ArticlePeerJ2019
MetaBAT 2: an adaptive binning algorithm for robust and efficient genome reconstruction from metagenome assemblies.
Article in PeerJ, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to trial NCT07169123 (Protease Regulation and Impact of Sodium as Mechanisms of Inflammation in IBD), which is not on this map. Cited by 2,170 papers.
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Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Protease Regulation and Impact of Sodium as Mechanisms of Inflammation in IBD
Who cites it
2,170 citing papers in PubMed.
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- Soil proteogenomics uncover microbial strategies for soil depth-specific carbon cycling under whole-soil warming conditions.Nature communications · 2026Article
- Extensive genomic diversity in Desulfovibrio reveals species-specific functional traits associated with disease.Nature communications · 2026Article
- Novel Antarctic chemolithotroph drives iron biomineralization.Microbiome · 2026Article
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- High diversity but limited expression of biosynthetic gene clusters in a peatland microbial community.Nature communications · 2026Article
2,110 more citing papers are in PubMed but not listed here.
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Authors and funding
7 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
We previously reported on MetaBAT, an automated metagenome binning software tool to reconstruct single genomes from microbial communities for subsequent analyses of uncultivated microbial species. MetaBAT has become one of the most popular binning tools largely due to its computational efficiency and ease of use, especially in binning experiments with a large number of samples and a large assembly. MetaBAT requires users to choose parameters to fine-tune its sensitivity and specificity. If those parameters are not chosen properly, binning accuracy can suffer, especially on assemblies of poor quality. Here, we developed MetaBAT 2 to overcome this problem. MetaBAT 2 uses a new adaptive binning algorithm to eliminate manual parameter tuning. We also performed extensive software engineering optimization to increase both computational and memory efficiency. Comparing MetaBAT 2 to alternative software tools on over 100 real world metagenome assemblies shows superior accuracy and computing speed. Binning a typical metagenome assembly takes only a few minutes on a single commodity workstation. We therefore recommend the community adopts MetaBAT 2 for their metagenome binning experiments. MetaBAT 2 is open source software and available at https://bitbucket.org/berkeleylab/metabat.
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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.