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May 10, 2026Bioinformatics0 citationsOpen Access

StrainMake: reproducible hybrid metagenomics with MAG recovery and strain-level resolution

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BHBaptiste HennecartEBEugeni BeldaRLRaynald de Lahondès

Key Points

  • This research aims to develop a reproducible metagenomic workflow capable of strain-level resolution and hybrid assembly support.
  • Developed StrainMake as a Snakemake-based workflow for metagenomic analysis.
  • Integrated tools for quality control, assembly, binning, and annotation across sequencing data types.
  • Applied the workflow to the CAMI II strain-madness dataset for validation.
  • StrainMake produced high-quality assemblies with metagenome-assembled genomes (MAGs).
  • Hybrid assemblies showed improved contiguity compared to short-read assemblies.
  • Short-read assemblies were faster, highlighting the workflow's flexibility and performance.

Abstract

SUMMARY: Metagenomic workflows involve complex multi-step analyses, from quality control and assembly to binning, annotation, and strain-level profiling. Few existing metagenomic pipelines achieve the combination of flexibility, reproducibility, and hybrid assembly support within a unified workflow. We present StrainMake, a Snakemake-based workflow for de novo metagenomic analysis from short, long, or hybrid sequencing data. StrainMake integrates widely used tools across all major steps-quality control, assembly, binning, dereplication, taxonomic and functional annotation-while also providing non-redundant gene catalogues, community-scale metabolic models, and strain-level microdiversity metrics. The modular design enables the use of alternative tools, scalable execution on HPC systems, and full reproducibility through Snakemake and Conda. RESULTS: Applied to the CAMI II strain-madness dataset, StrainMake produced high-quality assemblies and metagenome-assembled genomes (MAGs), while enabling strain-resolved comparisons across samples. Hybrid assemblies improved contiguity, whereas short-read assemblies offered faster runtimes, illustrating the workflow's benchmarking capacity. AVAILABILITY AND IMPLEMENTATION: StrainMake is open source and available at https://github.com/UMMISCO/strainmake, together with comprehensive documentation. Generated data are deposited in Zenodo (doi : 10.5281/zenodo.16950162).

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Cite This Study

Hennecart et al. (2026) studied this question.

synapsesocial.com/papers/6a0021fec8f74e3340f9cfa0https://doi.org/10.1093/bioinformatics/btag212
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