Bin3C: Exploiting Hi-C sequencing data to accurately resolve metagenome-assembled genomes
- Publication Type:
- Journal Article
- Genome Biology, 2019, 20 (1)
- Issue Date:
© 2019 The Author(s). 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).
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