| name | coverm |
| description | Calculate coverage/relative abundance of genomes or contigs. Use this skill when working with coverm: installing, choosing parameters, running commands, interpreting outputs, or troubleshooting. Upstream: https://github.com/wwood/CoverM. For routing across tools, use tool-selection. For end-to-end pipelines, use metagenomics-workflow.
|
| license | MIT |
| category | analysis-tools |
| tags | ["abundance","MAG","coverage"] |
| upstream | https://github.com/wwood/CoverM |
CoverM
Upstream: wwood/CoverM
Citation
Aroney, S. T. N. et al. CoverM: read alignment statistics for metagenomics. Bioinformatics 41, btaf147 (2025). https://doi.org/10.1093/bioinformatics/btaf147
See also docs/references.md.
Analytical thinking
CoverM unifies per-contig (binning inputs) and per-genome (community
profiling) coverage using Mosdepth-style arrays. Relative abundance (default
genome mode) scales mean coverages by the fraction of reads that align —
incomplete references leave many reads unmapped; CoverM accounts for that in
its relative-abundance formula.
Important defaults / assumptions from the paper:
- Genome presence filter: by default ≥10% of genome length covered ≥1× before
assigning non-zero coverage (limits off-target hits in conserved regions).
- Relative abundance assumes roughly similar average genome sizes for mapped vs
missing community members, and roughly complete/uncontaminated references.
- Near-identical references distort recruitment — CoverM can dereplicate with
Galah using skani/FastANI/Dashing ANI before mapping.
- Aligners: strobealign / minimap2 / BWA; filter by identity, alignment length,
or fraction of read aligned.
Relative abundance ≠ absolute load. Use the same dehosted reads that define
biological samples. Merge per-sample outputs carefully (headers differ by version).
How to run
coverm genome --coupled ${id}_1.fastq ${id}_2.fastq \
--genome-fasta-directory drep95/dereplicated_genomes/ -x fa \
-t 8 -o temp/coverm/${id}.txt
coverm contig -r contigs.fa --coupled ${id}_1.fastq ${id}_2.fastq \
-t 8 -o temp/coverm/${id}.contig.tsv
Key parameters
| Choice | Thinking |
|---|
genome vs contig | Profiling vs binning coverage tables |
| method (mean / trimmed_mean / …) | Match what your binner expects |
| min covered fraction | Default ~10% genome; tighten for strict presence |
| mapper | strobealign often fastest for Illumina→large refs |
Related skills
drep · skani · strobealign · gtdbtk · visualization · metabat2
