Tune ncomp using cross-validation.

CVTune_ncomp(
  reference,
  assayName = "logcounts",
  phenotypes = NULL,
  YY = NULL,
  center = TRUE,
  scale = FALSE,
  ncompLimits = c(1, 100),
  gridSize = 20,
  ncompGrid = NULL,
  selectedFeat = NULL,
  Kfolds = 5,
  regMethod = "PCA",
  labelCode = "-1,1",
  Ncores = 1,
  seed = 5202056,
  ncomp = NULL
)

Arguments

reference: SingleCellExperiment object.
assayName: Character.
phenotypes: Character.
YY: Matrix.
center: Logic.
scale: Logic.
ncompLimits: Vector.
gridSize: Integer.
ncompGrid: Vector.
selectedFeat: Vector.
Kfolds: Integer.
regMethod: Character.
labelCode: Character.
Ncores: Integer.
seed: Integer. The function sets the seed with withr::local_seed(), so the session's random-number state is restored on exit.
ncomp: Chosen number of components, or NULL to choose after the cross-validation: in an interactive session the function plots the loss and asks; otherwise it takes the grid value with the lowest loss.

Value

A list.