les
Identifying Differential Effects in Tiling Microarray Data
Bioconductor version: 2.9
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
| R Script | Introduction to the les package: Identifying Differential Effects in Tiling Microarray Data with the Loci of Enhanced Significance Framework | |
| Reference Manual | ||
| Text | NEWS |
Details
| biocViews | Microarray, Bioinformatics, DifferentialExpression, ChIPchip, DNAMethylation, 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 | 1.4.0 |
| Since | Bioconductor 2.7 (R-2.12) |
Package Downloads
| Package Source | les_1.4.0.tar.gz |
| Windows Binary | les_1.4.0.zip (32- & 64-bit) |
| MacOS 10.5 (Leopard) binary | les_1.4.0.tgz |
| Package Downloads Report | Download Stats |
Common Bioconductor workflows include:
- Oligonucleotide Arrays
- High-throughput Sequencing
- Annotation
- Variants
- Flow Cytometry and other assays
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