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bioRxiv · 10.1101/2020.12.13.422543

SnapHiC: a computational pipeline to map chromatin contacts from single cell Hi-C data

Yu, M.·Abnousi, A.·Zhang, Y.·Li, G.·Lee, L.·Chen, Z.·Fang, R.·Wen, J.·Sun, Q.·Li, Y.·Ren, B.·Hu, M.
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Abstract

Single cell Hi-C (scHi-C) analysis has been increasingly used to map the chromatin architecture in diverse tissue contexts, but computational tools to define chromatin contacts at high resolution from scHi-C data are still lacking. Here, we describe SnapHiC, a method that can identify chromatin loops at high resolution and accuracy from scHi-C data. We benchmark SnapHiC against HiCCUPS, a common tool for mapping chromatin contacts in bulk Hi-C data, using scHi-C data from 742 mouse embryonic stem cells. We further demonstrate its utility by analyzing single-nucleus methyl-3C-seq data from 2,869 human prefrontal cortical cells. We uncover cell-type-specific chromatin loops and predict putative target genes for non-coding sequence variants associated with neuropsychiatric disorders. Our results suggest that SnapHiC could facilitate the analysis of cell-type-specific chromatin architecture and gene regulatory programs in complex tissues.

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Yu, M., Abnousi, A., Zhang, Y., Li, G., Lee, L., Chen, Z., Fang, R., Wen, J., Sun, Q., Li, Y., Ren, B., Hu, M.. 2020-12-15. SnapHiC: a computational pipeline to map chromatin contacts from single cell Hi-C data. https://doi.org/10.1101/2020.12.13.422543

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