MetaBAT, an efficient tool for accurately reconstructing single genomes from complex microbial communities
Joint Genome Institute · Lawrence Berkeley National Laboratory · +1 more institution
Abstract
Grouping large genomic fragments assembled from shotgun metagenomic sequences to deconvolute complex microbial communities, or metagenome binning, enables the study of individual organisms and their interactions. Because of the complex nature of these communities, existing metagenome binning methods often miss a large number of microbial species. In addition, most of the tools are not scalable to large datasets. Here we introduce automated software called MetaBAT that integrates empirical probabilistic distances of genome abundance and tetranucleotide frequency for accurate metagenome binning. MetaBAT outperforms alternative methods in accuracy and computational efficiency on both synthetic and real metagenome…
Citation impact
- FWCI
- 48.64
- Percentile
- 100%
- References
- 37
Authors
4- DKDongwan KangCorresponding
Joint Genome Institute, Lawrence Berkeley National Laboratory
- JFJeff Froula
Lawrence Berkeley National Laboratory, Joint Genome Institute
- RERob Egan
Joint Genome Institute, Lawrence Berkeley National Laboratory
- ZWZhong Wang
Lawrence Berkeley National Laboratory, Joint Genome Institute, University of California, Merced
Topics & keywords
- Metagenomics
- Computer science
- Shotgun sequencing
- Genome
- Scalability
- Software
- Contig
- Computational biology