recipe bioconductor-vsn

Variance stabilization and calibration for microarray data







biotools: 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.

package bioconductor-vsn

(downloads) docker_bioconductor-vsn


3.54.0-0, 3.52.0-1, 3.50.0-0, 3.48.1-0, 3.46.0-0, 3.44.0-0, 3.38.0-1

Required By


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

conda install bioconductor-vsn

and update with:

conda update bioconductor-vsn

or use the docker container:

docker pull<tag>

(see bioconductor-vsn/tags for valid values for <tag>)