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 1.5.0 Index]