A supervised learning framework for chromatin loop detection in genome-wide contact maps.
Convert genomic coordinates of contact pairs from one assembly to another.
Predict neo-loops induced by structural variations
A Library to Explore Chromatin Interaction Patterns for Topologically Associating Domains
Identify real loops from Hi-C data.
A deep-learning framework for predicting a full range of structural variations from bulk and single-cell contact maps
A easy-to-use Hi-C processing software supporting distributed computation
A python implementation of original DI-based domain caller proposed by Dixon et al. (2012)
Automated Stripe Identification from contact matrix.
A hierarchical domain caller for Hi-C data based on a modified version of Directionality Index