Package: GSVA
Version: 2.4.1
Title: Gene Set Variation Analysis for Microarray and RNA-Seq Data
Authors@R: c(person("Robert", "Castelo", role=c("aut", "cre"), email="robert.castelo@upf.edu"),
             person("Justin", "Guinney", role="aut", email="jguinney@gmail.com"),
             person("Alexey", "Sergushichev", role="ctb", email="alsergbox@gmail.com"),
             person("Pablo Sebastian", "Rodriguez", role="ctb", email="pablo.rodriguez.bio2@gmail.com"),
             person("Axel", "Klenk", role="ctb", email="axelvolker.klenk@upf.edu"))
Depends: R (>= 3.5.0)
Imports: methods, stats, utils, graphics, BiocGenerics, MatrixGenerics,
        S4Vectors, S4Arrays, HDF5Array, SparseArray, DelayedArray,
        IRanges, Biobase, SummarizedExperiment, GSEABase, Matrix (>=
        1.5-0), parallel, BiocParallel, SingleCellExperiment,
        SpatialExperiment, sparseMatrixStats, DelayedMatrixStats,
        BiocSingular, cli
Suggests: RUnit, BiocStyle, knitr, rmarkdown, limma, RColorBrewer,
        org.Hs.eg.db, genefilter, edgeR, GSVAdata, sva, ggplot2,
        TENxPBMCData, scuttle, scran, igraph, shiny, shinydashboard,
        ggplot2, data.table, plotly, future, promises, shinybusy,
        shinyjs
LinkingTo: cli
Description: Gene Set Variation Analysis (GSVA) is a non-parametric,
        unsupervised method for estimating variation of gene set
        enrichment through the samples of a expression data set. GSVA
        performs a change in coordinate systems, transforming the data
        from a gene by sample matrix to a gene-set by sample matrix,
        thereby allowing the evaluation of pathway enrichment for each
        sample. This new matrix of GSVA enrichment scores facilitates
        applying standard analytical methods like functional
        enrichment, survival analysis, clustering, CNV-pathway analysis
        or cross-tissue pathway analysis, in a pathway-centric manner.
License: Artistic-2.0
VignetteBuilder: knitr
URL: https://github.com/rcastelo/GSVA
BugReports: https://github.com/rcastelo/GSVA/issues
Encoding: UTF-8
biocViews: FunctionalGenomics, Microarray, RNASeq, Pathways,
        GeneSetEnrichment
Roxygen: list(markdown = TRUE)
RoxygenNote: 7.3.3
Config/pak/sysreqs: make libmagick++-dev gsfonts libicu-dev libpng-dev
        libxml2-dev libssl-dev zlib1g-dev
Repository: https://bioc-release.r-universe.dev
Date/Publication: 2025-11-05 12:26:13 UTC
RemoteUrl: https://github.com/bioc/GSVA
RemoteRef: RELEASE_3_22
RemoteSha: 441c638a84915612b7603f8101368a2ac2e623ab
NeedsCompilation: yes
Packaged: 2025-11-11 19:53:06 UTC; root
Author: Robert Castelo [aut, cre],
  Justin Guinney [aut],
  Alexey Sergushichev [ctb],
  Pablo Sebastian Rodriguez [ctb],
  Axel Klenk [ctb]
Maintainer: Robert Castelo <robert.castelo@upf.edu>
Built: R 4.5.2; x86_64-w64-mingw32; 2025-11-12 03:18:35 UTC; windows
Archs: x64
