diffHic

diffHic detects differential chromatin interactions from Hi-C (Chromatin Conformation Capture with High-Throughput Sequencing) data to compare interaction intensities across biological conditions.

Key Features:

• Read Pair Alignment and Processing: Performs alignment and processing of Hi-C read pairs to map paired reads to genomic loci for downstream analysis.
• Interaction Counting and Filtering: Aggregates aligned reads into genomic bin pairs to produce interaction counts and filters low-abundance bin pairs to remove weak or spurious events.
• Normalization Techniques: Applies normalization procedures to correct trended biases and copy-number variation (CNV)-driven biases in interaction counts.
• Statistical Analysis Using edgeR: Uses the edgeR package to model biological variability and test for significant differences in interaction intensity between conditions.
• Visualization Options: Produces visualizations to facilitate exploration of interaction patterns and differential signals across conditions.

Scientific Applications:

• Gene regulation studies: Identification of condition-specific changes in chromatin interactions that may underlie gene expression differences.
• Epigenetics: Detection of differential interactions associated with epigenetic modifications across samples.
• Disease research (including cancer): Comparison of chromatin interaction changes between disease and control states to reveal structural alterations.
• Developmental biology: Analysis of dynamic chromatin interaction changes across developmental stages or cell differentiation.
• Evolutionary and environmental response studies: Investigation of interaction changes related to evolutionary divergence or responses to environmental stimuli.

Methodology:

Align read pairs from Hi-C experiments; aggregate aligned reads into bin pairs and count interactions with filtering of low-abundance events; apply normalization to correct trended and CNV-driven biases; perform statistical testing of differential interaction intensity using edgeR; generate visualizations.