plotTargetingDrugsVSsimilarPerturbations: Plot similar perturbations against predicted targeting drugs

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

Description

Plot similar perturbations against predicted targeting drugs

Usage

plotTargetingDrugsVSsimilarPerturbations(
  targetingDrugs,
  similarPerturbations,
  column,
  labelBy = "pert_iname",
  quantileThreshold = 0.25,
  showAllScores = FALSE,
  keyColTargetingDrugs = NULL,
  keyColSimilarPerturbations = NULL
)

Arguments

targetingDrugs	targetingDrugs object
similarPerturbations	similarPerturbations object
column	Character: column to plot (must be available in both databases)
labelBy	Character: column in as.table(similarPerturbations) or as.table(targetingDrugs) to be used for labelling
quantileThreshold	Numeric: quantile (between 0 and 1) to highlight values of interest
showAllScores	Boolean: show all scores? If FALSE, only the best score per compound will be plotted
keyColTargetingDrugs	Character: column from targetingDrugs to match against keyColSimilarPerturbations; if not set, it will be automatically determined
keyColSimilarPerturbations	Character: column from similarPerturbations to match against keyColTargetingDrugs; if not set, it will be automatically determined

Value

ggplot2 plot

See Also

Other functions related with the ranking of CMap perturbations: as.table.referenceComparison(), filterCMapMetadata(), getCMapConditions(), getCMapPerturbationTypes(), loadCMapData(), loadCMapZscores(), parseCMapID(), plot.perturbationChanges(), plot.referenceComparison(), prepareCMapPerturbations(), print.similarPerturbations(), rankSimilarPerturbations()

Other functions related with the prediction of targeting drugs: as.table.referenceComparison(), listExpressionDrugSensitivityAssociation(), loadExpressionDrugSensitivityAssociation(), plot.referenceComparison(), predictTargetingDrugs()

Examples

# Rank similarity against CMap compound perturbations
similarPerts <- rankSimilarPerturbations(diffExprStat,
                                         cmapPerturbationsCompounds)

# Predict targeting drugs
gdsc <- loadExpressionDrugSensitivityAssociation("GDSC 7")
predicted <- predictTargetingDrugs(diffExprStat, gdsc)

plotTargetingDrugsVSsimilarPerturbations(predicted, similarPerts,
                                         "spearman_rank")

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