SnapHiC: a computational pipeline to identify chromatin loops from single-cell Hi-C data

SnapHiC offers a computational tool for improving detection of chromatin loops from single-cell Hi-C data. Single-cell Hi-C (scHi-C) analysis has been increasingly used to map chromatin architecture in diverse tissue contexts, but computational tools to define chromatin loops at high resolution from scHi-C data are still lacking. Here, we describe Single-Nucleus Analysis Pipeline for Hi-C (SnapHiC), a method that can identify chromatin loops at high resolution and accuracy from scHi-C data. Using scHi-C data from 742 mouse embryonic stem cells, we benchmark SnapHiC against a number of computational tools developed for mapping chromatin loops and interactions from bulk Hi-C. We further demonstrate its use by analyzing single-nucleus methyl-3C-seq data from 2,869 human prefrontal cortical cells, which uncovers cell type-specific chromatin loops and predicts putative target genes for noncoding sequence variants associated with neuropsychiatric disorders. Our results indicate that SnapHiC could facilitate the analysis of cell type-specific chromatin architecture and gene regulatory programs in complex tissues.

Automated summary

SnapHiC is a computational tool for improving the detection of chromatin loops from single-cell Hi-C data, allowing high-resolution and accurate identification of chromatin loops. It can be used to analyze cell type-specific chromatin architecture and gene regulatory programs.