plotSigGeneSet: Plot gene set details

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

Description

This function is to generate a two-panel plot showing detailed information of the gene set specified. One panel is showing the running enrichment scores and the position where the ES appear. The other panel shows the significance level of the ES, comparing with permutation ESs.

Usage

plotSigGeneSet(gene.set, i, gene.score, pdf = NULL)

Arguments

gene.set	a SeqGeneSet object after running GSEnrichAnalyze.
i	the i-th gene set in the SeqGeneSet object. topGeneSets is useful to find the most significantly overrepresented gene set.
gene.score	the gene score vector containing gene scores for each gene.
pdf	whether to save the plot to PDF file; if yes, provide the name of the PDF file.

Details

See writeSigGeneSet, which writes the detailed gene set information to a file or to the screen.

Author(s)

Xi Wang, [e-mail]

See Also

GSEnrichAnalyze, topGeneSets, plotSig, plotES, writeSigGeneSet

Examples

data(DEscore, package="SeqGSEA")
data(DSscore, package="SeqGSEA")
gene.score <- geneScore(DEscore, DSscore, method="linear", DEweight = 0.3)
data(DEscore.perm, package="SeqGSEA")
data(DSscore.perm, package="SeqGSEA")
gene.score.perm <- genePermuteScore(DEscore.perm, DSscore.perm, method="linear",  DEweight=0.3)
data(GS_example, package="SeqGSEA")
GS_example <- GSEnrichAnalyze(GS_example, gene.score, gene.score.perm)
topGeneSets(GS_example, n=5)
plotSigGeneSet(GS_example, 9, gene.score) # 9th gene set is the most significant one.

Example output

Loading required package: Biobase
Loading required package: BiocGenerics
Loading required package: parallel

Attaching package: 'BiocGenerics'

The following objects are masked from 'package:parallel':

    clusterApply, clusterApplyLB, clusterCall, clusterEvalQ,
    clusterExport, clusterMap, parApply, parCapply, parLapply,
    parLapplyLB, parRapply, parSapply, parSapplyLB

The following objects are masked from 'package:stats':

    IQR, mad, sd, var, xtabs

The following objects are masked from 'package:base':

    Filter, Find, Map, Position, Reduce, anyDuplicated, append,
    as.data.frame, cbind, colMeans, colSums, colnames, do.call,
    duplicated, eval, evalq, get, grep, grepl, intersect, is.unsorted,
    lapply, lengths, mapply, match, mget, order, paste, pmax, pmax.int,
    pmin, pmin.int, rank, rbind, rowMeans, rowSums, rownames, sapply,
    setdiff, sort, table, tapply, union, unique, unsplit, which,
    which.max, which.min

Welcome to Bioconductor

    Vignettes contain introductory material; view with
    'browseVignettes()'. To cite Bioconductor, see
    'citation("Biobase")', and for packages 'citation("pkgname")'.

Loading required package: doParallel
Loading required package: foreach
Loading required package: iterators
Loading required package: DESeq
Loading required package: locfit
locfit 1.5-9.1 	 2013-03-22
Loading required package: lattice
    Welcome to 'DESeq'. For improved performance, usability and
    functionality, please consider migrating to 'DESeq2'.
Warning message:
executing %dopar% sequentially: no parallel backend registered 
                          GSName GSSize        ES ES.pos pval     FDR FWER
9                     TBK1.DF_UP      5 1.8953147     22 0.00 0.00000 0.04
8                 HOXA9_DN.V1_UP      5 1.5076333     39 0.08 0.25000 0.50
11 KRAS.600.LUNG.BREAST_UP.V1_DN      5 1.4063251     53 0.13 0.33333 0.77
1                  ERB2_UP.V1_DN      6 0.9322128     11 0.62 1.00000 1.00
2           AKT_UP_MTOR_DN.V1_UP      6 0.2393357    165 0.99 1.00000 1.00

SeqGSEA documentation built on Nov. 8, 2020, 5:46 p.m.