Calculate and visualize perplexity of all models in a celdaList, with count resampling

Calculates the perplexity of each model's cluster assignments given the provided countMatrix, as well as resamplings of that count matrix, providing a distribution of perplexities and a better sense of the quality of a given K/L choice.

resamplePerplexity(
  x,
  celdaList,
  useAssay = "counts",
  altExpName = "featureSubset",
  resample = 5,
  seed = 12345
)

# S4 method for SingleCellExperiment
resamplePerplexity(
  x,
  useAssay = "counts",
  altExpName = "featureSubset",
  resample = 5,
  seed = 12345
)

# S4 method for ANY
resamplePerplexity(x, celdaList, resample = 5, seed = 12345)

Arguments

x	A numeric matrix of counts or a SingleCellExperiment returned from celdaGridSearch with the matrix located in the assay slot under useAssay. Rows represent features and columns represent cells. Must contain "celda_grid_search" slot in metadata(x) if x is a SingleCellExperiment object.
celdaList	Object of class 'celdaList'. Used only if x is a matrix object.
useAssay	A string specifying which assay slot to use if x is a SingleCellExperiment object. Default "counts".
altExpName	The name for the altExp slot to use. Default "featureSubset".
resample	Integer. The number of times to resample the counts matrix for evaluating perplexity. Default 5.
seed	Integer. Passed to with_seed. For reproducibility, a default value of 12345 is used. If NULL, no calls to with_seed are made.

Value

A SingleCellExperiment object or celdaList object with a perplexity property, detailing the perplexity of all K/L combinations that appeared in the celdaList's models.

Examples

data(sceCeldaCGGridSearch)
sce <- resamplePerplexity(sceCeldaCGGridSearch)
plotGridSearchPerplexity(sce)
data(celdaCGSim, celdaCGGridSearchRes)
celdaCGGridSearchRes <- resamplePerplexity(
  celdaCGSim$counts,
  celdaCGGridSearchRes
)
plotGridSearchPerplexity(celdaCGGridSearchRes)