Package: NetActivity
Type: Package
Title: Compute gene set scores from a deep learning framework
Version: 1.12.0
Authors@R: c(person("Carlos", "Ruiz-Arenas", , "carlos.ruiza@upf.edu", role = c("aut", "cre")))
Description: #' 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.
License: MIT + file LICENSE
Encoding: UTF-8
Depends: R (>= 4.1.0)
Suggests: AnnotationDbi, BiocStyle, Fletcher2013a, knitr, org.Hs.eg.db,
        rmarkdown, testthat (>= 3.0.0), tidyverse
Config/testthat/edition: 3
biocViews: RNASeq, Microarray, Transcription, FunctionalGenomics, GO,
        GeneExpression, Pathways, Software
RoxygenNote: 7.2.1
Imports: airway, DelayedArray, DelayedMatrixStats, DESeq2, methods,
        methods, NetActivityData, SummarizedExperiment, utils
VignetteBuilder: knitr
git_url: https://git.bioconductor.org/packages/NetActivity
git_branch: RELEASE_3_22
git_last_commit: 2ba9ebf
git_last_commit_date: 2025-10-29
Repository: Bioconductor 3.22
Date/Publication: 2025-10-29
NeedsCompilation: no
Packaged: 2025-10-30 05:24:59 UTC; biocbuild
Author: Carlos Ruiz-Arenas [aut, cre]
Maintainer: Carlos Ruiz-Arenas <carlos.ruiza@upf.edu>
