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SnapHiC2: A computationally efficient loop caller for single cell Hi-C data.

ABSTRACT: Single cell Hi-C (scHi-C) technologies enable the study of chromatin spatial organization directly from complex tissues at single cell resolution. However, the identification of chromatin loops from single cells is challenging, largely due to the extremely sparse data. Our recently developed SnapHiC pipeline provides the first tool to map chromatin loops from scHi-C data, but it is computationally intensive. Here we introduce SnapHiC2, which adapts a sliding window approximation when imputing missing contacts in each single cell and reduces both memory usage and computational time by 70%. SnapHiC2 can identify 5 Kb resolution chromatin loops with high sensitivity and accuracy and help to suggest target genes for GWAS variants in a cell-type-specific manner. SnapHiC2 is freely available at: https://github.com/HuMingLab/SnapHiC/releases/tag/v0.2.2.

SUBMITTER: Li X

PROVIDER: S-EPMC9168059 | biostudies-literature | 2022

REPOSITORIES: biostudies-literature

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SnapHiC2: A computationally efficient loop caller for single cell Hi-C data.

Li Xiaoqi X Lee Lindsay L Abnousi Armen A Yu Miao M Liu Weifang W Huang Le L Li Yun Y Hu Ming M

Computational and structural biotechnology journal 20220601

Single cell Hi-C (scHi-C) technologies enable the study of chromatin spatial organization directly from complex tissues at single cell resolution. However, the identification of chromatin loops from single cells is challenging, largely due to the extremely sparse data. Our recently developed SnapHiC pipeline provides the first tool to map chromatin loops from scHi-C data, but it is computationally intensive. Here we introduce SnapHiC2, which adapts a sliding window approximation when imputing mi ...[more]

PMID: 35685374

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