Benchmarking metagenomic binning tools on real datasets across sequencing platforms and binning modes.

ABSTRACT: Metagenomic binning is a culture-free approach that facilitates the recovery of metagenome-assembled genomes by grouping genomic fragments. However, there remains a lack of a comprehensive benchmark to evaluate the performance of metagenomic binning tools across various combinations of data types and binning modes. In this study, we benchmark 13 metagenomic binning tools using short-read, long-read, and hybrid data under co-assembly, single-sample, and multi-sample binning, respectively. The benchmark results demonstrate that multi-sample binning exhibits optimal performance across short-read, long-read, and hybrid data. Moreover, multi-sample binning outperforms other binning modes in identifying potential antibiotic resistance gene hosts and near-complete strains containing potential bio

SUBMITTER: Han H 

PROVIDER: S-EPMC11933696 | biostudies-literature | 2025 Mar

REPOSITORIES: biostudies-literature