Gghic: a versatile R package for exploring and visualizing 3D genome organization

Three-dimensional genome architecture is essential for gene regulation and cellular homeostasis. Its perturbation underlies pathologies. Advances in chromosome conformation capture technologies, such as Hi-C [1], have enabled researchers to study genome architecture at high resolution, yet the resulting matrices are difficult to explore visually, especially when one wishes to overlay genomic annotations or examine inter-chromosomal interactions. We introduce gghic, an R package that extends the ggplot2 grammar for the publication-quality visualization of chromatin-interaction data. Gghic supplies layers that draw (i) triangular Hi-C heatmaps, (ii) chromatin loops, topologically associating domains, (iii) gene or transcript models, (iv) one-dimensional signal tracks, (v) and multi-way contacts. The package supports Bioconductor classes, including HiCExperiment [2] and GInteractions [3]. It handles data from multiple chromosomes, enabling inspection of inter-chromosomal contacts. We illustrate the utility of gghic with acute lymphoblastic leukemia Hi-C datasets, producing publication-ready figures that reveal translocation breakpoints and higher-order chromatin hubs. By coupling advanced genome-structure analyses with the ggplot2 syntax, gghic makes the exploration and communication of 3D genomics data both intuitive and reproducible. References 1. Belton JM, McCord RP, Gibcus JH et al. ‘Hi-C: a comprehensive technique to capture the conformation of genomes’ Methods 2012;58:268–276. 2. Serizay J, Matthey-Doret C, Bignaud A et al. ‘Orchestrating chromosome conformation capture analysis with Bioconductor’ Nat Commun 2024;15:1072. 3. Lun AT, Perry M, Ing-Simmons E. ‘Infrastructure for genomic interactions: Bioconductor classes for Hi-C, ChIA-PET and related experiments’ F1000Res 2016;5:950.