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Updated: Mar 8, 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

Software tools for visualizing Hi-C data.

Galip Gürkan Yardımcı¹, William Stafford Noble²

¹Department of Genome Sciences, University of Washington, 3720 15th Ave NE, Seattle, 98105, WA, USA.

|February 5, 2017

Summary

Understanding DNA

Area of Science:

Genomics
Molecular Biology
Bioinformatics

Background:

High-throughput assays reveal DNA's 3D structure and its functional implications.
Interpreting large datasets from ChIA-PET and Hi-C assays is difficult with standard genome browsers.

Purpose of the Study:

To review and compare five software tools for visualizing chromosome conformation capture (3C) data, specifically Hi-C.
To identify tools that facilitate the interpretation of complex 3D genome data without requiring programming expertise.

Main Methods:

Literature review and functional comparison of five selected Hi-C visualization software tools.
Assessment of visualization modes, data integration capabilities, and user-friendliness.

Main Results:

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Last Updated: Mar 8, 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

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

ExCYT: A Graphical User Interface for Streamlining Analysis of High-Dimensional Cytometry Data

ExCYT: A Graphical User Interface for Streamlining Analysis of High-Dimensional Cytometry Data

Published on: January 16, 2019

The reviewed tools offer diverse functionalities for 3D genome data visualization.
Specific tools excel in particular tasks, such as handling large datasets or integrating with other genomic data.

Conclusions:

Selecting the appropriate Hi-C visualization tool depends on specific research needs and data types.
User-friendly software is crucial for advancing the interpretation of 3D genome organization and function.