This is the development version of NetActivity; for the stable release version, see NetActivity.
Compute gene set scores from a deep learning frameworkBioconductor version: Development (3.22)
#' 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, entercitation("NetActivity")
): Installation
To install this package, start R (version "4.5") and enter:
if (!require("BiocManager", quietly = TRUE))
install.packages("BiocManager")
# The following initializes usage of Bioc devel
BiocManager::install(version='devel')
BiocManager::install("NetActivity")
For older versions of R, please refer to the appropriate Bioconductor release.
DocumentationTo view documentation for the version of this package installed in your system, start R and enter:
browseVignettes("NetActivity")
Details biocViews FunctionalGenomics, GO, GeneExpression, Microarray, Pathways, RNASeq, Software, Transcription Version 1.11.0 In Bioconductor since BioC 3.16 (R-4.2) (2.5 years) License MIT + file LICENSE Depends R (>= 4.1.0) Imports airway, DelayedArray, DelayedMatrixStats, DESeq2, methods, methods, NetActivityData, SummarizedExperiment, utils System Requirements URL See More Package Archives
Follow Installation instructions to use this package in your R session.
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