To install this package, start R and enter:

source("http://bioconductor.org/biocLite.R")
biocLite("les")

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

les

Identifying Differential Effects in Tiling Microarray Data

Bioconductor version: Release (3.0)

The 'les' package estimates Loci of Enhanced Significance (LES) in tiling microarray data. These are regions of regulation such as found in differential transcription, CHiP-chip, or DNA modification analysis. The package provides a universal framework suitable for identifying differential effects in tiling microarray data sets, and is independent of the underlying statistics at the level of single probes.

Author: Julian Gehring, Clemens Kreutz, Jens Timmer

Maintainer: Julian Gehring <julian.gehring at embl.de>

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

Installation

To install this package, start R and enter:

source("http://bioconductor.org/biocLite.R")
biocLite("les")

Documentation

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

browseVignettes("les")

 

PDF R Script Introduction to the les package: Identifying Differential Effects in Tiling Microarray Data with the Loci of Enhanced Significance Framework
PDF   Reference Manual
Text   NEWS
Text   LICENSE

Details

biocViews ChIPchip, DNAMethylation, DifferentialExpression, Microarray, Software, Transcription
Version 1.16.0
In Bioconductor since BioC 2.7 (R-2.12)
License GPL-3
Depends R (>= 2.13.2), methods, graphics, fdrtool
Imports boot, gplots, RColorBrewer
Suggests Biobase, limma
System Requirements
URL http://julian-gehring.github.com/les/
Depends On Me
Imports Me GSRI
Suggests Me

Package Archives

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

Package Source les_1.16.0.tar.gz
Windows Binary les_1.16.0.zip (32- & 64-bit)
Mac OS X 10.6 (Snow Leopard) les_1.16.0.tgz
Mac OS X 10.9 (Mavericks) les_1.16.0.tgz
Browse/checkout source (username/password: readonly)
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