Description Usage Arguments Details See Also Examples
Plots the distribution of gene set statistic values obtained in different resampling settings of an enrichment analysis, and draws the statistic value of the input set as a vertical line.
1 2 3 4 5 6 7 |
x |
A result of a call to |
signLevel |
The significance level that should be applied for the plots. Default is the significance level used for the analysis in |
subset |
Indices for the results that should be included in the diagram. |
ask |
If set to true, the plot function will prompt for a user input for each new plot that is shown on an interactive device (see |
addLegend |
If set to true (default), a |
... |
Other parameters which can be used for histograms (see |
The function plots the distribution of gene set statistic values under the null hypothesis. It requires the
significance assessment step of the enrichment analysis configuration (parameter significance
or gsAnalysis
) to be a computer-intensive testing procedure that yields a distribution of gene set statistic p-values under the null hypothesis. Predefined configurations for which this plot works are analysis.gsea
, analysis.averageCorrelation
and analysis.averageTStatistic
.
A histogram is plotted for the analysis in x
. If x
includes the analyses for several gene sets, one histogram is plotted for each of the gene sets.
The statistic value of the input set is depicted as a vertical line.
The most common graphical parameters can be supplied as vectors (one entry per analyzed gene set) to vary them between the different analyses. These parameters are: main
, xlab
, ylab
.
geneSetAnalysis
, predefinedAnalyses
, gsAnalysis
, evaluateGeneSetUncertainty
, plot.uncertaintyResult
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 | # load data
require(GlobalAncova)
data(vantVeer)
data(phenodata)
data(pathways)
res <- geneSetAnalysis(
# global parameters
dat = vantVeer,
geneSets = pathways[3],
analysis = analysis.averageCorrelation(),
# additional parameters for analysis.averageCorrelation
labs = phenodata$metastases,
p = 1,
numSamples = 10)
# plot the histogram for the cell cycle control gene set
hist(res, main = names(pathways[3]))
|
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