BHi-Cect

BHi-Cect applies a top-down spectral clustering approach to Hi-C contact maps to identify noncontiguous, hierarchical chromosome clusters ("enclaves") and relate their nesting to epigenomic activity.

Key Features:

• Top-Down Algorithmic Approach: Uses a top-down strategy that does not assume genomic contiguity, enabling detection of clusters beyond traditional topologically associating domains (TADs).
• Spectral Clustering Technique: Applies spectral clustering to Hi-C contact matrices to detect nested hierarchical structures within chromosomes.
• Identification of Enclaves: Identifies "enclaves," defined as smaller clusters nested within larger clusters, revealing interwoven interaction patterns at local and global scales.
• Association with Epigenomic Activity: Links hierarchical nesting patterns of clusters to epigenomic activity on DNA to suggest structure–function relationships.
• Integration of Functional Linkages: Analyzes hierarchical connections among enclaves to integrate and interpret their potential functional relationships.

Scientific Applications:

• Genome organization analysis: Reveals principles guiding chromatin architecture by detecting complex, noncontiguous interaction patterns.
• Chromatin–epigenome association studies: Relates clustering and nesting patterns to epigenomic activity for studies of structure–function coupling.
• Gene regulation insights: Provides information relevant to understanding how chromatin architecture influences gene regulation.
• Chromosomal dynamics: Supports investigation of hierarchical chromosomal interaction dynamics across local and global scales.
• Functional implication analysis: Enables interpretation of how hierarchical cluster integration may affect genomic function.

Methodology:

Top-down, noncontiguous clustering of Hi-C contact matrices using spectral clustering to detect nested hierarchical clusters ("enclaves") and associate nesting patterns with epigenomic activity.