Package: vsn Version: 3.46.0 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 Depends: R (>= 3.4.0), Biobase Imports: methods, affy, limma, lattice, ggplot2 Suggests: affydata, hgu95av2cdf, BiocStyle, knitr, dplyr, testthat Description: The package implements a method for normalising microarray intensities, and works for 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 NeedsCompilation: yes Packaged: 2017-10-30 22:38:01 UTC; biocbuild Built: R 3.4.1; i686-pc-linux-gnu; 2018-01-19 22:40:34 UTC; unix