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

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ID: 290634
2015
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Abstract
Abstract 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. Availability and implementation: MaxBin 2.0 is freely available at http://sourceforge.net/projects/maxbin/ under BSD license. Contact: ywwei@lbl.gov Supplementary information: Supplementary data are available at Bioinformatics online.
Reference Key
openalex_W1878521557 Use this key to autocite in the manuscript while using SciMatic Manuscript Manager or Thesis Manager
Authors Yu‐Wei Wu, Blake A. Simmons, Steven W. Singer
Journal BMC Bioinformatics
Year 2015
DOI
10.1093/bioinformatics/btv638
URL
https://academic.oup.com/bioinformatics/article-pdf/32/4/605/49017620/btv638.pdf
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