Package: vsn
Version: 3.72.0
Title: Variance stabilization and calibration for microarray data
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 <wolfgang.huber@embl.org>
Depends: R (>= 4.0.0), methods, Biobase
Imports: affy, limma, lattice, ggplot2
Suggests: affydata, hgu95av2cdf, BiocStyle, knitr, rmarkdown, dplyr,
        testthat
Description: The package implements a method for normalising microarray intensities from single- and 
        multiple-color arrays. It can also be used
	for data from other technologies, as long as they have similar format. The method uses a
	robust variant of the maximum-likelihood estimator for an additive-multiplicative error
	model and affine calibration. The model incorporates data calibration step (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.
Reference: [1] Variance stabilization applied to microarray data
        calibration and to the quantification of differential
        expression, Wolfgang Huber, Anja von Heydebreck, Holger
        Sueltmann, Annemarie Poustka, Martin Vingron; Bioinformatics
        (2002) 18 Suppl1 S96-S104. [2] Parameter estimation for the
        calibration and variance stabilization of microarray data,
        Wolfgang Huber, Anja von Heydebreck, Holger Sueltmann,
        Annemarie Poustka, and Martin Vingron; Statistical Applications
        in Genetics and Molecular Biology (2003) Vol. 2 No. 1, Article
        3; http://www.bepress.com/sagmb/vol2/iss1/art3.
License: Artistic-2.0
URL: http://www.r-project.org, http://www.ebi.ac.uk/huber
biocViews: Microarray, OneChannel, TwoChannel, Preprocessing
VignetteBuilder: knitr
Collate: AllClasses.R AllGenerics.R vsn2.R vsnLogLik.R justvsn.R
        methods-vsnInput.R methods-vsn.R methods-vsn2.R
        methods-predict.R RGList_to_NChannelSet.R meanSdPlot-methods.R
        plotLikelihood.R normalize.AffyBatch.vsn.R sagmbSimulateData.R
        zzz.R
git_url: https://git.bioconductor.org/packages/vsn
git_branch: RELEASE_3_19
git_last_commit: c91b4c6
git_last_commit_date: 2024-04-30
Repository: Bioconductor 3.19
Date/Publication: 2024-05-01
NeedsCompilation: yes
Packaged: 2024-05-02 02:34:29 UTC; biocbuild
Built: R 4.4.0; x86_64-w64-mingw32; 2024-05-02 13:42:11 UTC; windows
Archs: x64
