filterSpataObject: Subset SPATA2 object with logical expressions

In theMILOlab/SPATA2: A Toolbox for Spatial Expression Analysis

Subset SPATA2 object with logical expressions

Description

This function filters a SPATA2 object based on specified logical expressions, retaining only the observations that meet the criteria. It has the same effect as the function subsetSpataObject() has, but it provides more convenient input options.

Note the . prefix before the arguments.

Usage

filterSpataObject(
  object,
  ...,
  .normalize = FALSE,
  .spatial_proc = TRUE,
  .verbose = TRUE
)

Arguments

object	An object of class SPATA2 or, in case of S4 generics, objects of classes for which a method has been defined.
...	<data-masking> Expressions that return a logical value, and are defined in terms of the variables in .data. If multiple expressions are included, they are combined with the & operator. Only rows for which all conditions evaluate to TRUE are kept.
.normalize	Logical value indicating whether numeric variables should be scaled to 0-1 before filtering. Default is FALSE.
.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.
.verbose	Logical. If TRUE, informative messages regarding the computational process will be printed. (Warning messages will always be printed.)

Details

The function filters the input SPATA2 object based on the logical expressions provided in .... If no expressions are provided, the function returns the input object with a warning. The variables used in the expressions are extracted and joined with the SPATA2 object's data frame. The observations that meet the criteria specified by the logical expressions are retained.

Value

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

See Also

joinWithVariables(), subsetSpataObject()

Examples

library(SPATA2)
library(patchwork)

object <- loadExampleObject("UKF269T", process = TRUE, meta = TRUE)

orig_frame <- ggpLayerFrameByCoords(object)

# exemplifies the effect of the 'normalize'
# note the value range
plotSurface(object, color_by = "SNAP25", normalize = TRUE)
plotSurface(object, color_by = "SNAP25", normalize = FALSE)

# another grouping variable for this example
plotSurface(object, color_by = "bayes_space")

# example 1: normalize = TRUE
object_sub1 <- filterSpataObject(object, SNAP25 > 0.5, .normalize = TRUE)

plotSurface(object_sub1) +
(plotSurface(object_sub1) + orig_frame)


# example 2: normalize = FALSE
object_sub2 <- filterSpataObject(object, SNAP25 > 0.5, .normalize = FALSE)

plotSurface(object_sub2, color_by = "SNAP25") +
(plotSurface(object_sub1) + orig_frame)

# example 3: logical tests can be more complex
object_sub3 <- filterSpataObject(object, GFAP > 0.5 | bayes_space %in% c("1", "3"), .normalize = TRUE)

plotSurface(object_sub3, color_by = "SNAP25") +
plotSurface(object_sub3, color_by = "bayes_space")

theMILOlab/SPATA2 documentation built on Feb. 8, 2025, 11:41 p.m.