Description Usage Arguments Details Value See Also Examples
View source: R/evaluateGeneSetUncertainty.R
A robustness measure that quantifies the uncertainty of a gene set by performing a resampling experiment and can be used in the robustness
parameter of gsAnalysis
.
1 2 3 4 5 6 7 8 9 10 11 |
... |
Additional parameters for the different steps of the analysis pipeline, depending on the concrete configuration supplied in |
dat |
A numeric matrix of gene expression values for all analyzed genes. Here, each row corresponds to one gene, and each column corresponds to one sample. The rows must be named with the gene names used in the gene sets. |
geneSet |
A vector containing the names of genes in a gene set. All genes set must correspond to the row names of |
analysis |
The parameters of the analysis that is applied to the perturbed copies of the gene set. These parameters are described by an object of class |
numSamplesUncertainty |
The number of resampling experiments which should be applied to estimate the robustness of |
blockSize |
Number of genes in one resampled block. |
k |
A |
signLevel |
The significance level for the significance assessment of the gene sets (defaults to |
preprocessGeneSet |
Specifies whether the gene sets in |
cluster |
If the analyses should be applied in parallel for the different values of |
The uncertainty analysis repeatedly replaces parts of the original gene sets by random genes and calculating the gene set statistics for these randomized gene sets. This yields a distribution of gene set statistic values for slightly modified variants of the original gene set.
Returns a list (of class uncertaintyResult
) with the following elements:
uncertainty The calculated stability of the original gene set.
confidenceValues
A matrix of quantiles of gssValues
(signLevel, 0.5, 1-signLevel). One row for each value in k
.
uncertaintyEvaluations
A list with one entry per value in k
containing the following elements:
confidenceValues
Quantiles of gssValues
: signLevel, 0.5, 1-signLevel.
gssValues A vector of gene set statistic values, one for each randomly sampled gene set.
uncertainGeneSets A matrix containing all partially random gene sets.
k The percentage of genes in the randomized gene sets taken from the original gene set.
signLevel The significance level used for this analysis.
originalGeneSetValues
Result of geneSetAnalysis
for the original geneSet
.
geneSetAnalysis
, gsAnalysis
, gls
, transformation
, gss
, plot.uncertaintyResult
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 | # 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,
k = seq(0.1,0.9, by=0.1),
# additional parameters for analysis.averageCorrelation
labs = phenodata$metastases,
numSamples = 10)
|
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