MaxBin 2.0: an automated binning algorithm to recover genomes from multiple metagenomic datasets
- Joint BioEnergy Inst. (JBEI), Emeryville, CA (United States); Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States)
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. Supplementary information: Supplementary data are available at Bioinformatics online.
- Research Organization:
- Lawrence Berkeley National Laboratory (LBNL), Berkeley, CA (United States)
- Sponsoring Organization:
- USDOE Office of Science (SC), Biological and Environmental Research (BER) (SC-23)
- DOE Contract Number:
- AC02-05CH11231
- OSTI ID:
- 1407392
- Journal Information:
- Bioinformatics, Journal Name: Bioinformatics Journal Issue: 4 Vol. 32; ISSN 1367-4803
- Publisher:
- Oxford University Press
- Country of Publication:
- United States
- Language:
- English
Similar Records
ATLAS: a Snakemake workflow for assembly, annotation, and genomic binning of metagenome sequence data
Recovering complete and draft population genomes from metagenome datasets