This function calculates p-values for each gene set based on row permutations of the gene p values or column permutations of the expression matrix; the p values can be obtained either as individual gene set p values or p values based on smoothing across gene sets of similar size.

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Description

This function calculates p-values for each gene set based on row permutations of the gene p values or column permutations of the expression matrix; the p values can be obtained either as individual gene set p values or p values based on smoothing across gene sets of similar size.

Usage

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MLP(geneSet, geneStatistic, minGenes = 5, maxGenes = 100,
  rowPermutations = TRUE, nPermutations = 100, smoothPValues = TRUE,
  probabilityVector = c(0.5, 0.9, 0.95, 0.99, 0.999, 0.9999, 0.99999),
  df = 9, addGeneSetDescription = TRUE)

Arguments

geneSet

is the input list of gene sets (components) and gene IDs (character vectors). A gene set can, for example, be a GO category with for each category Entrez Gene identifiers; The getGeneSets function can be used to construct the geneSet argument for different pathway sources.

geneStatistic

is either a named numeric vector (if rowPermutations is TRUE) or a numeric matrix of pvalues (if rowPermutations is FALSE). The names of the numeric vector or row names of the matrix should represent the gene IDs.

minGenes

minimum number of genes in a gene set for it to be considered (lower threshold for gene set size)

maxGenes

maximum number of genes in a gene set for it to be considered (upper threshold for gene set size)

rowPermutations

logical indicating whether to use row permutations (TRUE; default) or column permutations (FALSE)

nPermutations

is the number of simulations. By default 100 permutations are conducted.

smoothPValues

logical indicating whether one wants to calculate smoothed cut-off thresholds (TRUE; default) or not (FALSE).

probabilityVector

vector of quantiles at which p values for each gene set are desired

df

degrees of freedom for the smooth.spline function used in getSmoothedPValues

addGeneSetDescription

logical indicating whether a column with the gene set description be added to the output data frame; defaults to TRUE.

Value

data frame with four (or five) columns: totalGeneSetSize, testedGeneSetSize, geneSetStatistic and geneSetPValue and (if addDescription is set to TRUE) geneSetDescription; the rows of the data frame are ordered by ascending geneSetPValue.

References

Raghavan, Nandini et al. (2007). The high-level similarity of some disparate gene expression measures, Bioinformatics, 23, 22, 3032-3038.

Examples

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if (require(GO.db)){
  pathExampleGeneSet <- system.file("exampleFiles", "exampleGeneSet.rda", package = "MLP")
  pathExamplePValues <- system.file("exampleFiles", "examplePValues.rda", package = "MLP")
  load(pathExampleGeneSet)
  load(pathExamplePValues)
  head(examplePValues)
  head(exampleGeneSet)
  mlpResult <- MLP(geneSet = exampleGeneSet, geneStatistic = examplePValues)
  head(mlpResult)
}