Wu Yu-Wei, Simmons Blake A, Singer Steven W
Joint BioEnergy Institute, Emeryville, CA 94608, USA, Biological Systems and Engineering Division, Lawrence Berkeley National Laboratory, Berkeley, CA 94720, USA and.
Joint BioEnergy Institute, Emeryville, CA 94608, USA, Biological Systems and Engineering Division, Lawrence Berkeley National Laboratory, Berkeley, CA 94720, USA and Biological and Engineering Sciences Center, Sandia National Laboratories, Livermore, CA 94551, USA.
Bioinformatics. 2016 Feb 15;32(4):605-7. doi: 10.1093/bioinformatics/btv638. Epub 2015 Oct 29.
UNLABELLED: 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.
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