Bioinformatics · 2025 · 383 citations · 24 references
Life SciencesBioinformaticsMicrobiologyGenomicsMetagenomicsMicrobial GenomicsGenome Recovery From MetagenomesMetagenome BinningMetagenomic AnalysisMicrobial Community ProfilingShotgun Metagenomic SequencingShotgun MetagenomicsCommunity CompositionComputational EfficiencyComputational Efficiency AnalysisCoverageMicrobial Community CompositionRead AlignmentRead Coverage AnalysisReference-based Metagenomics
SUMMARY: Genome-centric analysis of metagenomic samples is a powerful method for understanding the function of microbial communities. Calculating read coverage is a central part of analysis, enabling differential coverage binning for recovery of genomes and estimation of microbial community composition. Coverage is determined by processing read alignments to reference sequences of either contigs or genomes. Per-reference coverage is typically calculated in an ad-hoc manner, with each software package providing its own implementation and specific definition of coverage. Here we present a unified software package CoverM which calculates several coverage statistics for contigs and genomes in an ergonomic and flexible manner. It uses "Mosdepth arrays" for computational efficiency and avoids unnecessary I/O overhead by calculating coverage statistics from streamed read alignment results. AVAILABILITY AND IMPLEMENTATION: CoverM is free software available at https://github.com/wwood/coverm. CoverM is implemented in Rust, with Python (https://github.com/apcamargo/pycoverm) and Julia (https://github.com/JuliaBinaryWrappers/CoverM_jll.jl) interfaces.
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