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Differential Analysis of Hi-C Data

Bioconductor version: Release (3.19)

Detects differential interactions across biological conditions in a Hi-C experiment. Methods are provided for read alignment and data pre-processing into interaction counts. Statistical analysis is based on edgeR and supports normalization and filtering. Several visualization options are also available.

Author: Aaron Lun, Gordon Smyth

Maintainer: Aaron Lun <infinite.monkeys.with.keyboards at>, Gordon Smyth <smyth at>, Hannah Coughlin <coughlin.h at>

Citation (from within R, enter citation("diffHic")):


To install this package, start R (version "4.4") and enter:

if (!require("BiocManager", quietly = TRUE))


For older versions of R, please refer to the appropriate Bioconductor release.


To view documentation for the version of this package installed in your system, start R and enter:

diffHic Vignette PDF
diffHicUsersGuide.pdf PDF
Reference Manual PDF


biocViews Alignment, Clustering, Coverage, HiC, MultipleComparison, Normalization, Preprocessing, Sequencing, Software
Version 1.36.1
In Bioconductor since BioC 3.1 (R-3.2) (9 years)
License GPL-3
Depends R (>= 3.5), GenomicRanges, InteractionSet, SummarizedExperiment
Imports Rsamtools, Rhtslib, Biostrings, BSgenome, rhdf5, edgeR, limma, csaw, locfit, methods, IRanges, S4Vectors, GenomeInfoDb, BiocGenerics, grDevices, graphics, stats, utils, Rcpp, rtracklayer
System Requirements C++, GNU make
See More
Suggests BSgenome.Ecoli.NCBI.20080805, Matrix, testthat
Linking To Rhtslib(>= 1.13.1), zlibbioc, Rcpp
Depends On Me
Imports Me OHCA
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Package Archives

Follow Installation instructions to use this package in your R session.

Source Package diffHic_1.36.1.tar.gz
Windows Binary (64-bit only)
macOS Binary (x86_64) diffHic_1.36.1.tgz
macOS Binary (arm64) diffHic_1.36.1.tgz
Source Repository git clone
Source Repository (Developer Access) git clone
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Old Source Packages for BioC 3.19 Source Archive