CscoreTool-M

CscoreTool-M infers multiple 3D genome sub-compartments from Hi-C sequencing data using probabilistic modeling to quantify cell-population heterogeneity in chromatin organization.

Key Features:

• Input data: Operates on Hi-C sequencing data to assess spatial genome organization.
• Probabilistic modeling: Calculates compartment scores that represent the probability of genomic regions occupying specific sub-compartments, enabling discrimination of active versus repressed chromatin states.
• Quantification of heterogeneity: Measures heterogeneity levels of sub-compartment localization within cell populations and compares heterogeneity between proliferating and terminally differentiated non-proliferating cells.
• Cell cycle stage-specific analysis: Analyzes 10 distinct sub-compartments to deconvolve genome organization specific to different cell cycle stages and identifies a sub-compartment associated with early-G1 chromatin near the nuclear lamina in HCT116 cells.
• Functional enrichment identification: Detects sub-compartments enriched for housekeeping genes and for cell-type-specific functions to aid functional annotation of spatially grouped genomic regions.

Scientific Applications:

• Chromatin dynamics and nuclear architecture: Mapping probabilistic sub-compartment distributions to study 3D genome structure and its variability across cell populations.
• Cellular differentiation and proliferation studies: Comparing sub-compartment heterogeneity between proliferating and differentiated cells to investigate effects of cell-cycle stage on genome organization.
• Functional genomics: Relating sub-compartment membership to enrichment of housekeeping or cell-type-specific genes for functional interpretation of spatial genome domains.
• Cell-cycle-resolved analysis: Deconvolving asynchronously dividing cell populations to identify cell-cycle-stage-associated spatial domains, including early-G1 lamina-proximal regions in HCT116 cells.

Methodology:

Uses Hi-C sequencing data and a probabilistic modeling framework to calculate compartment scores as probabilities, infer multiple (10) 3D genome sub-compartments, quantify localization heterogeneity, and deconvolve cell-cycle-stage-specific organization.