hicrep: Measuring the reproducibility of Hi-C data

Hi-C is a powerful technology for studying genome-wide chromatin interactions. However, current methods for assessing Hi-C data reproducibility can produce misleading results because they ignore spatial features in Hi-C data, such as domain structure and distance-dependence. We present a novel reproducibility measure that systematically takes these features into consideration. This measure can assess pairwise differences between Hi-C matrices under a wide range of settings, and can be used to determine optimal sequencing depth. Compared to existing approaches, it consistently shows higher accuracy in distinguishing subtle differences in reproducibility and depicting interrelationships of cell lineages than existing approaches. This R package `hicrep` implements our approach.

Package details

AuthorTao Yang [aut, cre]
Bioconductor views HiC QualityControl Sequencing
MaintainerTao Yang <xadmyangt@gmail.com>
LicenseGPL (>= 2.0)
Package repositoryView on Bioconductor
Installation Install the latest version of this package by entering the following in R:
if (!requireNamespace("BiocManager", quietly = TRUE))


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hicrep documentation built on April 28, 2020, 7:51 p.m.