plot.referenceComparison {cTRAP} | R Documentation

## Plot data comparison

### Description

Plot data comparison

### Usage

    ## S3 method for class 'referenceComparison'
    plot(x, method = c("spearman", "pearson",
      "gsea", "rankProduct"), n = c(3, 3), showMetadata = TRUE,
      plotNonRankedPerturbations = FALSE, alpha = 0.3, ...)

### Arguments

`x` | `referenceComparison` object: obtained after running `rankSimilarPerturbations` or `predictTargetingDrugs`
`method` | Character: method to plot results (`spearman`, `pearson`, `gsea` or `rankProduct`)
`n` | Numeric: number of top and bottom genes to label (if a vector of two numbers is given, the first and second numbers will be used as the number of top and bottom genes to label, respectively)
`showMetadata` | Boolean: show available metadata information instead of identifiers (if available)?
`plotNonRankedPerturbations` | Boolean: plot non-ranked data in grey?
`alpha` | Numeric: transparency
`...` | Extra arguments currently not used

### Value

Plot illustrating the reference comparison

### See Also

Other functions related with the ranking of CMap perturbations: `[.perturbationChanges`, `as.table.similarPerturbations`, `dim.perturbationChanges`, `dimnames.perturbationChanges`, `filterCMapMetadata`, `getCMapConditions`, `getCMapPerturbationTypes`, `loadCMapData`, `loadCMapZscores`, `parseCMapID`, `plot.perturbationChanges`, `plotTargetingDrugsVSsimilarPerturbations`, `prepareCMapPerturbations`, `print.similarPerturbations`, `rankSimilarPerturbations`

Other functions related with the prediction of targeting drugs: `loadExpressionDrugSensitivityAssociation`, `plotTargetingDrugsVSsimilarPerturbations`, `predictTargetingDrugs`

### Examples

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

    ## Not run:
    # Download and load CMap perturbations to compare with
    cellLine <- "HepG2"
    cmapMetadataKD <- filterCMapMetadata(
      "cmapMetadata.txt", cellLine=cellLine,
      perturbationType="Consensus signature from shRNAs targeting the same gene")

    cmapPerturbationsKD <- prepareCMapPerturbations(
      cmapMetadataKD, "cmapZscores.gctx", "cmapGeneInfo.txt", loadZscores=TRUE)

    ## End(Not run)

    # Rank similar CMap perturbations
    compareKD <- rankSimilarPerturbations(diffExprStat, cmapPerturbationsKD)

    plot(compareKD, "spearman", c(7, 3))
    plot(compareKD, "pearson")
    plot(compareKD, "gsea")

[Package cTRAP version 1.5.0 Index]