plotRPC {celda} | R Documentation

## Visualize perplexity differences of a list of celda models

### Description

Visualize perplexity differences of every model in a celdaList, by unique K/L combinations. Line represents centered moving average with windows of length `n`.

### Usage

    plotRPC(x, altExpName = "featureSubset", sep = 1, n = 10, alpha = 0.5)

    ## S4 method for signature 'SingleCellExperiment'
    plotRPC(x, altExpName = "featureSubset", sep = 1, n = 10, alpha = 0.5)

    ## S4 method for signature 'celdaList'
    plotRPC(x, sep = 1, n = 10, alpha = 0.5)

### Arguments

`x` | Can be one of A SingleCellExperiment object returned from `celdaGridSearch`, `recursiveSplitModule`, or `recursiveSplitCell`. Must contain a list named `"celda_grid_search"` in `metadata(x)`. celdaList object.
`altExpName` | The name for the altExp slot to use. Default "featureSubset".
`sep` | Numeric. Breaks in the x axis of the resulting plot.
`n` | Integer. Width of the rolling window. Default 10.
`alpha` | Numeric. Passed to geom_jitter. Opacity of the points. Values of alpha range from 0 to 1, with lower values corresponding to more transparent colors.

### Value

A ggplot plot object showing perplexity diferences as a function of clustering parameters.

### Examples

    data(sceCeldaCGGridSearch)
    sce <- resamplePerplexity(sceCeldaCGGridSearch)
    plotRPC(sce, n = 1)
    data(celdaCGSim, celdaCGGridSearchRes)
    ## Run various combinations of parameters with 'celdaGridSearch'
    celdaCGGridSearchRes <- resamplePerplexity(
      celdaCGSim$counts,
      celdaCGGridSearchRes)
    plotRPC(celdaCGGridSearchRes, n = 1)

[Package celda version 1.8.1 Index]