Calculate the perplexity of a celda model

Perplexity is a statistical measure of how well a probability model can predict new data. Lower perplexity indicates a better model.

perplexity(
  x,
  celdaMod,
  useAssay = "counts",
  altExpName = "featureSubset",
  newCounts = NULL
)

# S4 method for SingleCellExperiment,ANY
perplexity(
  x,
  useAssay = "counts",
  altExpName = "featureSubset",
  newCounts = NULL
)

# S4 method for ANY,celda_CG
perplexity(x, celdaMod, newCounts = NULL)

# S4 method for ANY,celda_C
perplexity(x, celdaMod, newCounts = NULL)

# S4 method for ANY,celda_G
perplexity(x, celdaMod, newCounts = NULL)

Arguments

x	Can be one of A SingleCellExperiment object returned by celda_C, celda_G or celda_CG, with the matrix located in the useAssay assay slot. Rows represent features and columns represent cells. Integer counts matrix. Rows represent features and columns represent cells. This matrix should be the same as the one used to generate celdaMod.
celdaMod	Celda model object. Only works if x is an integer counts matrix.
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".
newCounts	A new counts matrix used to calculate perplexity. If NULL, perplexity will be calculated for the matrix in useAssay slot in x. Default NULL.

Value

Numeric. The perplexity for the provided x (and celdaModel).

Examples

data(sceCeldaCG)
perplexity <- perplexity(sceCeldaCG)
data(celdaCGSim, celdaCGMod)
perplexity <- perplexity(celdaCGSim$counts, celdaCGMod)
data(celdaCSim, celdaCMod)
perplexity <- perplexity(celdaCSim$counts, celdaCMod)
data(celdaGSim, celdaGMod)
perplexity <- perplexity(celdaGSim$counts, celdaGMod)