Introduction | Using a SLURM workload manager | Session information | References
Package: GSVA 2.7.10
Robert Castelo
GSVA: Gene Set Variation Analysis for Microarray and RNA-Seq Data
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.
Authors:
GSVA_2.7.10.tar.gz
GSVA_2.7.10.zip(r-4.7)GSVA_2.7.10.zip(r-4.6)GSVA_2.7.10.zip(r-4.5)
GSVA_2.7.10.tgz(r-4.6-x86_64)GSVA_2.7.10.tgz(r-4.6-arm64)GSVA_2.7.10.tgz(r-4.5-x86_64)GSVA_2.7.10.tgz(r-4.5-arm64)
GSVA_2.7.10.tar.gz(r-4.7-arm64)GSVA_2.7.10.tar.gz(r-4.7-x86_64)GSVA_2.7.10.tar.gz(r-4.6-arm64)GSVA_2.7.10.tar.gz(r-4.6-x86_64)
GSVA_2.7.10.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
DESCRIPTION |NEWS
card.svg |card.png
GSVA/json (API)
| # Install 'GSVA' in R: |
| install.packages('GSVA', repos = c('https://bioc.r-universe.dev', 'https://cloud.r-project.org')) |
Bug tracker:https://github.com/rcastelo/gsva/issues
On BioConductor:GSVA-2.7.9(bioc 3.24)GSVA-2.6.3(bioc 3.23)
functionalgenomicsmicroarrayrnaseqpathwaysgenesetenrichmentgene-set-enrichmentgenomicspathway-enrichment-analysis
Last updated from:32ba412412. Checks:1 ERROR, 13 OK. Indexed: yes.
| Target | Result | Time | Files | Syslog |
|---|---|---|---|---|
| bioc-checks | ERROR | 333 | ||
| linux-devel-arm64 | OK | 540 | ||
| linux-devel-x86_64 | OK | 749 | ||
| source / vignettes | OK | 427 | ||
| linux-release-arm64 | OK | 524 | ||
| linux-release-x86_64 | OK | 652 | ||
| macos-release-arm64 | OK | 353 | ||
| macos-release-x86_64 | OK | 811 | ||
| macos-oldrel-arm64 | OK | 365 | ||
| macos-oldrel-x86_64 | OK | 821 | ||
| windows-devel | OK | 634 | ||
| windows-release | OK | 620 | ||
| windows-oldrel | OK | 588 | ||
| wasm-release | OK | 287 |
Exports:computeGeneSetsOverlapdeduplicateGeneSetsdetailsfilterGeneSetsgeneIdsToGeneSetCollectiongeneSetsgeneSets<-geneSetSizesgsvagsvaAnnotationgsvaAnnotation<-gsvaBatchtoolsSlurmParamgsvaColRanksgsvaColScoresgsvaEnrichmentgsvaMapgsvaParamgsvaRanksgsvaReducegsvaRowNormgsvaScoresguessGeneIdTypeigsvaloadHDF5GSVAloadHDF5GSVAranksplageParamreadGMTsaveHDF5GSVAsaveHDF5GSVAranksspatCorssgseaParamzscoreParam
Dependencies:abindannotateAnnotationDbiaskpassassortheadbeachmatBHBiobaseBiocFileCacheBiocGenericsbiocmakeBiocParallelBiocSingularBiostringsbitbit64blobcachemclicodetoolscpp11crayoncurlDBIdbplyrDelayedArrayDelayedMatrixStatsdir.expirydplyrfastmapfilelockformatRfutile.loggerfutile.optionsgenericsGenomicRangesgluegraphGSEABaseh5mreadHDF5Arrayhttrhttr2IRangesirlbajsonliteKEGGRESTlambda.rlatticelifecyclemagickmagrittrMatrixMatrixGenericsmatrixStatsmemoisememusemimeopensslpillarpkgconfigpngpurrrR6Rcpprhdf5rhdf5filtersRhdf5librjsonrlangRSQLitersvdS4ArraysS4VectorsScaledMatrixSeqinfoSingleCellExperimentsnowSparseArraysparseMatrixStatsSpatialExperimentstringistringrSummarizedExperimentsystibbletidyrtidyselectutf8vctrswithrXMLxtableXVector
Running GSVA in an HPC environment
Last update: 2026-06-30
Started: 2026-06-30
GSVA on proteomics data
Introduction | Load gene sets | Usage and benchmark with RNA-seq data | Usage and benchmark with proteomics data | Session information | References
Last update: 2026-05-25
Started: 2026-04-27
GSVA on single-cell RNA-seq data
Introduction | Import data | Quality control and pre-processing | Annotate cell types using GSVA | Read gene sets in GMT format | Add gene identifier type metadata | Build parameter object | Calculate GSVA scores | Using GSVA scores to assign cell types | Benchmarking | Session information | References
