@article {678960,
	title = {dcHiC: Differential Compartment Analysis of Hi-C Data},
	year = {Submitted},
	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\&nbsp;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.

},
	author = {Jeffrey Wang and Abhijit Chakraborty and Ay, Ferhat}
}
