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Title: MetaBAT: Metagenome Binning based on Abundance and Tetranucleotide frequence

Grouping large fragments assembled from shotgun metagenomic sequences to deconvolute complex microbial communities, or metagenome binning, enables the study of individual organisms and their interactions. Here we developed automated metagenome binning software, called MetaBAT, which integrates empirical probabilistic distances of genome abundance and tetranucleotide frequency. On synthetic datasets MetaBAT on average achieves 98percent precision and 90percent recall at the strain level with 281 near complete unique genomes. Applying MetaBAT to a human gut microbiome data set we recovered 176 genome bins with 92percent precision and 80percent recall. Further analyses suggest MetaBAT is able to recover genome fragments missed in reference genomes up to 19percent, while 53 genome bins are novel. In summary, we believe MetaBAT is a powerful tool to facilitate comprehensive understanding of complex microbial communities.
Authors:
; ; ;
Publication Date:
OSTI Identifier:
1241199
Report Number(s):
LBNL-7106E
DOE Contract Number:
DE-AC02-05CH11231
Resource Type:
Conference
Resource Relation:
Conference: 9th Annual JGI User Meeting
Research Org:
Ernest Orlando Lawrence Berkeley National Laboratory, Berkeley, CA (US)
Sponsoring Org:
USDOE Office of Science (SC)
Country of Publication:
United States
Language:
English
Subject:
59 BASIC BIOLOGICAL SCIENCES