SnapHiC

SnapHiC identifies high-resolution chromatin loops from single-cell Hi-C (scHi-C) and related single-nucleus methyl-3C-seq data to characterize cell type–specific chromatin architecture and infer gene regulatory interactions.

Key Features:

• High-resolution loop identification: Detects chromatin loops at high resolution from scHi-C data.
• Single-cell specificity: Maps cell type–specific chromatin loops across individual cells.
• Compatibility with single-nucleus methyl-3C-seq: Applied to single-nucleus methyl-3C-seq data from human prefrontal cortical cells.
• Benchmarking against bulk Hi-C methods: Benchmarked against computational methods developed for bulk Hi-C and shown to perform better in single-cell contexts.
• Validation on empirical datasets: Validated using scHi-C data from 742 mouse embryonic stem cells and single-nucleus methyl-3C-seq data from 2,869 human prefrontal cortical cells.
• Variant-target prediction: Facilitates prediction of putative target genes for noncoding sequence variants associated with neuropsychiatric disorders.

Scientific Applications:

• Cell type–specific chromatin architecture: Dissects chromatin architecture within complex tissues at single-cell resolution.
• Gene regulatory program analysis: Investigates spatial genome organization underlying gene regulation in individual cells.
• Genetic variant interpretation: Links noncoding sequence variants to putative target genes for studies of neuropsychiatric disorders.
• Method benchmarking: Serves as a reference for comparing single-cell chromatin interaction analyses with bulk Hi-C approaches.

Methodology:

Computational pipeline that identifies chromatin loops from scHi-C and single-nucleus methyl-3C-seq data and that was benchmarked against computational methods for bulk Hi-C.