Bioconductor version: 2.10
The package implements a method for normalising microarray intensities, both between colours within array, and between arrays. The method uses a robust variant of the maximum-likelihood estimator for the stochastic model of microarray data described in the references (see vignette). The model incorporates data calibration (a.k.a. normalization), a model for the dependence of the variance on the mean intensity, and a variance stabilizing data transformation. Differences between transformed intensities are analogous to "normalized log-ratios". However, in contrast to the latter, their variance is independent of the mean, and they are usually more sensitive and specific in detecting differential transcription.
Author: Wolfgang Huber, with contributions from Anja von Heydebreck. Many comments and suggestions by users are acknowledged, among them Dennis Kostka, David Kreil, Hans-Ulrich Klein, Robert Gentleman, Deepayan Sarkar and Gordon Smyth.
Maintainer: Wolfgang Huber <huber at ebi.ac.uk>
To install this package, start R and enter:
source("http://bioconductor.org/biocLite.R") biocLite("vsn")
To cite this package in a publication, start R and enter:
citation("vsn")
R Script | Introduction to vsn | |
R Script | Likelihood Calculations for vsn | |
R Script | Verifying and assessing the performance with simulated data | |
Reference Manual |
biocViews | Microarray, OneChannel, Preprocessing, Software, TwoChannel |
Depends | R (>= 2.10), Biobase(>= 2.5.5) |
Imports | methods, affy(>= 1.23.4), limma, lattice |
Suggests | affydata, hgu95av2cdf |
System Requirements | |
License | Artistic-2.0 |
URL | http://www.r-project.org, http://www.ebi.ac.uk/huber |
Depends On Me | affyPara, cellHTS2, LVSmiRNA, MmPalateMiRNA, webbioc |
Imports Me | arrayQualityMetrics, imageHTS, MSnbase, Ringo, tilingArray |
Suggests Me | adSplit, Agi4x44PreProcess, beadarray, BiocCaseStudies, cellHTS, DESeq, estrogen, GlobalAncova, globaltest, limma, lumi, twilight |
Version | 3.24.0 |
Since | Bioconductor 1.6 (R-2.1) or earlier |
Package Source | vsn_3.24.0.tar.gz |
Windows Binary | vsn_3.24.0.zip (32- & 64-bit) |
MacOS 10.5 (Leopard) binary | vsn_3.24.0.tgz |
Package Downloads Report | Download Stats |
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