The shape of chromatin: insights from computational recognition of geometric patterns in Hi-C data

Andrea Raffo; Jonas Paulsen

doi:10.1093/bib/bbad302

The shape of chromatin: insights from computational recognition of geometric patterns in Hi-C data

Brief Bioinform. 2023 Sep 20;24(5):bbad302. doi: 10.1093/bib/bbad302.

Authors

Andrea Raffo¹, Jonas Paulsen^{1

2}

Affiliations

¹ Department of Biosciences, University of Oslo, 0316 Oslo, Norway.
² Centre for Bioinformatics, Department of Informatics, University of Oslo, 0316 Oslo, Norway.

Abstract

The three-dimensional organization of chromatin plays a crucial role in gene regulation and cellular processes like deoxyribonucleic acid (DNA) transcription, replication and repair. Hi-C and related techniques provide detailed views of spatial proximities within the nucleus. However, data analysis is challenging partially due to a lack of well-defined, underpinning mathematical frameworks. Recently, recognizing and analyzing geometric patterns in Hi-C data has emerged as a powerful approach. This review provides a summary of algorithms for automatic recognition and analysis of geometric patterns in Hi-C data and their correspondence with chromatin structure. We classify existing algorithms on the basis of the data representation and pattern recognition paradigm they make use of. Finally, we outline some of the challenges ahead and promising future directions.

Keywords: 3D genome organization; Hi-C; geometric patterns; pattern recognition.

Publication types

Review
Research Support, Non-U.S. Gov't

MeSH terms

Algorithms*
Chromatin* / genetics
Data Analysis

Substances

Chromatin