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

Journal Article · · PeerJ
DOI:https://doi.org/10.7717/peerj.1165· OSTI ID:1257449
 [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)

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.

Research Organization:
Lawrence Berkeley National Laboratory (LBNL), Berkeley, CA (United States)
Sponsoring Organization:
USDOE
Grant/Contract Number:
AC02-05CH11231
OSTI ID:
1257449
Journal Information:
PeerJ, Vol. 3; ISSN 2167-8359
Publisher:
PeerJ Inc.Copyright Statement
Country of Publication:
United States
Language:
English
Citation Metrics:
Cited by: 990 works
Citation information provided by
Web of Science

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