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multiHiCcompare
This package is for version 3.19 of Bioconductor; for the stable, up-to-date release version, see multiHiCcompare.
Normalize and detect differences between Hi-C datasets when replicates of each experimental condition are available
Bioconductor version: 3.19
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.
Author: Mikhail Dozmorov [aut, cre] , John Stansfield [aut]
Maintainer: Mikhail Dozmorov <mikhail.dozmorov at gmail.com>
citation("multiHiCcompare")):
Installation
To install this package, start R (version "4.4") and enter:
if (!require("BiocManager", quietly = TRUE))
install.packages("BiocManager")
BiocManager::install("multiHiCcompare")
For older versions of R, please refer to the appropriate Bioconductor release.
Documentation
To view documentation for the version of this package installed in your system, start R and enter:
browseVignettes("multiHiCcompare")
Details
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Package Archives
Follow Installation instructions to use this package in your R session.