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HiCBin: binning metagenomic contigs and recovering metagenome-assembled genomes using Hi-C contact maps

Yuxuan Du, Fengzhu Sun

2022Genome biology50 citationsDOIOpen Access PDF

Abstract

Recovering high-quality metagenome-assembled genomes (MAGs) from complex microbial ecosystems remains challenging. Recently, high-throughput chromosome conformation capture (Hi-C) has been applied to simultaneously study multiple genomes in natural microbial communities. We develop HiCBin, a novel open-source pipeline, to resolve high-quality MAGs utilizing Hi-C contact maps. HiCBin employs the HiCzin normalization method and the Leiden clustering algorithm and includes the spurious contact detection into binning pipelines for the first time. HiCBin is validated on one synthetic and two real metagenomic samples and is shown to outperform the existing Hi-C-based binning methods. HiCBin is available at https://github.com/dyxstat/HiCBin .

Topics & Concepts

MetagenomicsContigGenomeBiologyComputational biologyNormalization (sociology)Spurious relationshipCluster analysisPipeline (software)Computer scienceGeneticsArtificial intelligenceGeneMachine learningAnthropologySociologyProgramming languageGenomics and Phylogenetic StudiesRNA and protein synthesis mechanismsMicrobial Community Ecology and Physiology
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