recipe bioconductor-netactivity

Compute gene set scores from a deep learning framework

Homepage:

https://bioconductor.org/packages/3.16/bioc/html/NetActivity.html

License:

MIT + file LICENSE

Recipe:

/bioconductor-netactivity/meta.yaml

#' NetActivity enables to compute gene set scores from previously trained sparsely-connected autoencoders. The package contains a function to prepare the data (`prepareSummarizedExperiment`) and a function to compute the gene set scores (`computeGeneSetScores`). The package `NetActivityData` contains different pre-trained models to be directly applied to the data. Alternatively, the users might use the package to compute gene set scores using custom models.

package bioconductor-netactivity

(downloads) docker_bioconductor-netactivity

Versions:

1.0.0-0

Depends:
Required By:

Installation

With an activated Bioconda channel (see set-up-channels), install with:

conda install bioconductor-netactivity

and update with:

conda update bioconductor-netactivity

or use the docker container:

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

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

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