MetaStrainer : Accurate reconstruction of bacterial strain genotypes from short-read metagenomic samples

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ID: 314885
2026
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Abstract
MOTIVATION: Metagenomics provides broad insights from microbial communities, but more biological relevant phenotypes are attributed to subtle changes at the strain-level rather than species. Despite development of several tools using different algorithms, resolving individual strains from short-read pair-end sequencing data remains challenging. RESULTS: Here we present MetaStrainer, a tool capable of reconstructing strain genotypes from metagenomic data. Compared with existing approaches, MetaStrainer substantially increases genotype accuracy, correctly identifies the number of strains, and accurately estimates their relative abundances. Accuracy of reconstructed genotypes is robust to choice of mapping reference. AVAILABILITY: MetaStrainer is implemented in Python 3. Source code and instructions are available on GitHub at www.github.com/lbobay/MetaStrainer and on Zenodo: 10.5281/zenodo.17872331. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.
Reference Key
openalex_W7162318267 Use this key to autocite in the manuscript while using SciMatic Manuscript Manager or Thesis Manager
Authors Hazem Sharaf, Louis‐Marie Bobay
Journal BMC Bioinformatics
Year 2026
DOI
10.1093/bioinformatics/btag340
URL
https://doi.org/10.1093/bioinformatics/btag340
Keywords Keywords not found

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