Package: SeqGSEA 1.47.0

Xi Wang

SeqGSEA: Gene Set Enrichment Analysis (GSEA) of RNA-Seq Data: integrating differential expression and splicing

The package generally provides methods for gene set enrichment analysis of high-throughput RNA-Seq data by integrating differential expression and splicing. It uses negative binomial distribution to model read count data, which accounts for sequencing biases and biological variation. Based on permutation tests, statistical significance can also be achieved regarding each gene's differential expression and splicing, respectively.

Authors:Xi Wang <[email protected]>

SeqGSEA_1.47.0.tar.gz
SeqGSEA_1.47.0.zip(r-4.5)SeqGSEA_1.47.0.zip(r-4.4)SeqGSEA_1.47.0.zip(r-4.3)
SeqGSEA_1.47.0.tgz(r-4.4-any)SeqGSEA_1.47.0.tgz(r-4.3-any)
SeqGSEA_1.47.0.tar.gz(r-4.5-noble)SeqGSEA_1.47.0.tar.gz(r-4.4-noble)
SeqGSEA_1.47.0.tgz(r-4.4-emscripten)SeqGSEA_1.47.0.tgz(r-4.3-emscripten)
SeqGSEA.pdf |SeqGSEA.html✨
SeqGSEA/json (API)
NEWS

# Install 'SeqGSEA' in R:
install.packages('SeqGSEA', repos = c('https://bioc.r-universe.dev', 'https://cloud.r-project.org'))

Peer review:

Datasets:

On BioConductor:SeqGSEA-1.47.0(bioc 3.21)SeqGSEA-1.46.0(bioc 3.20)

This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.

sequencingrnaseqgenesetenrichmentgeneexpressiondifferentialexpressiondifferentialsplicingimmunooncology

4.30 score 10 scripts 458 downloads 18 mentions 54 exports 100 dependencies

Last updated 26 days agofrom:eb9808f6e2. Checks:OK: 1 NOTE: 5 WARNING: 1. Indexed: yes.

TargetResultDate
Doc / VignettesOKOct 31 2024
R-4.5-winWARNINGOct 31 2024
R-4.5-linuxNOTEOct 31 2024
R-4.4-winNOTEOct 31 2024
R-4.4-macNOTEOct 31 2024
R-4.3-winNOTEOct 31 2024
R-4.3-macNOTEOct 31 2024

Exports:calEScalES.permconvertEnsembl2SymbolconvertSymbol2Ensemblcountscounts<-DENBStat4GSEADENBStatPermut4GSEADENBTestDEpermutePvalDSpermute4GSEADSpermutePvalDSresultExonTableDSresultGeneTableestiExonNBstatestiGeneNBstatexonIDexonTestabilitygeneIDgeneListgenePermuteScoregeneScoregeneSetDescsgeneSetNamesgeneSetSizegeneTestabilitygenpermuteMatgetGeneCountGSEAresultTableGSEnrichAnalyzelabelloadExonCountDataloadGenesetsnewGeneSetsnewReadCountSetnormESnormFactorplotESplotGeneScoreplotSigplotSigGeneSetrankCombinerunDESeqrunSeqGSEAscoreNormalizationsignifESsizesubsetByGenestopDEGenestopDSExonstopDSGenestopGeneSetswriteScoreswriteSigGeneSet

Dependencies:abindAnnotationDbiaskpassBHBiobaseBiocFileCacheBiocGenericsBiocParallelbiomaRtBiostringsbitbit64blobcachemclicodetoolscolorspacecpp11crayoncurlDBIdbplyrDelayedArrayDESeq2digestdoParalleldplyrfansifarverfastmapfilelockforeachformatRfutile.loggerfutile.optionsgenericsGenomeInfoDbGenomeInfoDbDataGenomicRangesggplot2gluegtablehmshttrhttr2IRangesisobanditeratorsjsonliteKEGGRESTlabelinglambda.rlatticelifecyclelocfitmagrittrMASSMatrixMatrixGenericsmatrixStatsmemoisemgcvmimemunsellnlmeopensslpillarpkgconfigplogrpngprettyunitsprogresspurrrR6rappdirsRColorBrewerRcppRcppArmadillorlangRSQLiteS4ArraysS4VectorsscalessnowSparseArraystringistringrSummarizedExperimentsystibbletidyrtidyselectUCSC.utilsutf8vctrsviridisLitewithrxml2XVectorzlibbioc

Gene set enrichment analysis of RNA-Seq data with the SeqGSEA package

Rendered fromSeqGSEA.Rnwusingutils::Sweaveon Oct 31 2024.

