Abstract
Compartmental organization plays a role in important biological processes. However, its comparative analysis has been mainly limited to pairwise comparisons of contact maps with focus on finding compartment flips (e.g., A-to-B). Here, we introduce dcHiC, which utilizes Multiple Factor Analysis and a multivariate distance measure to systematically identify all compartmentalization differences among multiple contact maps. Evaluating dcHiC on three different collections of Hi-C data, we show its effectiveness and sensitivity in detecting biologically meaningful differences associated with cellular identity, gene expression, and lamin association. By providing a multivariate formulation, dcHiC immediately expands compartment analysis to new modalities in comparative genomics.
Competing Interest Statement
The authors have declared no competing interest.