HiC-spector: a matrix library for spectral and reproducibility analysis of Hi-C contact maps

Abstract

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.

Fig. 1

Reproducibility scores for three sets of Hi-C contact maps pairs. Contact maps came from Hi-C experiments performed in 11 cell lines. Biological replicates refer to a pair of replicates of the same experiment. Pseudo replicates are obtained by pooling the reads from two replicates together performing down sampling. There are 11 biological replicates, 33 pairs of pseudo replicates, and 110 pairs of maps between different cell types. Each box shows for a pair the distribution of Q in 23 chromosomes, with crosses as the outliers