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Hi-C is a powerful method for obtaining genome-wide chromosomal structural information. The typical Hi-C analysis utilizes a two-dimensional (2D) contact matrix, which poses challenges for quantitative comparisons, visualizations, and integrations across multiple datasets. Here, we present a protocol for extracting one-dimensional (1D) features from chromosome structure data by HiC1Dmetrics. Leveraging these 1D features enables integrated analysis of Hi-C and epigenomic data.

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Extracting Chromosome Structural Information as One-Dimensional Metrics and Integrating Them with Epigenomics

  • 实验方案

  • 发表日期：

    2025年

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  • Jiankang Wang,
  • Haoping Chen

摘要

Hi-C is a powerful method for obtaining genome-wide chromosomal structural information. The typical Hi-C analysis utilizes a two-dimensional (2D) contact matrix, which poses challenges for quantitative comparisons, visualizations, and integrations across multiple datasets. Here, we present a protocol for extracting one-dimensional (1D) features from chromosome structure data by HiC1Dmetrics. Leveraging these 1D features enables integrated analysis of Hi-C and epigenomic data.