bioRxivBioinformaticsPreprint
SnapHiC-D: a computational pipeline to identify differential chromatin contacts from single cell Hi-C data
Lindsay LeeiD, Miao YuiD, Xiaoqi LiiD, Chenxu ZhuiD, Yanxiao ZhangiD, Hongyu YuiD, Bing ReniD, Yun LiiD, Ming HuiD
Abstract
Single cell Hi-C (scHi-C) has been used to map genome organization in complex tissues. However, computational tools to detect dynamic chromatin contacts from scHi-C datasets in development and through disease pathogenesis are still lacking. Here, we present SnapHiC-D, a computational pipeline to identify differential chromatin contacts (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 celltype-specific chromatin contacts at 10 kilobase resolution in mouse hippocampal and human prefrontal cortical tissues, and demonstrated that DCCs detected in the cortical and hippocampal cell types are generally correlated with cell-type-specific gene expression patterns and epigenomic features.
- organism: mouse
- organism: human
- assay: Hi-C
- research focus: differential expression
- research focus: gene regulatory network inference
- approach: statistical model
- Citations
- 2
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