To install this package, start R and enter:

## try http:// if https:// URLs are not supported
source("https://bioconductor.org/biocLite.R")
biocLite("diffHic")

In most cases, you don't need to download the package archive at all.

diffHic

This package is for version 3.4 of Bioconductor; for the stable, up-to-date release version, see diffHic.

Differential Analyis of Hi-C Data

Bioconductor version: 3.4

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 <alun at wehi.edu.au>

Maintainer: Aaron Lun <alun at wehi.edu.au>

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

Installation

To install this package, start R and enter:

## try http:// if https:// URLs are not supported
source("https://bioconductor.org/biocLite.R")
biocLite("diffHic")

Documentation

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

browseVignettes("diffHic")
PDF diffHic Vignette
PDF diffHicUsersGuide.pdf
PDF Reference Manual
Text NEWS

Details

Version 1.6.0
In Bioconductor since BioC 3.1 (R-3.2) (2 years)
License GPL-3
Imports Rsamtools, Rhtslib, Biostrings, BSgenome, rhdf5, edgeR, limma, csaw, locfit, methods, IRanges, S4Vectors, GenomeInfoDb, BiocGenerics, grDevices, graphics, stats, utils
LinkingTo Rhtslib, zlibbioc
SystemRequirements
Enhances
URL
Depends On Me
Imports Me
Suggests Me

Package Archives

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

Package Source diffHic_1.6.0.tar.gz
Windows Binary diffHic_1.6.0.zip (32- & 64-bit)
Mac OS X 10.9 (Mavericks) diffHic_1.6.0.tgz
Package Downloads Report Download Stats

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