MaxBin 2.0: an automated binning algorithm to recover genomes from multiple metagenomic datasets

The recovery of genomes from metagenomic datasets is a critical step to defining the functional roles of the underlying uncultivated populations. We previously developed MaxBin, an automated binning approach for high-throughput recovery of microbial genomes from metagenomes. Here we present an expan...

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Bibliographic Details
Published in:Bioinformatics 2016-02, Vol.32 (4), p.605-607
Main Authors: Wu, Yu-Wei, Simmons, Blake A, Singer, Steven W
Format: Article
Language:English
Subjects:
Algorithms
Automation
Bacteria
BASIC BIOLOGICAL SCIENCES
Bioinformatics
Genome, Bacterial
Genome, Microbial
Genomes
MATHEMATICS AND COMPUTING
Metagenome
Metagenomics - methods
Microorganisms
Recovering
Recovery
Software
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Summary:The recovery of genomes from metagenomic datasets is a critical step to defining the functional roles of the underlying uncultivated populations. We previously developed MaxBin, an automated binning approach for high-throughput recovery of microbial genomes from metagenomes. Here we present an expanded binning algorithm, MaxBin 2.0, which recovers genomes from co-assembly of a collection of metagenomic datasets. Tests on simulated datasets revealed that MaxBin 2.0 is highly accurate in recovering individual genomes, and the application of MaxBin 2.0 to several metagenomes from environmental samples demonstrated that it could achieve two complementary goals: recovering more bacterial genomes compared to binning a single sample as well as comparing the microbial community composition between different sampling environments. MaxBin 2.0 is freely available at http://sourceforge.net/projects/maxbin/ under BSD license.
ISSN:1367-4803
1367-4811
1460-2059
DOI:10.1093/bioinformatics/btv638