Sun Chentong, Qin Zhen, Liu Ruishan, Guo Yuanxiong, Ge Yong, Du Yuxuan
Department of Electrical and Computer Engineering, The University of Texas at San Antonio, San Antonio, Texas 78249, United States.
Department of Computer Science, University of Southern California, Los Angeles, California 90089, United States.
Nucleic Acids Res. 2025 Jul 7;53(W1):W383-W389. doi: 10.1093/nar/gkaf340.
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.
宏基因组Hi-C(metaHi-C)通过捕获基因组片段之间的物理接触,能够重建微生物基因组组织和种间相互作用。然而,原始的metaHi-C数据常常受到系统偏差和虚假接触的干扰,这可能会掩盖有意义的生物学信号。现有的metaHi-C流程通常缺乏用户友好的标准化工作流程和直观的可视化工具,限制了探索微生物相互作用网络的能力。在此,我们介绍MetaHiCNet,这是一个基于网络的平台,支持具有可定制参数的广泛使用的标准化方法。MetaHiCNet提供了一个用于偏差校正、去除虚假接触以及微生物相互作用交互式可视化的逐步工作流程。该平台支持多种可视化模式,包括分类树状图、跨分类单元网络和跨基因组箱网络,能够实现从群落范围概述到特定分类单元或基因组箱详细分析的无缝过渡。此功能有助于研究宿主-微生物相互作用以及移动遗传元件与其微生物宿主之间的关系,从而更深入地了解微生物群落结构和动态。无需登录即可通过www.metahicnet.com免费访问MetaHiCNet。