Last update: 2026-05-25
Started: 2025-10-27
GSVA: gene set variation analysis
Quick start | Introduction | Overview of the GSVA functionality | Gene set definitions and containers | Importing gene sets from GMT files | Quantification of pathway activity in bulk microarray and RNA-seq data | Example applications | Molecular signature identification | Differential expression at pathway level | Data exploration at gene level | Running GSVA | Data exploration at pathway level | Interactive web app | Contributing | Session information | References
Last update: 2026-02-19
Started: 2021-02-05
Readme and manuals
Help Manual
| Help page | Topics |
|---|---|
| Compute gene-sets overlap | computeGeneSetsOverlap computeGeneSetsOverlap,GeneSetCollection,character-method computeGeneSetsOverlap,list,character-method |
| Handling of Duplicated Gene Set Names | deduplicateGeneSets |
| Filter gene sets | filterGeneSets filterGeneSets,GeneSetCollection-method filterGeneSets,list-method |
| Construct a GeneSetCollection object from a list of character vectors | geneIdsToGeneSetCollection |
| Retrieve or Determine Gene Sets | geneSets geneSets,GsvaExprData-method geneSets,GsvaMethodParam-method geneSets,SingleCellExperiment-method geneSets,SpatialExperiment-method geneSets,SummarizedExperiment-method geneSetSizes geneSetSizes,GsvaExprData-method geneSetSizes,GsvaMethodParam-method |
| Gene Set Variation Analysis | gsva gsva,gsvaParam-method gsva,plageParam-method gsva,ssgseaParam-method gsva,zscoreParam-method |
| Store and Retrieve Annotation Metadata | gsvaAnnotation gsvaAnnotation,ExpressionSet-method gsvaAnnotation,GeneSetCollection-method gsvaAnnotation,GsvaExprData-method gsvaAnnotation,list-method gsvaAnnotation,SingleCellExperiment-method gsvaAnnotation,SpatialExperiment-method gsvaAnnotation,SummarizedExperiment-method gsvaAnnotation<- gsvaAnnotation<-,ExpressionSet,character-method gsvaAnnotation<-,ExpressionSet,GeneIdentifierType-method gsvaAnnotation<-,GsvaExprData,GeneIdentifierType-method gsvaAnnotation<-,list,GeneIdentifierType-method gsvaAnnotation<-,SingleCellExperiment,GeneIdentifierType-method gsvaAnnotation<-,SpatialExperiment,GeneIdentifierType-method gsvaAnnotation<-,SummarizedExperiment,GeneIdentifierType-method |
| GSVA enrichment data and visualization | gsvaEnrichment |
| 'GsvaExprData' class | GsvaExprData GsvaExprData-class |
| 'GsvaGeneSets' class | GsvaGeneSets-class |
| MapReduce parallelization for HPC environments | gsvaBatchtoolsSlurmParam gsvaMap gsvaReduce |
| 'GsvaMethodParam' class | details,GsvaMethodParam-method details,gsvaParam-method details,ssgseaParam-method GsvaMethodParam-class |
| 'gsvaParam' class | anyNA,gsvaParam-method geneSets<- geneSets<-,gsvaParam,GsvaGeneSets-method gsvaParam gsvaParam-class gsvaRanksParam-class |
| GSVA ranks and scores | gsvaColRanks gsvaColScores gsvaRowNorm |
| Guess the gene identifier type from a list of character vectors | guessGeneIdType |
| Gene Set Variation Analysis | igsva |
| 'plageParam' class | plageParam plageParam-class |
| Import Gene Sets from a GMT File | readGMT |
| Save/load GSVA output to disk using HDF5 format | loadHDF5GSVA saveHDF5GSVA |
| Compute Spatial Autocorrelation for SpatialExperiment objects | spatCor spatCor,SpatialExperiment-method |
| 'ssgseaParam' class | anyNA,ssgseaParam-method ssgseaParam ssgseaParam-class |
| 'zscoreParam' class | zscoreParam zscoreParam-class |
