analyseDrugSetEnrichment: Analyse drug set enrichment

In cTRAP: Identification of candidate causal perturbations from differential gene expression data

Description

Analyse drug set enrichment

Usage

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

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::fgsea minSize Minimal size of a gene set to test. All pathways below the threshold are excluded. 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.

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)

cTRAP documentation built on Nov. 8, 2020, 10:58 p.m.