Package Recipe 'bioconductor-vsn'

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:

3.78.1-0, 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,

3.78.1-0, 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:

on bioconductor-affy >=1.88.0,<1.89.0
on bioconductor-affy >=1.88.0,<1.89.0a0
on bioconductor-biobase >=2.70.0,<2.71.0
on bioconductor-biobase >=2.70.0,<2.71.0a0
on bioconductor-limma >=3.66.0,<3.67.0
on bioconductor-limma >=3.66.0,<3.67.0a0
on libblas >=3.9.0,<4.0a0
on libgcc >=14
on liblapack >=3.9.0,<4.0a0
on liblzma >=5.8.2,<6.0a0
on libzlib >=1.3.1,<2.0a0
on r-base >=4.5,<4.6.0a0
on r-ggplot2
on r-lattice

Additional platforms:

linux-aarch64, osx-arm64

Installation¶

You need a conda-compatible package manager (currently either pixi, conda, or micromamba) and the Bioconda channel already activated (see Usage). Below, we show how to install with either pixi or conda (for micromamba and mamba, commands are essentially the same as with conda).

Pixi¶

With pixi installed and the Bioconda channel set up (see Usage), to install globally, run:

pixi global install bioconductor-vsn

to add into an existing workspace instead, run:

pixi add bioconductor-vsn

In the latter case, make sure to first add bioconda and conda-forge to the channels considered by the workspace:

pixi workspace channel add conda-forge
pixi workspace channel add bioconda

Conda¶

With conda installed and the Bioconda channel set up (see Usage), to install into an existing and activated environment, run:

conda install bioconductor-vsn

Alternatively, to install into a new environment, run:

conda create -n envname bioconductor-vsn

with envname being the name of the desired environment.

Container¶

Alternatively, every Bioconda package is available as a container image for usage with your preferred container runtime. For e.g. docker, run:

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

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

Integrated deployment¶

Finally, note that many scientific workflow management systems directly integrate both conda and container based software deployment. Thus, workflow steps can be often directly annotated to use the package, leading to automatic deployment by the respective workflow management system, thereby improving reproducibility and transparency. Check the documentation of your workflow management system to find out about the integration.

Download stats¶

Link to this page¶

Render an badge with the following MarkDown:

[![install with bioconda](https://img.shields.io/badge/install%20with-bioconda-brightgreen.svg?style=flat)](http://bioconda.github.io/recipes/bioconductor-vsn/README.html)