recipe 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.

Homepage

https://bioconductor.org/packages/3.9/bioc/html/vsn.html

License

Artistic-2.0

Recipe

/bioconductor-vsn/meta.yaml

Links

biotools: vsn

package bioconductor-vsn

(downloads) docker_bioconductor-vsn

Versions

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

Depends bioconductor-affy

>=1.60.0,<1.61.0

Depends bioconductor-biobase

>=2.42.0,<2.43.0

Depends bioconductor-limma

>=3.38.0,<3.39.0

Depends libgcc-ng

>=7.3.0

Depends r-base

>=3.5.1,<3.5.2.0a0

Depends r-ggplot2

Depends r-lattice

Requirements

Installation

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 quay.io/biocontainers/bioconductor-vsn:<tag>

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