Package: vsn
Version: 3.78.0
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
Config/pak/sysreqs: zlib1g-dev
Repository: https://bioc-release.r-universe.dev
Date/Publication: 2025-10-29 13:42:11 UTC
RemoteUrl: https://github.com/bioc/vsn
RemoteRef: RELEASE_3_22
RemoteSha: 909160be118baf7e5bde9c83e2bbfd0c3ff451c9
NeedsCompilation: yes
Packaged: 2025-11-11 18:14:46 UTC; root
Built: R 4.5.2; x86_64-w64-mingw32; 2025-11-11 18:18:17 UTC; windows
Archs: x64
