iChip

DOI: 10.18129/B9.bioc.iChip    

Bayesian Modeling of ChIP-chip Data Through Hidden Ising Models

Bioconductor version: Release (3.8)

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>

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

Installation

To install this package, start R and enter:

if (!requireNamespace("BiocManager", quietly = TRUE))
    install.packages("BiocManager")
BiocManager::install("iChip", version = "3.8")

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 1.36.0
In Bioconductor since BioC 2.6 (R-2.11) (8.5 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_1.36.0.tar.gz
Windows Binary iChip_1.36.0.zip (32- & 64-bit)
Mac OS X 10.11 (El Capitan) iChip_1.36.0.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 http://bioconductor.org/packages/iChip/
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