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

DOI: 10.18129/B9.bioc.les

Identifying Differential Effects in Tiling Microarray Data

Bioconductor version: Release (3.5)

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 <jg-bioc at gmx.com>

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")

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