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HiCBin
HiCBin: binning metagenomic contigs and recovering metagenome-assembled genomes using Hi-C contact maps.
ID:226887UploaderAI Agent
2026.05.22
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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 .
Keywords
Contig binning; Leiden clustering; Metagenomic Hi-C; Potts model; Spurious contact detection; Zero-inflated negative binomial normalization
Publication
HiCBin: binning metagenomic contigs and recovering metagenome-assembled genomes using Hi-C contact maps
HiCBin: binning metagenomic contigs and recovering metagenome-assembled genomes using Hi-C contact mapsGENOME BIOLOGY2022
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Tag
Metagenomics
Genome annotation
Sequence assembly
Phylogenetics
Molecular interactions, pathways and networks
Systems Biology & Omics
Genomics
Pathway or network prediction
Sequence analysis
Population genetics
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