Description Usage Arguments Details See Also Examples
For each percentage of original gene set genes, the quantiles of the distribution obtained by a resampling simulation are plotted. Significance threshold (quantile of the Null distribution) and the test statistic of the original gene set are drawn as horizontal lines.
1 2 3 4 5 6 |
x |
A result of a call to |
signLevel |
Only results with significance level smaller than the given value are plotted. |
addLegend |
If set to true (default), a |
addMinimalStability |
If set to true, a line is added to the plot giving the minimal stability. |
... |
Other parameters which can be used for histograms (see |
The function plots the quantiles of the resampling distributions for evaluated degrees of fuzziness. 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 values under the null hypothesis. Predefined configurations for which this plot works are analysis.gsea
, analysis.averageCorrelation
and analysis.averageTStatistic
.
Three lines, corresponding to the different qunatiles with one dot per fuzziness evaluation (k
) are plotted for the analysis in x
. The significance threshold is shown as a green horizontal line. The statistic value of the original input set is depicted as a red horizontal line.
If addMinimalStability
is TRUE
, the lower bound of the stability is ploted as a dotted line.
geneSetAnalysis
, predefinedAnalyses
, gsAnalysis
, evaluateGeneSetUncertainty
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 | # load data
require(GlobalAncova)
data(vantVeer)
data(phenodata)
data(pathways)
res <- evaluateGeneSetUncertainty(
# parameters for evaluateGeneSetUncertainty
dat = vantVeer,
geneSet = pathways[[1]],
analysis = analysis.averageCorrelation(),
numSamplesUncertainty = 10,
N = seq(0.1,0.9, by=0.1),
# additional parameters for analysis.averageCorrelation
labs = phenodata$metastases,
numSamples = 10)
# plot the results for the cell cycle control gene set
plot(res, addMinimalStability = TRUE)
|
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