CoMet: a workflow using contig coverage and composition for binning a metagenomic sample with high precision
Damayanthi Herath, Sen-Lin Tang, Kshitij Tandon, David Ackland, Saman Kumara Halgamuge
BMC BIOINFORMATICS | BMC | Published : 2017
BACKGROUND: In metagenomics, the separation of nucleotide sequences belonging to an individual or closely matched populations is termed binning. Binning helps the evaluation of underlying microbial population structure as well as the recovery of individual genomes from a sample of uncultivable microbial organisms. Both supervised and unsupervised learning methods have been employed in binning; however, characterizing a metagenomic sample containing multiple strains remains a significant challenge. In this study, we designed and implemented a new workflow, Coverage and composition based binning of Metagenomes (CoMet), for binning contigs in a single metagenomic sample. CoMet utilizes coverage..View full abstract
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Awarded by Australian Research Council (ARC)
Awarded by ARC
This work is partially funded by Australian Research Council (ARC) grant LP140100670. DH is supported by the MIRS and MIFRS Scholarships of The University of Melbourne. Publication costs of this article were funded by ARC grant LP140100670.