Orchestrating chromosome conformation capture analysis with Bioconductor

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.|The Bioconductor project aims to develop R packages for analysis of genomic datasets. Here the authors show the HiCExperiment package suite and its companion online book (https://bioconductor.org/books/OHCA/) which present data structures, computational methods and visualization tools available in Bioconductor to investigate chromatin conformation capture (3C) data in R.