dozmorovlab/multHiCcompare: Normalize and detect differences between Hi-C datasets when replicates of each experimental condition are available

multiHiCcompare provides functions for joint normalization and difference detection in multiple Hi-C datasets. This extension of the original HiCcompare package now allows for Hi-C experiments with more than 2 groups and multiple samples per group. multiHiCcompare operates on processed Hi-C data in the form of sparse upper triangular matrices. It accepts four column (chromosome, region1, region2, IF) tab-separated text files storing chromatin interaction matrices. multiHiCcompare provides cyclic loess and fast loess (fastlo) methods adapted to jointly normalizing Hi-C data. Additionally, it provides a general linear model (GLM) framework adapting the edgeR package to detect differences in Hi-C data in a distance dependent manner.

Getting started

Package details

AuthorJohn Stansfield <>, Mikhail Dozmorov <>
Bioconductor views HiC Normalization Sequencing Software
MaintainerJohn Stansfield <>, Mikhail Dozmorov <>
LicenseMIT + file LICENSE
Package repositoryView on GitHub
Installation Install the latest version of this package by entering the following in R:
dozmorovlab/multHiCcompare documentation built on April 30, 2022, 3:02 p.m.