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Updated: Aug 18, 2025

Deciphering High-Resolution 3D Chromatin Organization via Capture Hi-C
Published on: October 14, 2022
Algorithmic considerations when analysing capture Hi-C data
Linden Disney-Hogg1,2, Ben Kinnersley1, Richard Houlston1
1Division of Genetics and Epidemiology, The Institute of Cancer Research and The Royal Marsden NHS Foundation Trust, Sutton, Surrey, SM2 5NG, UK.
Abstract:
Chromosome conformation capture methodologies have provided insight into the effect of 3D genomic architecture on gene regulation. Capture Hi-C (CHi-C) is a recent extension of Hi-C that improves the effective resolution of chromatin interactions by enriching for defined regions of biological relevance. The varying targeting efficiency between capture regions, however, introduces bias not present in conventional Hi-C, making analysis more complicated. Here we consider salient features of an algorithm that should be considered in evaluating the performance of a program used to analyse CHi-C data in order to infer meaningful interactions. We use the program CHICAGO to analyse promoter capture Hi-C data generated on 28 different cell lines as a case study.

