# 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.

### 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

1 2 3 4 |

### 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

1 2 3 4 5 6 7 8 9 10 | ```
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)
}
``` |