- 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:
#' 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¶
-
- Versions:
1.0.0-0
- Depends:
bioconductor-airway
>=1.18.0,<1.19.0
bioconductor-delayedarray
>=0.24.0,<0.25.0
bioconductor-delayedmatrixstats
>=1.20.0,<1.21.0
bioconductor-deseq2
>=1.38.0,<1.39.0
bioconductor-netactivitydata
>=1.0.0,<1.1.0
bioconductor-summarizedexperiment
>=1.28.0,<1.29.0
r-base
>=4.2,<4.3.0a0
- 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>
)
Download stats¶
Link to this page¶
Render an badge with the following MarkDown:
[](http://bioconda.github.io/recipes/bioconductor-netactivity/README.html)