MetaHiCNet: a web server for normalizing and visualizing microbial Hi-C interaction networks

Metagenomic Hi-C (metaHi-C) enables the reconstruction of microbial genome organization and interspecies interactions by capturing physical contacts between genomic fragments. However, raw metaHi-C data are often confounded by systematic biases and spurious contacts, which can obscure meaningful biological signals. Existing metaHi-C pipelines typically lack user-friendly normalization workflows and intuitive visualization tools, limiting the ability to explore microbial interaction networks. Here, we introduce MetaHiCNet, a web-based platform that supports widely used normalization methods with customizable parameters. MetaHiCNet provides a stepwise workflow for bias correction, spurious contact removal, and interactive visualization of microbial interactions. The platform supports multiple visualization modes, including taxonomic treemaps, cross-taxa networks, and cross-bin networks, enabling seamless transitions from community-wide overviews to detailed analyses of specific taxa or bins. This functionality facilitates the investigation of host-microbe interactions and the relationships between mobile genetic elements and their microbial hosts, offering deeper insights into microbial community structures and dynamics. MetaHiCNet is freely accessible at www.metahicnet.com without login.

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Publication Details

Journal
Nucleic Acids Research
Published
2025-04-26
DOI
https://doi.org/10.1093/nar/gkaf340
Primary Topic
Gut microbiota and health
Type
article
Field-Weighted Citation Impact
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article

MetaHiCNet: a web server for normalizing and visualizing microbial Hi-C interaction networks

Yuxuan Du, Chung‐Ming Sun, Ruishan Liu, Yuanxiong Guo et al.
Nucleic Acids Research
Gut microbiota and health
article

MetaHiCNet: a web server for normalizing and visualizing microbial Hi-C interaction networks

Yuxuan Du, Chung‐Ming Sun, Ruishan Liu, Yuanxiong Guo, Zhen Qin
article en

Abstract

Metagenomic Hi-C (metaHi-C) enables the reconstruction of microbial genome organization and interspecies interactions by capturing physical contacts between genomic fragments. However, raw metaHi-C data are often confounded by systematic biases and spurious contacts, which can obscure meaningful biological signals. Existing metaHi-C pipelines typically lack user-friendly normalization workflows and intuitive visualization tools, limiting the ability to explore microbial interaction networks. Here, we introduce MetaHiCNet, a web-based platform that supports widely used normalization methods with customizable parameters. MetaHiCNet provides a stepwise workflow for bias correction, spurious contact removal, and interactive visualization of microbial interactions. The platform supports multiple visualization modes, including taxonomic treemaps, cross-taxa networks, and cross-bin networks, enabling seamless transitions from community-wide overviews to detailed analyses of specific taxa or bins. This functionality facilitates the investigation of host-microbe interactions and the relationships between mobile genetic elements and their microbial hosts, offering deeper insights into microbial community structures and dynamics. MetaHiCNet is freely accessible at www.metahicnet.com without login.

Nucleic Acids ResearchVol. 53(W1)
University of Southern California (US), The University of Texas at San Antonio Health Science Center (US), The University of Texas at San Antonio (US)
Openalex Percentile: Top 92%
Gut microbiota and health
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