Comparison of computational methods for Hi-C data analysis
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Updated: Feb 28, 2026

Deciphering High-Resolution 3D Chromatin Organization via Capture Hi-C
Published on: October 14, 2022
Mattia Forcato1, Chiara Nicoletti1, Koustav Pal2
1Dept. of Life Sciences, Center for Genome Research, University of Modena and Reggio Emilia, Modena, Italy.
Abstract:
Hi-C is a genome-wide sequencing technique used to investigate 3D chromatin conformation inside the nucleus. Computational methods are required to analyze Hi-C data and identify chromatin interactions and topologically associating domains (TADs) from genome-wide contact probability maps. We quantitatively compared the performance of 13 algorithms in their analyses of Hi-C data from six landmark studies and simulations. This comparison revealed differences in the performance of methods for chromatin interaction identification, but more comparable results for TAD detection between algorithms.
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