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bin3C: exploiting Hi-C sequencing data to accurately resolve metagenome-assembled genomes
- DeMaere, Matthew Z., Darling, Aaron E.
- Genome biology 2019 v.20 no.1 pp. 46
- algorithms, genome, metagenomics, microorganisms, time series analysis
- 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).