recipe bioconductor-vsn

Variance stabilization and calibration for microarray data

Homepage:

https://bioconductor.org/packages/3.20/bioc/html/vsn.html

License:

Artistic-2.0

Recipe:

/bioconductor-vsn/meta.yaml

Links:

biotools: vsn

The package implements a method for normalising microarray intensities from 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

versions:

3.74.0-1,  3.74.0-0,  3.70.0-1,  3.70.0-0,  3.68.0-0,  3.66.0-1,  3.66.0-0,  3.62.0-2,  3.62.0-1, 

3.74.0-1,  3.74.0-0,  3.70.0-1,  3.70.0-0,  3.68.0-0,  3.66.0-1,  3.66.0-0,  3.62.0-2,  3.62.0-1,  3.62.0-0,  3.60.0-0,  3.58.0-1,  3.58.0-0,  3.56.0-0,  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

depends bioconductor-affy:

>=1.84.0,<1.85.0

depends bioconductor-affy:

>=1.84.0,<1.85.0a0

depends bioconductor-biobase:

>=2.66.0,<2.67.0

depends bioconductor-biobase:

>=2.66.0,<2.67.0a0

depends bioconductor-limma:

>=3.62.0,<3.63.0

depends bioconductor-limma:

>=3.62.1,<3.63.0a0

depends libblas:

>=3.9.0,<4.0a0

depends libgcc:

>=13

depends liblapack:

>=3.9.0,<4.0a0

depends r-base:

>=4.4,<4.5.0a0

depends r-ggplot2:

depends r-lattice:

requirements:

additional platforms:

linux-aarch64,  osx-arm64

Installation

You need a conda-compatible package manager (currently either micromamba, mamba, or conda) and the Bioconda channel already activated (see set-up-channels).

While any of above package managers is fine, it is currently recommended to use either micromamba or mamba (see here for installation instructions). We will show all commands using mamba below, but the arguments are the same for the two others.

Given that you already have a conda environment in which you want to have this package, install with:

   mamba install bioconductor-vsn

and update with::

   mamba update bioconductor-vsn

To create a new environment, run:

mamba create --name myenvname bioconductor-vsn

with myenvname being a reasonable name for the environment (see e.g. the mamba docs for details and further options).

Alternatively, use the docker container:

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

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

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