bio-hi-c-analysis-compartment-analysis - Identify A/B compartments from Hi-C data with cooltools
Detects A/B chromatin compartments from Hi-C contact matrices using cooltools eigenvector decomposition and quantifies compartmentalization strength.
Tags
Updated: 2026-09-19Capabilities
Typical Inputs
Typical Outputs
What this skill does
- Compute compartment eigenvectors
- Orient compartments using GC content
- Extract AB compartment calls
- Compute compartment saddle plots
- Calculate compartment strength score
- Plot compartment eigenvector tracks
- Export compartment call files
- Compare compartments between samples
- Correlate compartments with gene expression
Inputs
- Hi-C contact matrices in mcool format
- Reference genome FASTA file
- Reference genome chromosome sizes
- Gene expression data
Outputs
- Compartment calls in BED format
- Eigenvector tracks in bedGraph format
- Saddle plot image file
- Compartment track plot image file
- Compartment strength score
- Sample comparison and switch annotations
Requirements
- Python environment
- cooler 0.9+
- cooltools 0.6+
- matplotlib 3.8+
- numpy 1.26+
- pandas 2.2+
- scipy 1.12+
- bioframe