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