ArticleNature biotechnology2026
Troubleshooting common errors in assemblies of long-read metagenomes.
Article in Nature biotechnology, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.
What it found
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The trial behind it
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Who cites it
9 citing papers in PubMed.
- DecBin: Bayesian-optimized deep clustering for long-read metagenomic binning.Briefings in bioinformatics · 2026Article
- Evidence tiers for strain-resolved long-read metagenomics.iMetaOmics · 2026Article
- Phylogenize2: robust phylogenetic methods link genes to phenotypes across host-associated and environmental microbiomes.bioRxiv : the preprint server for biology · 2026Article
- Diversification in ANME-1 archaea is associated with the presence of highly variable genomic hotspots.Nature communications · 2026Article
- Benchmarking of shotgun sequencing depth reveals the potential and limitations of shallow metagenomics and strain-level analysis.Nature microbiology · 2026Article
- Antibiotic resistance gene analyses in microbial communities: challenges and opportunities.Nature communications · 2026Article
- High-quality metagenome assembly from nanopore reads with nanoMDBG.Nature communications · 2026Article
- Recovery and microbial host assignment of mobile genetic elements in complex microbiomes: insights from a spiked gut sample.mSystems · 2026Article
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Corrections and comments
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Authors and funding
4 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Assessing the accuracy of long-read assemblies, especially from complex environmental metagenomes that include underrepresented organisms, is challenging. Here we benchmark four state-of-the-art long-read assembly software programs, HiCanu, hifiasm-meta, metaFlye and metaMDBG, on 21 PacBio HiFi metagenomes spanning mock communities, gut microbiomes and ocean samples. By quantifying read clipping events, in which long reads are systematically split during mapping to maximize the agreement with assembled contigs, we identify where assemblies diverge from their source reads. Our analyses reveal that long-read metagenome assemblies can include >40 errors per 100 million base pairs of assembled contigs, including multi-domain chimeras, prematurely circularized sequences, haplotyping errors, excessive repeats and phantom sequences. We provide an open-source tool and a reproducible workflow for rigorous evaluation of assembly errors, charting a path toward more reliable genome recovery from long-read metagenomes.
Identifiers
41482538What OpenQuestion holds
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.