DESCRIPTION

Package: NetActivity
Type: Package
Title: Compute gene set scores from a deep learning framework
Version: 1.1.1
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
LazyData: false
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