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NetActivity

This package is for version 3.19 of Bioconductor; for the stable, up-to-date release version, see NetActivity.

Compute gene set scores from a deep learning framework


Bioconductor version: 3.19

#' 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.

Author: Carlos Ruiz-Arenas [aut, cre]

Maintainer: Carlos Ruiz-Arenas <carlos.ruiza at upf.edu>

Citation (from within R, enter citation("NetActivity")):

Installation

To install this package, start R (version "4.4") and enter:


if (!require("BiocManager", quietly = TRUE))
 install.packages("BiocManager")
BiocManager::install("NetActivity")

For older versions of R, please refer to the appropriate Bioconductor release.

Documentation

To view documentation for the version of this package installed in your system, start R and enter:

browseVignettes("NetActivity")
Gene set scores computation with NetActivity HTML R Script
Reference Manual PDF
NEWS Text
LICENSE Text

Details

Version 1.6.0
In Bioconductor since BioC 3.16 (R-4.2) (2 years)
License MIT + file LICENSE
Depends R (>= 4.1.0)
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Package Archives

Follow Installation instructions to use this package in your R session.

Source Package NetActivity_1.6.0.tar.gz
Windows Binary (x86_64) NetActivity_1.6.0.zip
macOS Binary (x86_64) NetActivity_1.6.0.tgz
macOS Binary (arm64) NetActivity_1.6.0.tgz
Source Repository git clone https://git.bioconductor.org/packages/NetActivity
Source Repository (Developer Access) git clone git@git.bioconductor.org:packages/NetActivity
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