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Title: MetaBAT, an efficient tool for accurately reconstructing single genomes from complex microbial communities

Abstract

Grouping large genomic fragments assembled from shotgun metagenomic sequences to deconvolute complex microbial communities, or metagenome binning, enables the study of individual organisms and their interactions. Because of the complex nature of these communities, existing metagenome binning methods often miss a large number of microbial species. In addition, most of the tools are not scalable to large datasets. Here we introduce automated software called MetaBAT that integrates empirical probabilistic distances of genome abundance and tetranucleotide frequency for accurate metagenome binning. MetaBAT outperforms alternative methods in accuracy and computational efficiency on both synthetic and real metagenome datasets. Lastly, it automatically forms hundreds of high quality genome bins on a very large assembly consisting millions of contigs in a matter of hours on a single node. MetaBAT is open source software and available at https://bitbucket.org/berkeleylab/metabat.

Authors:
 [1];  [1];  [1];  [2]
  1. Department of Energy Joint Genome Institute, Walnut Creek, CA, (United States); ; Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States). Genomics Division
  2. Department of Energy Joint Genome Institute, Walnut Creek, CA, (United States); ; Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States). Genomics Division; Univ. of California, Merced, CA (United States)
Publication Date:
Research Org.:
Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States)
Sponsoring Org.:
USDOE
OSTI Identifier:
1257449
Grant/Contract Number:  
AC02-05CH11231
Resource Type:
Journal Article: Accepted Manuscript
Journal Name:
PeerJ
Additional Journal Information:
Journal Volume: 3; Journal ID: ISSN 2167-8359
Publisher:
PeerJ Inc.
Country of Publication:
United States
Language:
English
Subject:
59 BASIC BIOLOGICAL SCIENCES; Metagenome binning; MetaBAT

Citation Formats

Kang, Dongwan D., Froula, Jeff, Egan, Rob, and Wang, Zhong. MetaBAT, an efficient tool for accurately reconstructing single genomes from complex microbial communities. United States: N. p., 2015. Web. doi:10.7717/peerj.1165.
Kang, Dongwan D., Froula, Jeff, Egan, Rob, & Wang, Zhong. MetaBAT, an efficient tool for accurately reconstructing single genomes from complex microbial communities. United States. doi:10.7717/peerj.1165.
Kang, Dongwan D., Froula, Jeff, Egan, Rob, and Wang, Zhong. Thu . "MetaBAT, an efficient tool for accurately reconstructing single genomes from complex microbial communities". United States. doi:10.7717/peerj.1165. https://www.osti.gov/servlets/purl/1257449.
@article{osti_1257449,
title = {MetaBAT, an efficient tool for accurately reconstructing single genomes from complex microbial communities},
author = {Kang, Dongwan D. and Froula, Jeff and Egan, Rob and Wang, Zhong},
abstractNote = {Grouping large genomic fragments assembled from shotgun metagenomic sequences to deconvolute complex microbial communities, or metagenome binning, enables the study of individual organisms and their interactions. Because of the complex nature of these communities, existing metagenome binning methods often miss a large number of microbial species. In addition, most of the tools are not scalable to large datasets. Here we introduce automated software called MetaBAT that integrates empirical probabilistic distances of genome abundance and tetranucleotide frequency for accurate metagenome binning. MetaBAT outperforms alternative methods in accuracy and computational efficiency on both synthetic and real metagenome datasets. Lastly, it automatically forms hundreds of high quality genome bins on a very large assembly consisting millions of contigs in a matter of hours on a single node. MetaBAT is open source software and available at https://bitbucket.org/berkeleylab/metabat.},
doi = {10.7717/peerj.1165},
journal = {PeerJ},
number = ,
volume = 3,
place = {United States},
year = {Thu Jan 01 00:00:00 EST 2015},
month = {Thu Jan 01 00:00:00 EST 2015}
}

Journal Article:
Free Publicly Available Full Text
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Cited by: 87 works
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