bin3C: exploiting Hi-C sequencing data to accurately resolve metagenome-assembled genomes

Published on 2019-03-14T09:19:38Z (GMT) by
Abstract Most microbes cannot be easily cultured, and metagenomics provides a means to study them. Current techniques aim to resolve individual genomes from metagenomes, so-called metagenome-assembled genomes (MAGs). Leading approaches depend upon time series or transect studies, the efficacy of which is a function of community complexity, target abundance, and sequencing depth. We describe an unsupervised method that exploits the hierarchical nature of Hi-C interaction rates to resolve MAGs using a single time point. We validate the method and directly compare against a recently announced proprietary service, ProxiMeta. bin3C is an open-source pipeline and makes use of the Infomap clustering algorithm ( https://github.com/cerebis/bin3C ).

Cite this collection

DeMaere, Matthew Z.; E. Darling, Aaron (2019): bin3C: exploiting Hi-C sequencing data to accurately resolve metagenome-assembled genomes. figshare. Collection.