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

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 HiCrayon's 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. Overall design: Hi-C samples from 8 cell lines in LCL, with replicates ranging from 3 to 34. The following shows cell line with replicate number; AK1: 9, GM12878: 34 (re-analyzed; raw files not uploaded. Only processed combination), GM12891: 4, GM12892: 3, GM13976: 16, GM13977: 16, GM18526: 20, GM19239: 24 Please note that the GM12878.hic was generated by re-analyzing the 'GSM1551550-GSM1551578' samples (in GSE63525) and the re-analyzed sample details are provided in the 're-analyzed_sample_accns.txt'

将染色质构象与一维组学（1D 'omics）数据进行联合可视化，是依托多组学开展三维基因组组织数据分析的核心环节。染色质相互作用图谱通常以二维热图形式呈现，传统可视化策略仅通过简单并置来实现其与一维基因组数据的视觉对比。尽管该策略较为常用，但精度不足，需要研究者自行对齐不同数据中的特征，增加了解读负担。为解决这一问题，我们开发了HiCrayon——一款可实现三维染色质组织图谱与一维组学数据集整合的交互式可视化工具。该可视化方法通过根据一维信号对染色质相互作用进行着色，将基因组检测得到的数据直接整合至染色质相互作用图谱中。HiCrayon基于R Shiny与Python开发，构建了图形用户界面（GUI）应用程序，提供网页版与容器化部署两种形式以提升工具的可及性。该工具基于R实现，除完整GUI外，还包含轻量化网页版本，可帮助用户快速生成符合期刊发表要求的可视化图像。我们通过实例展示了HiCrayon在可视化染色质区室调用效果，以及分析染色质免疫共沉淀测序（ChIP-seq）与染色质组织各类特征间关联方面的实用性。此外，我们还展示了HiCrayon对其他三维基因组现象的优化可视化效果，例如与CTCF/黏连蛋白（cohesin）结合的染色质环，同与H3K27ac修饰相关的染色质环之间的差异。随后，我们展示了HiCrayon对细胞分化过程中染色质组织动态变化的可视化效果，并借助该工具识别出了无法归类为A/B区室的特殊染色质区室模式，揭示了一类全新的第三类染色质区室。综上，我们验证了在同一矩阵中联合可视化二维染色质构象与一维基因组信号的实用性，该方法可用于揭示基因组组织的核心特征。
实验整体设计：本数据集包含淋巴母细胞样细胞系（LCL）中的8株细胞的高通量染色体构象捕获（Hi-C）样本，生物学重复数介于3至34之间。各细胞系及其重复数如下：AK1：9次重复；GM12878：34次重复（已重新分析，原始数据未上传，仅提供合并后的处理后数据）；GM12891：4次重复；GM12892：3次重复；GM13976：16次重复；GM13977：16次重复；GM18526：20次重复；GM19239：24次重复。
请注意：GM12878.hic文件是通过重新分析GSE63525数据集下的GSM1551550至GSM1551578样本生成的，重新分析的样本详情可在're-analyzed_sample_accns.txt'文件中查看。