predictTargetingDrugs {cTRAP}R Documentation

Predict targeting drugs

Description

Identify compounds that may target the phenotype associated with a user-provided differential expression profile by comparing such against a correlation matrix of gene expression and drug sensitivity.

Usage

predictTargetingDrugs(diffExprGenes, expressionDrugSensitivityCor,
  method = c("spearman", "pearson", "gsea"), geneSize = 150,
  isDrugActivityDirectlyProportionalToSensitivity = NULL)

Arguments

diffExprGenes

Numeric: named vector of differentially expressed genes whose names are gene identifiers and respective values are a statistic that represents significance and magnitude of differentially expressed genes (e.g. t-statistics)

expressionDrugSensitivityCor

Matrix: correlation matrix of gene expression (rows) and drug sensitivity (columns) across cell lines. Pre-prepared gene expression and drug sensitivity associations are available to download using loadExpressionDrugSensitivityAssociation.

method

Character: comparison methods to run (spearman, pearson or gsea); multiple methods can be selected

geneSize

Number: top and bottom number of differentially expressed genes for gene set enrichment (only used if method = gsea)

isDrugActivityDirectlyProportionalToSensitivity

Boolean: are the values used for drug activity directly proportional to drug sensitivity? See details.

Details

If isDrugActivityDirectlyProportionalToSensitivity is set to NULL (as by default), the attribute isDrugMetricDirectlyProportionalToSensitivity on the object passed as argument expressionDrugSensitivityCor is used (objects obtained via loadExpressionDrugSensitivityAssociation have the mentioned attribute set).

Value

Data table with correlation or GSEA results comparing differential expression values against gene expression and drug sensitivity associations

GSEA score

Weighted connectivity scores (WTCS) are calculated when method = "gsea" (https://clue.io/connectopedia/cmap_algorithms).

See Also

Other functions related with the prediction of targeting drugs: loadExpressionDrugSensitivityAssociation, plot.referenceComparison, plotTargetingDrugsVSsimilarPerturbations

Examples

# Example of a differential expression profile
data("diffExprStat")

# Load expression and drug sensitivity association derived from GDSC data
gdsc <- loadExpressionDrugSensitivityAssociation("GDSC 7")

# Predict targeting drugs on a differential expression profile
predictTargetingDrugs(diffExprStat, gdsc)

[Package cTRAP version 1.4.0 Index]