# bioconductor-vsn¶

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.

 Home http://bioconductor.org/packages/3.6/bioc/html/vsn.html Versions 3.38.0, 3.44.0, 3.46.0 License Artistic-2.0 Recipe https://github.com/bioconda/bioconda-recipes/tree/master/recipes/bioconductor-vsn

## Installation¶

With an activated Bioconda channel (see 2. Set up channels), install with:

conda install bioconductor-vsn


and update with:

conda update bioconductor-vsn


A Docker container is available at https://quay.io/repository/biocontainers/bioconductor-vsn.