding ecological change requires robust, inexpensive methods for monitoring populations. One approach is using low-coverage genome sequencing (genome skimming) to compute genetic diversity via assembly-free, alignment-free, k-mer-based methods to compute genomic distances from shotgun sequences using the intersection of k-mer sets. Skmer extended this approach to genome skims by modeling coverage and error. However, these methods ignore genome repetitiveness, hampering population genetic distance calculation. Here, we mathematically derive the expected intersection size between k-mers sampled from two repetitive genomes, accounting for repeats, coverage, and errors, leading to the method ReSkmer. Our experiments show highly accurate distances despite sampling highly repetitive genomes.
Source: Genome biology
Language: English
Subfield: Molecular Biology
Domain: Life Sciences
Open Access status: gold
Estimated APC paid: $5,490
Awards: Track 4: Advanced CI Coordination Ecosystem: Monitoring and Measurement Services, Track 1: ACCESS Resource Allocations Marketplace and Platform Services (RAMPS), ACO: An Open CI Ecosystem to Advance Scientific Discovery (OpenCI), Track 3: COre National Ecosystem for CyberinfrasTructure (CONECT), Track 2: Customized Multi-tier Assistance, Training, and Computational Help (MATCH) for End User ACCESS to CI, Computational methods for detecting patterns of complex genomic variation
OpenAlex ID: W7162197711