Last update: 2020-11-30
Started: 2013-11-01

Readme and manuals

Help Manual

Help pageTopics
SeqGSEA: a Bioconductor package for gene set enrichment analysis of RNA-Seq dataSeqGSEA-package SeqGSEA
Calculate running enrichment scores of gene setscalES
Calculate enrichment scores for gene sets in the permutation data setscalES.perm
Convert ensembl gene IDs to gene symbolsconvertEnsembl2Symbol
Convert gene symbols to ensembl gene IDsconvertSymbol2Ensembl
Accessors for the 'counts' slot of a ReadCountSet object.counts counts,ReadCountSet-method counts-methods counts<-,ReadCountSet,matrix-method
Calculate NB-statistics quantifying differential expression for each geneDENBStat4GSEA
Calculate NB-statistics quantifying DE for each gene in the permutation data setsDENBStatPermut4GSEA
Perform negative binomial exact test for differential expressionDENBTest
Permutation for p-values in differential expression analysisDEpermutePval
Pre-calculated DE/DS scoresDEscore DEscore.perm DSscore DSscore.perm
Compute NB-statistics quantifying differential splicing on the permutation data set.DSpermute4GSEA
Permutation for p-values in differential splicing analysisDSpermutePval
Form a table for DS analysis results at the Exon levelDSresultExonTable
Form a table for DS analysis results at the gene levelDSresultGeneTable
Calculate NB-statistics quantifying differential splicing for individual exonsestiExonNBstat
Calculate NB-statistics quantifying differential splicing for each geneestiGeneNBstat
Accessor to the exonID slot of ReadCountSet objectsexonID exonID<-
Check exon testabilityexonTestability
Accessor to the geneID slot of ReadCountSet objectsgeneID geneID<-
Get the gene list in a SeqGeneSet objectgeneList
Calculate gene scores on permutation data setsgenePermuteScore
Calculate gene scores by integrating DE and DS scoresgeneScore
Get the descriptions of gene sets in a SeqGeneSet objectgeneSetDescs
Get the names of gene set in a SeqGeneSet objectgeneSetNames
Get the numbers of genes in each gene set in a SeqGeneSet objectgeneSetSize
Check gene testabilitygeneTestability
Generate permutation matrixgenpermuteMat
Calculate read counts of genes from a ReadCountSet objectgetGeneCount
SeqGeneSet object exampleGS_example
Form a table for GSEA resultsGSEAresultTable
Main function of gene set enrichment analysisGSEnrichAnalyze
Get the labels of samples in a ReadCountSet objectlabel
Load Exon Count DataloadExonCountData
Load gene sets from filesloadGenesets
Initialize a new SeqGeneSet objectnewGeneSets
Generate a new ReadCountSet objectnewReadCountSet
Normalize enrichment scoresnormES
Get normalization factors for normalization DE or DS scoresnormFactor
Plot the distribution of enrichment scoresplotES
Plot gene (DE/DS) scoresplotGeneScore
Plot showing SeqGeneSet's p-values/FDRs vs. NESsplotSig
Plot gene set detailsplotSigGeneSet
Integration of differential expression and differential splice scores with a rank-based strategyrankCombine
ReadCountSet object exampleRCS_example
Class '"ReadCountSet"'ReadCountSet ReadCountSet-class
Run DESeq for differential expression analysisrunDESeq
An all-in function that allows end users to apply SeqGSEA to their data with one step.runSeqGSEA
Normalization of DE/DS scoresscoreNormalization
Class '"SeqGeneSet"'SeqGeneSet SeqGeneSet-class show,SeqGeneSet-method [,SeqGeneSet,numeric,ANY,ANY-method [,SeqGeneSet,numeric-method
Calculate significance of ESssignifES
Number of gene sets in a SeqGeneSet objectsize
Get a new ReadCountSet with specified gene IDs.subsetByGenes
Extract top differentially expressed genes.topDEGenes
Extract top differentially spliced exonstopDSExons
Extract top differentially spliced genestopDSGenes
Extract top significant gene setstopGeneSets
Write DE/DS scores and gene scoreswriteScores
Write gene set supporting informationwriteSigGeneSet