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Related Experiment Video

Updated: May 18, 2026

Hi-C: A Method to Study the Three-dimensional Architecture of Genomes.

Hi-C: A Method to Study the Three-dimensional Architecture of Genomes.

Published on: May 6, 2010

Computational Analysis of Hi-C Data.

Mattia Forcato¹, Silvio Bicciato²

¹Department of Life Sciences, University of Modena and Reggio Emilia, Modena, Italy. mattia.forcato@unimore.it.

Methods in Molecular Biology (Clifton, N.J.)

|August 22, 2020

Summary

This summary is machine-generated.

This chapter details computational analysis of Hi-C data for understanding 3D genome organization. It covers processing, normalization, and identifying topologically associating domains (TADs) and enhancer-promoter loops in chromatin.

Keywords:

3D chromatin structure Bioinformatics Chromatin interactions Hi-C data Topologically associating domains

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Last Updated: May 18, 2026

Hi-C: A Method to Study the Three-dimensional Architecture of Genomes.

Hi-C: A Method to Study the Three-dimensional Architecture of Genomes.

Published on: May 6, 2010

Capturing Chromosome Conformation Across Length Scales

Capturing Chromosome Conformation Across Length Scales

Published on: January 20, 2023

Deciphering High-Resolution 3D Chromatin Organization via Capture Hi-C

Deciphering High-Resolution 3D Chromatin Organization via Capture Hi-C

Published on: October 14, 2022

Area of Science:

Genomics
Molecular Biology
Bioinformatics

Background:

3D chromatin organization is crucial for genome function, involving chromosome territories, compartments, topologically associating domains (TADs), and enhancer-promoter loops.
Chromosome conformation capture (3C) techniques, especially Hi-C, are powerful tools for studying this nuclear organization.
Analyzing the vast Hi-C data requires complex computational pipelines, posing challenges even for experts.

Purpose of the Study:

To provide a comprehensive guide to the computational analysis of Hi-C data.
To detail the processing of raw Hi-C data, generation, and normalization of contact maps.
To explain the detection and visualization of genomic structures like TADs and loops.

Main Methods:

Utilized Hi-C technology on the GM12878 lymphoblastoid cell line.
Employed multistep computational procedures for raw data processing and analysis.
Applied algorithms for contact map generation, normalization, TAD detection, and interaction identification.

Main Results:

Successfully processed and analyzed Hi-C data from GM12878 cells.
Generated normalized Hi-C contact maps.
Identified topologically associating domains (TADs) and enhancer-promoter interactions.

Conclusions:

The described computational pipeline facilitates the analysis of Hi-C data for studying 3D genome organization.
This approach enables detailed characterization of chromatin structure, including TADs and loops.
The methodology aids in understanding the relationship between chromatin organization and genome functionality.