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

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 ar...

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Bibliographic Details
Published in:Bioinformatics (Oxford, England) England), 2017-07, Vol.33 (14), p.2199-2201
Main Authors: Yan, Koon-Kiu, Yardimci, Galip Gürkan, Yan, Chengfei, Noble, William S, Gerstein, Mark
Format: Article
Language:English
Subjects:
Applications Notes
Biotinylation
Chromosomes - chemistry
DNA - chemistry
Gene Library
Genetic Techniques
Genome
Humans
Reproducibility of Results
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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. Source code in Julia and Python, and detailed documentation is available at https://github.com/gersteinlab/HiC-spector . koonkiu.yan@gmail.com or mark@gersteinlab.org. Supplementary data are available at Bioinformatics online.
ISSN:1367-4803
1367-4811
DOI:10.1093/bioinformatics/btx152