dViolins {DepecheR} | R Documentation

## Create violin plots for any variables of choise

### Description

Here, assymetrical violin plots for each cluster vs all other clusters are plotted for variables either retrieved from a depeche analysis or user-defined.

### Usage

    dViolins(
      clusterVector,
      inDataFrame,
      plotClusters = unique(clusterVector),
      plotElements = "all",
      colorOrder = plotClusters,
      colorScale = "viridis",
      plotDir = "dViolin_result",
      createOutput = TRUE
    )

### Arguments

`clusterVector` | Vector with the same length as inDataFrame containing information about the cluster identity of each observation.
`inDataFrame` | The data used to generate the depecheObject
`plotClusters` | This vector of numbers define which cluster(s) to plot the violins for. Defaults to all.
`plotElements` | This provides information on which features to plot. In the typical case, this is the essenceElementList from a depeche run. Other input formats are however accepted: if a vector of column names is provided, then these features will be plotted for all clusters. A custom list of features specific for each cluster is also accepted. A final alternative is to return "all" (default), in which case all markers will be plotted for all clusters.If more than a 100 markers are provided, however, this will return an error.
`colorOrder` | The order of the cluster colors. Defaults to the order that the unique values in clusterVector occurs.
`colorScale` | The color scale. Options identical to dColorVector.
`plotDir` | The name of the created directory.
`createOutput` | For testing purposes. Defaults to TRUE. If FALSE, no plots are generated.

### Value

One graph is created for each cluster, containing a bean per specified variable.

### See Also

`dDensityPlot`, `dColorPlot`, `dColorVector`, `depeche`

### Examples

    # Load some data
    data(testData)

    # Run the clustering function. For more rapid example execution,
    # a depeche clustering of the data is inluded
    # testDataDepeche <- depeche(testData[,2:15])
    data(testDataDepeche)

    # Create the plots of the variables that contribute to creating cluster 3
    dViolins(testDataDepeche$clusterVector, inDataFrame = testData,
        plotClusters = 3, plotElements = testDataDepeche$essenceElementList)

[Package DepecheR version 1.4.1 Index]