Summary: Genome-wide proximity ligation based assays like Hi-C have opened a window to the 3D organization of the genome. In so doing, they present data structures that are different from conventional 1D signal tracks. To exploit the 2D nature of Hi-C contact maps, matrix techniques like spectral analysis are particularly useful. Here, we present HiC-spector, a collection of matrix-related functions for analyzing Hi-C contact maps. In particular, we introduce a novel reproducibility metric for quantifying the similarity between contact maps based on spectral decomposition. The metric successfully separates contact maps mapped from Hi-C data coming from biological replicates, pseudo-replicates and different cell types.
Availability and implementation: Source code in Julia and Python, and detailed documentation is available at https://github.com/gersteinlab/HiC-spector .
Contact: koonkiu.yan@gmail.com or mark@gersteinlab.org.
Supplementary information: Supplementary data are available at Bioinformatics online.
© The Author(s) 2017. Published by Oxford University Press.