ChromSCape

ChromSCape analyzes single-cell epigenomic data to characterize chromatin landscapes and the heterogeneity of histone modifications and chromatin accessibility across cell populations, including low-coverage and sparse datasets.

Key Features:

• Single-cell epigenomic data processing: Processes single-cell epigenomic datasets to enable downstream analysis of chromatin marks and accessibility.
• Histone modification analysis: Analyzes the distribution of both repressive and active histone modifications.
• Chromatin accessibility analysis: Profiles chromatin accessibility landscapes from single-cell datasets.
• Heterogeneity characterization: Focuses on cell-to-cell variability and chromatin mark heterogeneity at single-cell resolution.
• Low-coverage and sparse data handling: Tailored for the low coverage and sparse data typical of single-cell epigenomic assays.
• Chromatin landscape deconvolution: Deconvolves chromatin landscapes to reveal distinct modification patterns, including H3K27me3 signatures associated with cell identity and breast tumor subtypes.
• Single-cell histone mark mapping support: Leverages mapping of histone marks at single-cell resolution to characterize chromatin mark heterogeneity.

Scientific Applications:

• Gene regulation in development and disease: Analysis of histone modification distributions to study dynamic regulation of gene expression during development and disease processes.
• Chromatin accessibility studies: Examination of chromatin accessibility landscapes to investigate regulatory states across individual cells.
• Tumor micro-environment and cancer subtype analysis: Deconvolution of chromatin landscapes in tumor micro-environment studies to identify H3K27me3 patterns linked to cell identity and breast tumor subtypes.
• Characterization of chromatin mark heterogeneity over time: Identification of chromatin mark heterogeneity in complex biological systems across temporal or condition-specific contexts.

Methodology:

Analyzes mapped single-cell histone mark and chromatin accessibility data, accommodating low-coverage, sparse datasets to characterize chromatin mark heterogeneity.