Identify molecules of high variability — identifyVariableMolecules • SPATA2

Identfies molecules that are outliers on a mean-variability plot as proposed by Seurat.

identifyVariableMolecules(
  object,
  n_mol = 2500,
  method = "vst",
  assay_name = activeAssay(object),
  ...
)

Arguments

object: An object of class SPATA2 or, in case of S4 generics, objects of classes for which a method has been defined.
n_mol: Numeric value. The number of molecules to be identified. Given to nfeatures of Seurat::FindVariableFeatures().
method: Character value. The identification method. One of 'vst', 'mean.var.plot' or 'dispersion'. Given to selection.method of Seurat::FindVariableFeatures().
assay_name: Only relevant if the SPATA2 object contains more than one assay: Denotes the assay of interest and thus the molecular modality to use. Defaults to the active assay as set by activateAssay().
...: Used to absorb deprecated arguments or functions.

Value

The updated input object, containing the added, removed or computed results.

Examples


library(SPATA2)
data("example_data")

object <- loadExampleObject("UKF269T")

# default is method = 'vst'
object <- identifyVariableMolecules(object, n_mol = 2000)

# multiple results can be stored simultaneously
object <- identifyVariableMolecules(object, n_mol = 3000, method = "mean.var.plot")

# fails, cause results for two methods are stored and method = NULL
vars_vst <- getVariableMolecules(object)

vars_vst <- getVariableMoleculs(object, method = "vst") # works

# should work
vars_mvp <- getVariableMolecules(object, method = "mean.var.plot")

length(vars_vst)
length(vars_mvp)