Randomized trial shows improved genotype accuracy in bacterial strains from metagenomic data, indicating better microbial profiling capabilities.
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.
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Sharaf et al. (2026) studied this question.
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