Orchestrating chromosome conformation capture analysis with Bioconductor

Jacques Serizay; Cyril Matthey-Doret; Amaury Bignaud; Lyam Baudry; Romain Koszul

doi:10.1038/s41467-024-44761-x

Orchestrating chromosome conformation capture analysis with Bioconductor

Nat Commun. 2024 Feb 5;15(1):1072. doi: 10.1038/s41467-024-44761-x.

Authors

Jacques Serizay¹, Cyril Matthey-Doret^{2

3

4}, Amaury Bignaud^{2

3}, Lyam Baudry^{2

3

5}, Romain Koszul²

Affiliations

¹ Institut Pasteur, CNRS UMR3525, Université Paris Cité, Unité Régulation Spatiale des Génomes, Paris, France. jacques.serizay@pasteur.fr.
² Institut Pasteur, CNRS UMR3525, Université Paris Cité, Unité Régulation Spatiale des Génomes, Paris, France.
³ Sorbonne Université, Collège Doctoral, Paris, France.
⁴ Swiss Data Science Center, École Polytechnique Fédérale de Lausanne, 1015, Lausanne, Switzerland.
⁵ Université de Lausanne, Center for Integrative Genomics, Quartier Sorge, 1015, Lausanne, Switzerland.

Abstract

Genome-wide chromatin conformation capture assays provide formidable insights into the spatial organization of genomes. However, due to the complexity of the data structure, their integration in multi-omics workflows remains challenging. We present data structures, computational methods and visualization tools available in Bioconductor to investigate Hi-C, micro-C and other 3C-related data, in R. An online book ( https://bioconductor.org/books/OHCA/ ) further provides prospective end users with a number of workflows to process, import, analyze and visualize any type of chromosome conformation capture data.

MeSH terms

Chromatin* / genetics
Chromosomes* / genetics
Genome
Molecular Conformation
Prospective Studies

Substances

Chromatin