iChip

DOI: 10.18129/B9.bioc.iChip    

Bayesian Modeling of ChIP-chip Data Through Hidden Ising Models

Bioconductor version: Release (3.13)

Hidden Ising models are implemented to identify enriched genomic regions in ChIP-chip data. They can be used to analyze the data from multiple platforms (e.g., Affymetrix, Agilent, and NimbleGen), and the data with single to multiple replicates.

Author: Qianxing Mo

Maintainer: Qianxing Mo <qianxing.mo at moffitt.org>

Installation

To install this package, start R (version "4.1") and enter:

if (!requireNamespace("BiocManager", quietly = TRUE))
    install.packages("BiocManager")

BiocManager::install("iChip")

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("iChip")

 

PDF	R Script	iChip
PDF		Reference Manual

Details

biocViews	AgilentChip, ChIPchip, Microarray, OneChannel, Software
Version	1.46.0
In Bioconductor since	BioC 2.6 (R-2.11) (11.5 years)
License	GPL (>= 2)
Depends	R (>= 2.10.0)
Imports	limma
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Package Archives

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

Source Package	iChip_1.46.0.tar.gz
Windows Binary	iChip_1.46.0.zip (32- & 64-bit)
macOS 10.13 (High Sierra)	iChip_1.46.0.tgz
Source Repository	git clone https://git.bioconductor.org/packages/iChip
Source Repository (Developer Access)	git clone git@git.bioconductor.org:packages/iChip
Package Short Url	https://bioconductor.org/packages/iChip/
Package Downloads Report	Download Stats