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

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…

• UD
  U.S. Department of Energy

  Awards: -AC02-05CH11231, 05CH11231, AC02-05CH11231, DE-AC02, DE-AC02-05CH11231, DE-AC02-
• OO
  Office of Science

  Awards: AC02-05CH11231, -AC02-05CH11231, DE-AC02
• BA
  Biological and Environmental Research

  Awards: 05CH11231, DE-AC02-05CH11231, AC02-05CH11231
• LB
  Lawrence Berkeley National Laboratory

  Awards: DE-AC02-05CH11231, 05CH11231, AC02-05CH11231