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

### Arguments

`input` | `Named numeric 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); or `character` of gene symbols composing a gene set that is tested for enrichment in reference data (only used if `method` includes `gsea`)
`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: one or more methods to compare data (`spearman`, `pearson` or `gsea`)
`geneSize` | Numeric: number of top up-/down-regulated genes to use as gene sets to test for enrichment in reference data; if a 2-length numeric vector, the first index is the number of top up-regulated genes and the second index is the number of down-regulated genes used to create gene sets; only used if `method` includes `gsea` and if `input` is not a gene set
`isDrugActivityDirectlyProportionalToSensitivity` | Boolean: are the values used for drug activity directly proportional to drug sensitivity? See details.

### Details

If `isDrugActivityDirectlyProportionalToSensitivity = NULL`, the attribute `isDrugMetricDirectlyProportionalToSensitivity` of `expressionDrugSensitivityCor` is used (see `loadExpressionDrugSensitivityAssociation()`).

### 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: `as.table.referenceComparison()`, `listExpressionDrugSensitivityAssociation()`, `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 1.8.0 Index]