plot.perturbationChanges {cTRAP} | R Documentation

## Operations on a `perturbationChanges` object

### Description

Operations on a `perturbationChanges` object

### Usage

    ## S3 method for class 'perturbationChanges'
    plot(
      x,
      perturbation,
      input,
      method = c("spearman", "pearson", "gsea"),
      geneSize = 150,
      genes = c("both", "top", "bottom"),
      ...,
      title = NULL
    )

    ## S3 method for class 'perturbationChanges'
    x[i, j, drop = FALSE, ...]

    ## S3 method for class 'perturbationChanges'
    dim(x)

    ## S3 method for class 'perturbationChanges'
    dimnames(x)

### Arguments

`x` | `perturbationChanges` object
`perturbation` | Character (perturbation identifier) or a `similarPerturbations` table (from which the respective perturbation identifiers are retrieved)
`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`)
`method` | Character: comparison method (`spearman`, `pearson` or `gsea`; multiple methods may be selected at once)
`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
`genes` | Character: when plotting gene set enrichment analysis (GSEA), plot most up-regulated genes (`genes = "top"`), most down-regulated genes (`genes = "bottom"`) or both (`genes = "both"`); only used if `method = "gsea"` and `geneset = NULL`
`...` | Extra arguments
`title` | Character: plot title (if `NULL`, the default title depends on the context; ignored when plotting multiple perturbations)
`i, j` | Character or numeric indexes specifying elements to extract
`drop` | Boolean: coerce result to the lowest possible dimension?

### Value

Subset, plot or return dimensions or names of a `perturbationChanges` object

### See Also

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

### Examples

    data("diffExprStat")
    data("cmapPerturbationsKD")

    compareKD <- rankSimilarPerturbations(diffExprStat, cmapPerturbationsKD)
    EIF4G1knockdown <- grep("EIF4G1", compareKD[[1]], value=TRUE)
    plot(cmapPerturbationsKD, EIF4G1knockdown, diffExprStat, method="spearman")
    plot(cmapPerturbationsKD, EIF4G1knockdown, diffExprStat, method="pearson")
    plot(cmapPerturbationsKD, EIF4G1knockdown, diffExprStat, method="gsea")

    data("cmapPerturbationsCompounds")
    pert <- "CVD001_HEPG2_24H:BRD-A14014306-001-01-1:4.1"
    plot(cmapPerturbationsCompounds, pert, diffExprStat, method="spearman")
    plot(cmapPerturbationsCompounds, pert, diffExprStat, method="pearson")
    plot(cmapPerturbationsCompounds, pert, diffExprStat, method="gsea")

    # Multiple cell line perturbations
    pert <- "CVD001_24H:BRD-A14014306-001-01-1:4.1"
    plot(cmapPerturbationsCompounds, pert, diffExprStat, method="spearman")
    plot(cmapPerturbationsCompounds, pert, diffExprStat, method="pearson")
    plot(cmapPerturbationsCompounds, pert, diffExprStat, method="gsea")

[Package cTRAP version 1.10.1 Index]