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This is the development version of diffHic; for the stable release version, see diffHic.

Differential Analysis of Hi-C Data

Bioconductor version: Development (3.20)

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))

# The following initializes usage of Bioc devel


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 1.37.3
In Bioconductor since BioC 3.1 (R-3.2) (9.5 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
Suggests Me
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Follow Installation instructions to use this package in your R session.

Source Package diffHic_1.37.3.tar.gz
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macOS Binary (x86_64) diffHic_1.37.3.tgz
macOS Binary (arm64) diffHic_1.37.3.tgz
Source Repository git clone
Source Repository (Developer Access) git clone
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