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MetaBAT specifications


Unique identifier OMICS_10415
Name MetaBAT
Software type Pipeline/Workflow
Interface Command line interface
Restrictions to use None
Input data MetaBAT takes an assembly file (fasta format, required) and sorted bam files (one per sample, optional) as inputs.
Output data Each discovered bin will be saved as a fasta format.
Operating system Unix/Linux
Programming languages C++
Computer skills Advanced
Stability Stable
Boost, Python, scons, g++, zlib
Maintained Yes


No version available



  • person_outline Zhong Wang

Publication for MetaBAT

MetaBAT citations


Draft Genome Sequence of Actinobacterial Strain Kineosporia sp. R_H_3, a Neutrophilic Iron Depositing Bacterium

Genome Announc
PMCID: 5897805
PMID: 29650587
DOI: 10.1128/genomeA.00335-18

[…] up to 99 bp. scaffolds of ≥500 bp of this preassembly were subject to extension and second-round scaffolding with sspace standard v3.0 (). scaffolds of ≥2,500 bp were assigned to genome bins by metabat v0.32.4 (), and functional annotation of the draft genomes was performed with prokka v1.12b (). the draft genome included 270 scaffolds with an n50 assembly quality of 39,507 and an l50 value […]


Draft Genome Sequence of Strain B 225, an Iron Depositing Isolate of the Genus Novosphingobium

Genome Announc
PMCID: 5897806
PMID: 29650584
DOI: 10.1128/genomeA.00325-18

[…] up to 99 bp. scaffolds ≥500 bp of this preassembly were subject to extension and second-round scaffolding with the sspace standard version 3.0 (). scaffolds ≥2,500 bp were assigned to genome bins by metabat version 0.32.4 (), and functional annotation of the draft genomes was performed with prokka version 1.12b ()., the draft genome included 73 contigs, with an n50 assembly quality of 107,389 bp […]


Genomic expansion of magnetotactic bacteria reveals an early common origin of magnetotaxis with lineage specific evolution

PMCID: 5955933
PMID: 29581530
DOI: 10.1038/s41396-018-0098-9

[…] bases, and were assembled using metaspades [] with the following parameters (--only-assembler -k 31,41,51,61,71,81,91,101,111,121). assembled scaffolds ≥ 2500 bp were binned separately using metabat v0.26.1 [] and mycc []. results of two binning methods for each sample were combined and a non-redundant set of bins was chosen. the acquired genomes were curated manually with two […]


Species classifier choice is a key consideration when analysing low complexity food microbiome data

PMCID: 5859664
PMID: 29554948
DOI: 10.1186/s40168-018-0437-0

[…] another possible option for compositional analysis, which we did not explore here, is to use a de novo metagenome assembly approach, wherein genomes are binned using tools like concoct [] or metabat [], and reads are then mapped against these bins to calculate species abundances. an advantage of such an approach is that it does not rely on a reference database for diversity analysis […]


Metagenomic Insights into the Phylogenetic and Metabolic Diversity of the Prokaryotic Community Dwelling in Hypersaline Soils from the Odiel Saltmarshes (SW Spain)

PMCID: 5867873
PMID: 29518047
DOI: 10.3390/genes9030152

[…] manually curated. functional annotation of reads and contigs was carried out using cognizer v0.9b []. rarefaction curves were computed with qiime pipeline v1.9.1 []. , binning was performed with metabat v0.26.3 []. checkm v1.0.5 [] was then used for assessment of completion and contamination of the extracted genomes or bins. further refinement of bins was carried out with vizbin v0.9 []. […]


Metagenome Sequencing of Prokaryotic Microbiota from Two Hypersaline Soils of the Odiel Salt Marshes in Huelva, Southwestern Spain

Genome Announc
PMCID: 5834333
PMID: 29496841
DOI: 10.1128/genomeA.00140-18

[…] contigs were annotated using megan v6.5.10 lowest common ancestor (lca) algorithm (), and extraction, refinement, and quality assessment of metagenome assembled genomes (mags) were accomplished with metabat v0.26.3 (), vizbin v0.9 (), and checkm v1.0.5. additionally, blastn searches of metagenomic reads of smo1 and smo2 against rdp database v11.4 () were performed to retrieve and classify […]

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MetaBAT institution(s)
Department of Energy Joint Genome Institute, Walnut Creek, CA, USA; Genomics Division, Lawrence Berkeley National Laboratory, Berkeley, CA, USA; School of Natural Sciences, University of California at Merced, Merced, CA, USA
MetaBAT funding source(s)
The work was supported by the Office of Science of the US Department of Energy under Contract No. DE-AC02-05CH11231.

MetaBAT review

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Sarah Turner

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I think this is a useful and easy-to-use tool. However, it did not perform well with samples containing a large number of unknown/unidentified organisms (freshwater sediment), and may be more useful in situations where more of the taxa present in a sample have references available.