DiffGR

DiffGR detects differentially interacting genomic regions at the topologically associating domain (TAD) level between two Hi-C contact maps.

Key Features:

• Stratum-Adjusted Correlation Coefficient (SCC): DiffGR employs the stratum-adjusted correlation coefficient to measure similarity between local regions in two Hi-C contact matrices and mitigate the genomic-distance effect.
• Nonparametric Permutation Test: DiffGR applies a nonparametric permutation test on SCC values to identify statistically significant differential interacting genomic regions.
• Simulation Studies: Extensive simulation studies demonstrate DiffGR's ability to robustly detect differential genomic regions across diverse scenarios.
• Empirical Validation: Application to human and mouse Hi-C datasets reveals cell type-specific changes and comparative analyses indicate consistent, advantageous performance over existing differential TAD detection methods.

Scientific Applications:

• Comparative Genomics: Investigating cell type-specific and species-specific differences in chromatin organization.
• Epigenetics: Exploring how changes in chromatin structure relate to gene regulation and expression.
• Disease Research: Identifying alterations in chromatin interactions associated with diseases such as cancer.

Methodology:

DiffGR computes SCC between local regions of two Hi-C contact matrices and uses a nonparametric permutation test on SCC values to determine statistically significant differential TADs.