ArticleNature communications2023
MetaCC allows scalable and integrative analyses of both long-read and short-read metagenomic Hi-C data.
Article in Nature communications, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers.
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Who cites it
14 citing papers in PubMed, 21 citations in OpenAlex.
- Plasmid-Host Networks Reveal Persistent Mobile Elements Across Wastewater Treatment.Nature communications · 2026Article
- VirBinn improves viral genome binning from metagenomic Hi-C through graph diffusion.Bioinformatics (Oxford, England) · 2026Article
- A review of computational approaches for metagenomics by long-read sequencing.Science China. Life sciences · 2026Review
- Metagenomic Hi‑C Protocols for Viral Genome Binning, Taxonomic Annotation, and Interaction Network Visualization.Current protocols · 2026Article
- Recovery and microbial host assignment of mobile genetic elements in complex microbiomes: insights from a spiked gut sample.mSystems · 2026Article
- Benchmarking alignment strategies for Hi-C reads in metagenomic Hi-C data.Genome biology · 2026Article
- Benchmarking with synthetic communities provides a baseline for virus-host inferences from Hi-C proximity linking.PLoS biology · 2025Article
- Metagenomic approaches for studying ubiquitous yet diverse nucleoid associated proteins in microbial communities: challenges and advances.World journal of microbiology & biotechnology · 2025Review
- MetaflowX: a scalable and resource-efficient workflow for multi-strategy metagenomic analysis.Nucleic acids research · 2025Article
- Computational Tools and Resources for Long-read Metagenomic Sequencing Using Nanopore and PacBio.Genomics, proteomics & bioinformatics · 2025Review
- MetaHiCNet: a web server for normalizing and visualizing microbial Hi-C interaction networks.Nucleic acids research · 2025Article
- Benchmarking metagenomic binning tools on real datasets across sequencing platforms and binning modes.Nature communications · 2025Article
- Analysis of metagenomic data.Nature reviews. Methods primers · 2025Article
- MetaCC allows scalable and integrative analyses of both long-read and short-read metagenomic Hi-C data.Nature communications · 2023Article
Corrections and comments
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Authors and funding
2 authors at 1 institution in 1 country.
Funding
Abstract
Metagenomic Hi-C (metaHi-C) can identify contig-to-contig relationships with respect to their proximity within the same physical cell. Shotgun libraries in metaHi-C experiments can be constructed by next-generation sequencing (short-read metaHi-C) or more recent third-generation sequencing (long-read metaHi-C). However, all existing metaHi-C analysis methods are developed and benchmarked on short-read metaHi-C datasets and there exists much room for improvement in terms of more scalable and stable analyses, especially for long-read metaHi-C data. Here we report MetaCC, an efficient and integrative framework for analyzing both short-read and long-read metaHi-C datasets. MetaCC outperforms existing methods on normalization and binning. In particular, the MetaCC normalization module, named NormCC, is more than 3000 times faster than the current state-of-the-art method HiCzin on a complex wastewater dataset. When applied to one sheep gut long-read metaHi-C dataset, MetaCC binning module can retrieve 709 high-quality genomes with the largest species diversity using one single sample, including an expansion of five uncultured members from the order Erysipelotrichales, and is the only binner that can recover the genome of one important species Bacteroides vulgatus. Further plasmid analyses reveal that MetaCC binning is able to capture multi-copy plasmids.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.