To install this package, start R and enter:
## try http:// if https:// URLs are not supported
source("https://bioconductor.org/biocLite.R")
biocLite("les")
In most cases, you don't need to download the package archive at all.
les
|
This package is for version 2.10 of Bioconductor; for the stable, up-to-date release version, see 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>
Citation (from within R,
enter citation("les")):
Installation
To install this package, start R and enter:
## try http:// if https:// URLs are not supported
source("https://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")
| Introduction to the les package: Identifying Differential Effects in Tiling Microarray Data with the Loci of Enhanced Significance Framework | ||
| Reference Manual | ||
| Text | NEWS | |
| Text | LICENSE |
Details
| biocViews | Bioinformatics, ChIPchip, DNAMethylation, DifferentialExpression, Microarray, Software, Transcription |
| Version | 1.6.0 |
| In Bioconductor since | BioC 2.7 (R-2.12) (5.5 years) |
| License | GPL-3 |
| Depends | R (>= 2.13.2), methods, graphics, fdrtool |
| Imports | boot, gplots, RColorBrewer |
| LinkingTo | |
| Suggests | Biobase, limma |
| SystemRequirements | |
| Enhances | multicore |
| URL | http://julian-gehring.github.com/les/ |
| Depends On Me | |
| Imports Me | GSRI |
| Suggests Me | |
| Build Report |
Package Archives
Follow Installation instructions to use this package in your R session.
| Package Source | les_1.6.0.tar.gz |
| Windows Binary | les_1.6.0.zip |
| Mac OS X 10.6 (Snow Leopard) | |
| Subversion source | (username/password: readonly) |
| Git source | https://github.com/Bioconductor-mirror/les/tree/release-2.10 |
| Package Short Url | http://bioconductor.org/packages/les/ |
| Package Downloads Report | Download Stats |
Documentation »
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