Remove spatial outliers

Removes data points that were identified as spatial outliers and all their related data. If no spatial outliers exist, the input object is returned as is.

removeSpatialOutliers(
  object,
  spatial_proc = TRUE,
  rm_var = TRUE,
  verbose = NULL
)

Arguments

object

An object of class SPATA2 or, in case of S4 generics, objects of classes for which a method has been defined.

spatial_proc

Logical value. Indicates whether the new sub-object is processed spatially. If TRUE, a new tissue outline is identified based on the remaining observations via identifyTissueOutline(). Then, spatial annotations are tested on being located on either of the remaining tissue sections. If they are not, they are removed.

If FALSE, these processing steps are skipped. Generally speaking, this is not recommended. Only set to FALSE, if you know what you're doing.

Only relevant, if barcodes is not NULL.

rm_var

Logical value. If TRUE, the variable sp_outlier is removed since it only contains FALSE after this function call and is of no value any longer.

verbose

Logical. If TRUE, informative messages regarding the computational progress will be printed.

(Warning messages will always be printed.)

Value

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

Examples


library(SPATA2)

data("example_data")

object <- example_data$object_UKF269T_diet

# spatial outliers have not been labeled histologically (= NA)
plotSurface(object, color_by = "histology")

object <- identifyTissueOutline(object) # step 1

plotSurface(object, color_by = "tissue_section")

object <- identifySpatialOutliers(object) # step 2

plotSurface(object, color_by = "sp_outlier")

nObs(object) # before removal

object <- removeSpatialOutliers(object) # step 3

plotSurface(object, color_by = "histology")

nObs(object) # after removal