3DNetMod

3DNetMod detects hierarchical chromatin domains from Hi-C data using graph theory–based network modularity optimization to identify genomic interaction structures.

Key Features:

• Graph-Based Domain Detection: Represents Hi-C interaction data as a graph of genomic loci and spatial contacts to analyze chromatin organization.
• Network Modularity Optimization: Applies modularity optimization to identify chromatin domains with enriched intra-domain interactions relative to inter-domain interactions.
• Hierarchical Domain Identification: Detects nested and partially overlapping chromatin domains including topologically associating domains (TADs), subTADs, and chromatin loops.
• Resolution Parameter Control: Uses a tunable resolution parameter to detect chromatin domains across multiple genomic length scales.

Scientific Applications:

• 3D Genome Architecture Analysis: Characterizes hierarchical chromatin organization and spatial genome structure using Hi-C interaction data.
• Gene Regulation Studies: Investigates relationships between chromatin domain organization and gene regulatory mechanisms.
• Developmental Genome Organization: Examines changes in chromatin domain architecture during cellular differentiation and development.
• Disease-Associated Chromatin Structure Research: Studies alterations in chromatin domain organization associated with genetic disorders and chromatin misregulation.

Methodology:

3DNetMod constructs a graph representation of Hi-C interaction data in which nodes represent genomic loci and edges represent spatial contacts, and applies network modularity optimization with a tunable resolution parameter to detect hierarchical chromatin domains.