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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.
Rémi Guillaume Petitpierre, Paul Robert Guhennec, Beatrice Vaienti, Didier Louis Dupertuis
Brice Tanguy Alphonse Lecampion, Andreas Möri