plotRPC {celda} | R Documentation |
Visualize perplexity differences of every model in a celdaList,
by unique K/L combinations. Line represents centered moving average with
windows of length n
.
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)
x |
Can be one of
|
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. |
A ggplot plot object showing perplexity diferences as a function of clustering parameters.
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)