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

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 ).

journal_name

Genome Biol

journal_title

Genome biology

authors

DeMaere MZ,Darling AE

doi

10.1186/s13059-019-1643-1

subject

Has Abstract

pub_date

2019-02-26 00:00:00

pages

46

issue

1

eissn

1474-7596

issn

1474-760X

pii

10.1186/s13059-019-1643-1

journal_volume

20

pub_type

杂志文章

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