CoverM: read alignment statistics for metagenomics.

IF 5.4 Bioinformatics (Oxford, England) Pub Date : 2025-03-29 DOI:10.1093/bioinformatics/btaf147

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

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Abstract

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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CoverM：读取宏基因组的比对统计信息。

摘要：以基因组为中心的宏基因组样本分析是了解微生物群落功能的有力方法。计算读覆盖是分析的核心部分，它使基因组恢复和微生物群落组成估算的差异覆盖结合成为可能。覆盖范围是通过处理读取比对参考序列或组群或基因组来确定的。每个引用的覆盖率通常以一种特别的方式计算，每个软件包提供它自己的实现和特定的覆盖率定义。在这里，我们提出了一个统一的软件包CoverM，它以人体工程学和灵活的方式计算基因组和基因组的几种覆盖统计。它使用“Mosdepth数组”来提高计算效率，并通过计算流读对齐结果的覆盖统计数据来避免不必要的I/O开销。可用性和实现：CoverM是免费软件，可在https://github.com/wwood/coverm上获得。CoverM是用Rust实现的，使用Python （https://github.com/apcamargo/pycoverm）和Julia （https://github.com/JuliaBinaryWrappers/CoverM_jll.jl）接口。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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Bioinformatics (Oxford, England)

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