recipe bioconductor-nnnorm

Spatial and intensity based normalization of cDNA microarray data based on robust neural nets

Homepage:

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

License:

LGPL

Recipe:

/bioconductor-nnnorm/meta.yaml

Links:

biotools: nnnorm, doi: 10.1093/bioinformatics/bti397

This package allows to detect and correct for spatial and intensity biases with two-channel microarray data. The normalization method implemented in this package is based on robust neural networks fitting.

package bioconductor-nnnorm

(downloads) docker_bioconductor-nnnorm

Versions:
2.74.0-0,  2.70.0-0,  2.66.0-0,  2.64.0-0,  2.62.0-0,  2.58.0-0,  2.56.0-0,  2.54.0-1,  2.54.0-0, 

2.74.0-0,  2.70.0-0,  2.66.0-0,  2.64.0-0,  2.62.0-0,  2.58.0-0,  2.56.0-0,  2.54.0-1,  2.54.0-0,  2.52.0-0,  2.50.0-0,  2.48.0-1,  2.48.0-0,  2.46.0-0,  2.44.0-0,  2.42.0-0,  2.40.0-0

Depends:

  • on bioconductor-marray >=1.88.0,<1.89.0

  • on r-base >=4.5,<4.6.0a0

  • on r-nnet

Additional platforms:

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-nnnorm

to add into an existing workspace instead, run:

pixi add bioconductor-nnnorm

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-nnnorm

Alternatively, to install into a new environment, run:

conda create -n envname bioconductor-nnnorm

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-nnnorm:<tag>

(see bioconductor-nnnorm/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.

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