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Identifying Differential Effects in Tiling Microarray Data

Bioconductor version: Release (3.19)

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>

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


To install this package, start R (version "4.4") and enter:

if (!require("BiocManager", quietly = TRUE))


For older versions of R, please refer to the appropriate Bioconductor release.


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

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


biocViews ChIPchip, DNAMethylation, DifferentialExpression, Microarray, Software, Transcription
Version 1.54.0
In Bioconductor since BioC 2.7 (R-2.12) (13.5 years)
License GPL-3
Depends R (>= 2.13.2), methods, graphics, fdrtool
Imports boot, gplots, RColorBrewer
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Suggests Biobase, limma
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Enhances parallel
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Follow Installation instructions to use this package in your R session.

Source Package les_1.54.0.tar.gz
Windows Binary
macOS Binary (x86_64) les_1.54.0.tgz
macOS Binary (arm64) les_1.54.0.tgz
Source Repository git clone
Source Repository (Developer Access) git clone
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