Department of Quantitative Health Sciences, Lerner Research Institute, Cleveland Clinic Foundation, Cleveland, OH, USA.
Ludwig Institute for Cancer Research, La Jolla, CA, USA.
Brief Bioinform. 2023 Sep 20;24(5). doi: 10.1093/bib/bbad315.
Single-cell high-throughput chromatin conformation capture technologies (scHi-C) has been used to map chromatin spatial organization in complex tissues. However, computational tools to detect differential chromatin contacts (DCCs) from scHi-C datasets in development and through disease pathogenesis are still lacking. Here, we present SnapHiC-D, a computational pipeline to identify DCCs between two scHi-C datasets. Compared to methods designed for bulk Hi-C data, SnapHiC-D detects DCCs with high sensitivity and accuracy. We used SnapHiC-D to identify cell-type-specific chromatin contacts at 10 Kb resolution in mouse hippocampal and human prefrontal cortical tissues, demonstrating that DCCs detected in the hippocampal and cortical cell types are generally associated with cell-type-specific gene expression patterns and epigenomic features. SnapHiC-D is freely available at https://github.com/HuMingLab/SnapHiC-D.
单细胞高通量染色质构象捕获技术(scHi-C)已被用于绘制复杂组织中的染色质空间构象。然而,用于从发育和疾病发病机制中的 scHi-C 数据集检测差异染色质接触(DCC)的计算工具仍然缺乏。在这里,我们提出了 SnapHiC-D,这是一种用于识别两个 scHi-C 数据集之间 DCC 的计算管道。与专门为批量 Hi-C 数据设计的方法相比,SnapHiC-D 具有高灵敏度和准确性地检测 DCC。我们使用 SnapHiC-D 在小鼠海马体和人类前额皮质组织中以 10 Kb 的分辨率识别细胞类型特异性染色质接触,证明在海马体和皮质细胞类型中检测到的 DCC 通常与细胞类型特异性基因表达模式和表观基因组特征相关。SnapHiC-D 可在 https://github.com/HuMingLab/SnapHiC-D 上免费获得。