HiCrayon reveals distinct layers of multi-state 3D chromatin organization

Abstract

The co-visualization of chromatin conformation with 1D omics data is key to the multi-omics driven data analysis of 3D genome organization. Chromatin contact maps are often shown as 2D heatmaps and visually compared to 1D genomic data by simple juxtaposition. While common, this strategy is imprecise, placing the onus on the reader to align features with each other. To remedy this, we developed HiCrayon, an interactive tool that facilitates the integration of 3D chromatin organization maps and 1D datasets. This visualization method integrates data from genomic assays directly into the chromatin contact map by coloring interactions according to 1D signal. HiCrayon is implemented using R shiny and python to create a graphical user interface (GUI) application, available in both web or containerized format to promote accessibility. HiCrayon is implemented in R, and includes a graphical user interface (GUI), as well as a slimmed-down web-based version that lets users quickly produce publication-ready images. We demonstrate the utility of HiCrayon in visualizing the effectiveness of compartment calling and the relationship between ChIP-seq and various features of chromatin organization. We also demonstrate the improved visualization of other 3D genomic phenomena, such as differences between loops associated with CTCF/cohesin vs. those associated with H3K27ac. We then demonstrate HiCrayons visualization of organizational changes that occur during differentiation and use HiCrayon to detect compartment patterns that cannot be assigned to either A or B compartments, revealing a distinct 3rd chromatin compartment. Overall, we demonstrate the utility of co-visualizing 2D chromatin conformation with 1D genomic signals within the same matrix to reveal fundamental aspects of genome organization. Local version: https://github.com/JRowleyLab/HiCrayon Web version: https://jrowleylab.com/HiCrayon