Precise and scalable metagenomic profiling with sample-tailored minimizer libraries.

ABSTRACT: Reference-based metagenomic profiling requires large genome libraries to maximize detection and minimize false positives. However, as libraries grow, classification accuracy suffers, particularly in k-mer-based tools, as the growing overlap in genomic regions among organisms results in more high-level taxonomic assignments, blunting precision. To address this, we propose sample-tailored minimizer libraries, which improve on the minimizer-lowest common ancestor classification algorithm from the widely used Kraken 2. In this method, an initial filtering step using a large library removes non-resemblance genomes, followed by a refined classification step using a dynamically built smaller minimizer library. This 2-step classification method shows significant performance improvements compared t

SUBMITTER: Nystrom-Persson J 

PROVIDER: S-EPMC12147018 | biostudies-literature | 2025 Jun

REPOSITORIES: biostudies-literature