les

Identifying Differential Effects in Tiling Microarray Data

Bioconductor version: 2.10

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>

To install this package, start R and enter:

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

To cite this package in a publication, start R and enter:

    citation("les")

Documentation

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	Bioinformatics, ChIPchip, DNAMethylation, DifferentialExpression, Microarray, Software, Transcription
Depends	R (>= 2.13.2), methods, graphics, fdrtool
Imports	boot, gplots, RColorBrewer
Suggests	Biobase, limma
System Requirements
License	GPL-3
URL	http://julian-gehring.github.com/les/
Depends On Me
Imports Me	GSRI
Suggests Me
Version	1.6.0
Since	Bioconductor 2.7 (R-2.12)

Package Downloads

Package Source	les_1.6.0.tar.gz
Windows Binary	les_1.6.0.zip (32- & 64-bit)
MacOS 10.5 (Leopard) binary	les_1.6.0.tgz
Package Downloads Report	Download Stats

Workflows »

Common Bioconductor workflows include:

Mailing Lists »

Post questions about Bioconductor packages to our mailing lists. Read the posting guide before posting!

Hosting provided by Fred Hutchinson Cancer Research Center