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!

Fred Hutchinson Cancer Research Center