analyseDrugSetEnrichment {cTRAP} | R Documentation

## Analyse drug set enrichment

### Description

Analyse drug set enrichment

### Usage

    analyseDrugSetEnrichment(
      sets,
      stats,
      col = NULL,
      nperm = 10000,
      maxSize = 500,
      ...,
      keyColSets = NULL,
      keyColStats = NULL
    )

### Arguments

`sets` | Named list of characters: named sets containing compound identifiers (obtain drug sets by running `prepareDrugSets()`)
`stats` | Named numeric vector or either a `similarPerturbations` or a `targetingDrugs` object (obtained after running `rankSimilarPerturbations` or `predictTargetingDrugs`, respectively)
`col` | Character: name of the column to use for statistics (only required if class of `stats` is either `similarPerturbations` or `targetingDrugs`)
`nperm` | Number of permutations to do. Minimial possible nominal p-value is about 1/nperm
`maxSize` | Maximal size of a gene set to test. All pathways above the threshold are excluded.
`...` | Arguments passed on to `fgsea::fgseaSimple` `minSize` Minimal size of a gene set to test. All pathways below the threshold are excluded. `scoreType` This parameter defines the GSEA score type. Possible options are ("std", "pos", "neg") `nproc` If not equal to zero sets BPPARAM to use nproc workers (default = 0). `gseaParam` GSEA parameter value, all gene-level statis are raised to the power of 'gseaParam' before calculation of GSEA enrichment scores. `BPPARAM` Parallelization parameter used in bplapply. Can be used to specify cluster to run. If not initialized explicitly or by setting 'nproc' default value 'bpparam()' is used.
`keyColSets` | Character: column from `sets` to compare with column `keyColStats` from `stats`; automatically selected if `NULL`
`keyColStats` | Character: column from `stats` to compare with column `keyColSets` from `sets`; automatically selected if `NULL`

### Value

Enrichment analysis based on GSEA

### See Also

Other functions for drug set enrichment analysis: `loadDrugDescriptors()`, `plotDrugSetEnrichment()`, `prepareDrugSets()`

### Examples

    descriptors <- loadDrugDescriptors()
    drugSets <- prepareDrugSets(descriptors)

    # Analyse drug set enrichment in ranked targeting drugs for a differential
    # expression profile
    data("diffExprStat")
    gdsc      <- loadExpressionDrugSensitivityAssociation("GDSC")
    predicted <- predictTargetingDrugs(diffExprStat, gdsc)

    analyseDrugSetEnrichment(drugSets, predicted)

[Package cTRAP version 1.10.1 Index]