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RTN (version 1.10.0)

tna.plot.gsea2: Plot enrichment analyses from TNA objects.

Description

This function takes a TNA object and plots the two-tailed GSEA results for individual regulons.

Usage

tna.plot.gsea2(object, labPheno="tna", file=labPheno, filepath=".", regulon.order="size", ntop=NULL, tfs=NULL, ylimPanels=c(-3.0,3.0,-0.5,0.5), heightPanels=c(2.0,0.8,5.0), width=2.7, height=3.0, ylabPanels=c("Phenotype","Regulon","Enrichment score"), xlab="Position in the ranked list of genes", alpha=1.0, sparsity=10, autoformat=TRUE, ...)

Arguments

object
an object of class 'TNA' TNA-class.
file
a character string naming a file.
filepath
a single character value specifying where to store GSEA2 figures.
regulon.order
a single character value specifying whether regulons should be ordered by 'size', 'score', 'pvalue', 'adj.pvalue' and 'name' (or 'none' to keep the input ordering).
ntop
a single integer value specifying how many regulons of top significance will be plotted.
tfs
an optional vector with transcription factor identifiers (this option overrides the 'ntop' argument).
ylimPanels
a numeric vector of length=4 specifying y coordinates ranges of the 1st and 3th plots (i.e. ylim for 'Phenotypes' and 'Running enrichment score').
heightPanels
a numeric vector of length=3 specifying the relative height of each panel in the plot.
width
a single numeric value specifying the width of the graphics region in inches.
height
a single numeric value specifying the height of the graphics region in inches.
ylabPanels
a character vector of length=3 specifying the the title for the y axes.
xlab
a single character specifying the the title for the x axis.
labPheno
a single character specifying a label for the phenotype (will also be used as the name of output file).
alpha
a single numeric value in [0,1] specifying the transparency of the hits in the ranked list.
sparsity
a single integer value (>1) specifying the density of the dots representing the running score.
autoformat
a single logical value specifying to set the graph format using predefined themes. This option overrides the "ylimPanels" argument.
...
other arguments used by the function pdf.

See Also

tna.gsea2

Examples

Run this code

data(dt4rtn)

tfs4test<-c("PTTG1","E2F2","FOXM1","E2F3","RUNX2")
rtni <- new("TNI", gexp=dt4rtn$gexp, transcriptionFactors=dt4rtn$tfs[tfs4test])

## Not run: 
# 
# rtni <- tni.preprocess(rtni,gexpIDs=dt4rtn$gexpIDs)
# rtni<-tni.permutation(rtni)
# rtni<-tni.bootstrap(rtni)
# rtni<-tni.dpi.filter(rtni)
# rtna<-tni2tna.preprocess(rtni, phenotype=dt4rtn$pheno, hits=dt4rtn$hits, phenoIDs=dt4rtn$phenoIDs)
# 
# # run GSEA2 analysis pipeline
# rtna <- tna.gsea2(rtna, stepFilter=FALSE)
# 
# # plot available GSEA2 results
# tna.plot.gsea2(rtna, labPheno="test")
# ## End(Not run)

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