ArticleCommunications biology2025
Calculating fast differential genome coverages among metagenomic sources using micov.
Article in Communications biology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
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Who cites it
5 citing papers in PubMed.
- Megascale microbiome analysis with DartUniFrac.Nature biotechnology · 2026Article
- Interconnected influences of diet, gut microbiome, and metabolome on cognition across three metabolomics platforms.Research square · 2026Article
- Antibiotic Exposure Through Human Milk Influences the Infant Gut Microbiome.bioRxiv : the preprint server for biology · 2026Article
- A Multi-Omics Processing Pipeline (MOPP) for Extracting Taxonomic and Functional Insights from Metaribosome Profiling (metaRibo-Seq) data.bioRxiv : the preprint server for biology · 2026Article
- Community assembly modeling of the microbiome within Barrett's esophagus and esophageal adenocarcinoma.BMC genomics · 2026Article
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Authors and funding
15 authors.
Funding
Abstract
Breadth of coverage, the proportion of a reference genome covered by at least one sequencing read, is critical for interpreting metagenomic data, informing analyses from genome assembly to taxonomic profiling. However, existing tools typically summarize coverage breadth at the whole-genome or aggregate-sample level, missing informative variation along genomes and between sample groups. Here we introduce MIcrobiome COVerage (micov), a tool that computes and compares per-sample breadth of coverage across many genomes and samples. micov offers two key advances: (1) rapid cumulative coverage breadth calculations specific to each sample type, and (2) detection of differential coverage breadth along genomes. Applying micov to three metagenomic datasets, we show that it identifies a genomic region in Prevotella copri that explains variation in community composition independent of host country of origin, uncovers dietary association with a partially annotated region in an uncharacterized Lachnospiraceae genome, enabling hypothesis generation for genes of unknown function, and improves sensitivity in low-biomass settings by detecting a single genomic copy of enteropathogenic Escherichia coli (EPEC) in wastewater and distinguishing Mediterraneibacter gnavus across specimen types.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.