CoverM: read alignment statistics for metagenomics

Samuel T.N. Aroney; Rhys J.P. Newell; Jakob N. Nissen; Antonio Pedro Camargo; Gene W. Tyson; Ben J. Woodcroft

doi:10.1093/bioinformatics/btaf147

CoverM: read alignment statistics for metagenomics

Samuel T.N. Aroney, Rhys J.P. Newell, Jakob N. Nissen, Antonio Pedro Camargo, Gene W. Tyson, Ben J. Woodcroft^*

^*Corresponding author for this work

Rasmussen Group

Research output: Contribution to journal › Journal article › Research › peer-review

1 Citation (Scopus)

Abstract

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.

Original language	English
Article number	btaf147
Journal	Bioinformatics
Volume	41
Issue number	4
Number of pages	4
ISSN	1367-4803
DOIs	https://doi.org/10.1093/bioinformatics/btaf147
Publication status	Published - 2025

Bibliographical note

Publisher Copyright:
© The Author(s) 2025.

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10.1093/bioinformatics/btaf147Licence: CC BY

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Cite this

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title = "CoverM: read alignment statistics for metagenomics",

abstract = "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.",

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T2 - read alignment statistics for metagenomics

AU - Aroney, Samuel T.N.

AU - Newell, Rhys J.P.

AU - Nissen, Jakob N.

AU - Camargo, Antonio Pedro

AU - Tyson, Gene W.

AU - Woodcroft, Ben J.

PY - 2025

Y1 - 2025

N2 - 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.

AB - 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.

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