hic-compartments-calling

Hi-C compartments calling derives PC1 scores from contact maps by applying PCA through an automated workflow. It processes your input data to generate compartment scores and visualization outputs like saddle plots.

PCA-based Hi-C compartment calling supports .mcool, .cool, and .hic file formats. You must provide the Hi-C data along with the required genome assembly and resolution parameters to execute the workflow successfully.

Saddle analysis and A/B compartment identification require an end-to-end workflow including genome localization, chromosomal name harmonization, arm view creation, GC binning, and running expected_cis and eigs_cis before plotting final results.

Cooltools processes mcool files by running eigs_cis to compute eigenvectors and generate BigWig tracks for genome browsers. It then performs saddle analysis on the binned contact matrices to plot compartment strength visualizations.

Hi-C compartment calling generates visualization-ready outputs including PC1 compartment scores as BigWig tracks for genome browsers and saddle plots. These outputs visualize the A/B compartment separation derived from the PCA analysis.

Genome assembly and resolution are required for Hi-C compartment analysis to properly localize genomic regions and harmonize chromosomal names. These parameters ensure the contact maps are correctly binned and aligned for accurate PCA computation.