vsn: Variance stabilization and calibration for microarray data

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.

AuthorWolfgang 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
Date of publicationNone
MaintainerWolfgang Huber <whuber@embl.de>
LicenseArtistic-2.0
Version3.42.3
http://www.r-project.org
http://www.ebi.ac.uk/huber

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Files in this package

vsn/.Rinstignore
vsn/DESCRIPTION
vsn/NAMESPACE
vsn/R
vsn/R/AllClasses.R vsn/R/AllGenerics.R vsn/R/RGList_to_NChannelSet.R vsn/R/getIntensityMatrix.R vsn/R/justvsn.R vsn/R/meanSdPlot-methods.R vsn/R/methods-predict.R vsn/R/methods-vsn.R vsn/R/methods-vsn2.R vsn/R/methods-vsnInput.R vsn/R/normalize.AffyBatch.vsn.R vsn/R/plotLikelihood.R vsn/R/sagmbSimulateData.R vsn/R/vsn.R vsn/R/vsn2.R vsn/R/vsnLogLik.R vsn/R/vsnPlotPar.R vsn/R/vsnh.R vsn/R/zzz.R
vsn/build
vsn/build/vignette.rds
vsn/data
vsn/data/kidney.RData
vsn/data/lymphoma.RData
vsn/inst
vsn/inst/CITATION
vsn/inst/doc
vsn/inst/doc/A-vsn.R
vsn/inst/doc/A-vsn.Rnw
vsn/inst/doc/A-vsn.pdf
vsn/inst/doc/C-likelihoodcomputations.R
vsn/inst/doc/C-likelihoodcomputations.Rnw
vsn/inst/doc/C-likelihoodcomputations.pdf
vsn/inst/doc/D-convergence.Rnw
vsn/inst/doc/D-convergence.pdf
vsn/inst/doc/vsn.R
vsn/inst/doc/vsn.Rmd
vsn/inst/doc/vsn.html
vsn/inst/scripts
vsn/inst/scripts/README
vsn/inst/scripts/convergence.Rnw
vsn/inst/scripts/lymphomasamples.txt
vsn/inst/scripts/makedata.R
vsn/inst/scripts/swirl.R
vsn/inst/scripts/testderiv.R
vsn/inst/scripts/testmlest.R
vsn/inst/scripts/testprofiling.R
vsn/inst/vignettes
vsn/inst/vignettes/4-convergence.Rnw
vsn/inst/vignettes/4-convergence.pdf
vsn/man
vsn/man/class.vsn.Rd vsn/man/class.vsnInput.Rd vsn/man/justvsn.Rd vsn/man/kidney.Rd vsn/man/lymphoma.Rd vsn/man/meanSdPlot.Rd vsn/man/normalize.AffyBatch.vsn.Rd vsn/man/sagmbSimulateData.Rd vsn/man/scalingFactorTransformation.Rd vsn/man/vsn-package.Rd vsn/man/vsn.Rd vsn/man/vsn2.Rd vsn/man/vsn2trsf.Rd vsn/man/vsnLikelihood.Rd vsn/man/vsnPlotPar.Rd vsn/man/vsnh.Rd
vsn/src
vsn/src/init.c
vsn/src/vsn.c
vsn/src/vsn.h
vsn/src/vsn2.c
vsn/vignettes
vsn/vignettes/A-vsn.Rnw
vsn/vignettes/C-likelihoodcomputations.Rnw
vsn/vignettes/D-convergence.Rnw
vsn/vignettes/vsn.Rmd
vsn/vignettes/vsn.bib

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