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vsn

Variance stabilization and calibration for microarray data.

vsn implements a method for normalising single- and multiple-color microarray intensities (and, in principle, data from other technologies with a similar format). 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.

Installation

vsn is part of Bioconductor:

if (!requireNamespace("BiocManager", quietly = TRUE))
    install.packages("BiocManager")
BiocManager::install("vsn")

Usage

The simplest way to normalize a dataset is:

data("kidney")          # ExpressionSet of unnormalised data
xnorm <- justvsn(kidney)
xnorm
#> ExpressionSet (storageMode: lockedEnvironment)
#> assayData: 8704 features, 2 samples 
#>   element names: exprs 
#> protocolData: none
#> phenoData
#>   sampleNames: green red
#>   varLabels: channel
#>   varMetadata: labelDescription
#> featureData: none
#> experimentData: use 'experimentData(object)'
#> Annotation:

For more control, fit the model and apply it in two steps:

fit <- vsn2(kidney)
ynorm <- predict(fit, kidney)
ynorm
#> ExpressionSet (storageMode: lockedEnvironment)
#> assayData: 8704 features, 2 samples 
#>   element names: exprs 
#> protocolData: none
#> phenoData
#>   sampleNames: green red
#>   varLabels: channel
#>   varMetadata: labelDescription
#> featureData: none
#> experimentData: use 'experimentData(object)'
#> Annotation:

Both are equivalent. The two-step form is useful when fitting on a subset (e.g. spike-in or control features) and then applying the fit to the full data, or when you want to inspect the fit object. justvsn() and vsn2() are also available for AffyBatch and RGList objects.

References 

citation(package = "vsn")
#> To cite the vsn package in publications use:
#> 
#>   Huber W, von Heydebreck A, Sueltmann H, Poustka A, Vingron M (2002).
#>   "Variance Stabilization Applied to Microarray Data Calibration and to
#>   the Quantification of Differential Expression." _Bioinformatics_, *18
#>   Suppl. 1*, S96-S104. doi:10.1093/bioinformatics/18.suppl_1.s96
#>   <https://doi.org/10.1093/bioinformatics/18.suppl_1.s96>.
#> 
#> A BibTeX entry for LaTeX users is
#> 
#>   @Article{,
#>     title = {Variance Stabilization Applied to Microarray Data Calibration and to the Quantification of Differential Expression},
#>     author = {Wolfgang Huber and Anja {von Heydebreck} and Holger Sueltmann and Annemarie Poustka and Martin Vingron},
#>     doi = {10.1093/bioinformatics/18.suppl_1.s96},
#>     journal = {Bioinformatics},
#>     year = {2002},
#>     volume = {18 Suppl. 1},
#>     pages = {S96-S104},
#>   }

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