Nature Communications
Nature Communications
5 years ago

An integrated model for detecting significant chromatin interactions from high-resolution Hi-C data

An integrated model for detecting significant chromatin interactions from high-resolution Hi-C data
Lee Zamparo, Merve Sahin, Olivier Elemento, Mark Carty, Alvaro González, Raphael Pelossof, Christina S. Leslie
Here we present HiC-DC, a principled method to estimate the statistical significance (P values) of chromatin interactions from Hi-C experiments. HiC-DC uses hurdle negative binomial regression account for systematic sources of variation in Hi-C read counts—for example, distance-dependent random polymer ligation and GC content and mappability bias—and model zero inflation and overdispersion. Applied to high-resolution Hi-C data in a lymphoblastoid cell line, HiC-DC detects significant interactions at the sub-topologically associating domain level, identifying potential structural and regulatory interactions supported by CTCF binding sites, DNase accessibility, and/or active histone marks. CTCF-associated interactions are most strongly enriched in the middle genomic distance range (∼700 kb–1.5 Mb), while interactions involving actively marked DNase accessible elements are enriched both at short (<500 kb) and longer (>1.5 Mb) genomic distances. There is a striking enrichment of longer-range interactions connecting replication-dependent histone genes on chromosome 6, potentially representing the chromatin architecture at the histone locus body.

Publisher URL: http://www.nature.com/articles/ncomms15454

DOI: 10.1038/ncomms15454

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