plotRPC: Visualize perplexity differences of a list of celda models
In campbio/celda: CEllular Latent Dirichlet Allocation

plotRPC

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.

Usage

plotRPC(x, altExpName = "featureSubset", sep = 5, alpha = 0.5)

## S4 method for signature 'SingleCellExperiment'
plotRPC(x, altExpName = "featureSubset", sep = 5, alpha = 0.5)

## S4 method for signature 'celdaList'
plotRPC(x, sep = 5, 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.
`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 differences as a function of clustering parameters.

Examples

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

campbio/celda documentation built on April 5, 2024, 11:47 a.m.