plotValidate {GenomicSuperSignature} | R Documentation

## Plot validation results in an interactive graph

### Description

There are three main information on the graph:

- x-axis : Pearson correlation coefficient. Higher value means that test dataset and RAV is more tightly associated with.

- y-axis : Silhouette width representing the quality of RAVs.

- size : The number of studies in each RAV. (= cluster size)

- color : Test dataset's PC number that validate each RAV. Because we used top 8 PCs of the test dataset, there are 8 categories.

### Usage

    plotValidate(
      val_all,
      minClusterSize = 2,
      swFilter = FALSE,
      minSilhouetteWidth = 0,
      interactive = FALSE,
      minClSize = NULL,
      maxClSize = NULL,
      colorPalette = "Dark2"
    )

### Arguments

`val_all` | Output from validate function.
`minClusterSize` | The minimum size of clusters to be included in the plotting. Default value is 2, so any single-element clusters are excluded.
`swFilter` | If `swFilter=TRUE`, only RAV above the cutoff, defined through `minSilhouetteWidth` argument will be plotted. Default is `swFilter=FALSE`
`minSilhouetteWidth` | A minimum average silhouette width to be plotted. Only effective under `swFilter=TRUE` condition. Default is 0.
`interactive` | If set to `TRUE`, the output will be interactive plot. Default is `FALSE`.
`minClSize` | The minimum number of PCs in the clusters you want.
`maxClSize` | The maximum number of PCs in the clusters you want.
`colorPalette` | Default is `Dark2`. For other color options, please check `scale_color_brewer`

### Value

a ggplot object

### Examples

    data(miniRAVmodel)
    library(bcellViper)
    data(bcellViper)
    val_all <- validate(dset, miniRAVmodel)
    plotValidate(val_all)

[Package GenomicSuperSignature version 1.2.1 Index]