spatialAnnotationScreening: The Spatial Annotation Screening algorithm
In theMILOlab/SPATA2: A Toolbox for Spatial Expression Analysis

spatialAnnotationScreening

R Documentation

The Spatial Annotation Screening algorithm

Description

Screens the sample for numeric variables that stand in meaningful, spatial relation to annotated structures/areas, spatial annotations. For a detailed explanation on how to define the parameters distance, resolution, angle_span and n_bins_angle see details section.

Usage

spatialAnnotationScreening(
  object,
  ids,
  variables,
  core,
  distance = "dte",
  resolution = recSgsRes(object),
  angle_span = c(0, 360),
  unit = getDefaultUnit(object),
  bcs_exclude = character(0),
  sign_var = "fdr",
  sign_threshold = 0.05,
  force_comp = FALSE,
  skip_comp = FALSE,
  model_add = NULL,
  model_subset = NULL,
  model_remove = NULL,
  estimate_R2 = TRUE,
  control = NULL,
  n_random = 10000,
  rm_zero_infl = TRUE,
  seed = 123,
  add_image = 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.
`ids`	Character vector. Specifies the IDs of the spatial annotations of interest.
`variables`	Character vector. The numeric variables to be included in the screening process. Makre sure that the correct matrix is active in the respective assays.
`distance`	`Distance measure`. Specifies the distance from the border of the spatial annotation to the horizon in the periphery up to which the screening is conducted. Defaults to a distance that covers the whole tissue section the spatial annotation is located on using `distToEdge()`. (This distance must not be exceeded.)
`resolution`	Distance measure. The resolution with which the expression gradient is inferred. Defaults are platform specific. See more in detail section of `recSgsRes()`.
`angle_span`	Numeric vector of length 2. Confines the area screened by an angle span relative to the center of its closest spatial annotation.
`unit`	Character value. Specifies the desired unit in which distance measures or area measures are provided. Run `validUnitsOfLength()` or `validUnitsOfArea()` for valid input options.
`bcs_exclude`	Character value containing the barcodes of observations to be excluded from the analysis.
`sign_var`	Either p_value or fdr. Defaults to fdr.
`sign_threshold`	The significance threshold. Defaults to 0.05.
`model_add`	Named list. Every slot in the list must be either a formula containing a function that takes a numeric vector as input and returns a numeric vector with the same length as its input vector. Or a numeric vector with the same length as the input vector. Test models with `showModels()`.
`model_subset`	Character value. Used as a regex to subset models. Use `validModelNames()` to obtain all model names that are known to `SPATA2` and `showModels()` to visualize them.
`model_remove`	Character value. Used as a regex to remove models are not supposed to be included.
`control`	A list of arguments as taken from `stats::loess.control()`. Default setting is stored in `SPATA2::sgs_loess_control`.
`n_random`	Number of random permutations for the significance testing of step 2.
`seed`	Numeric value. Sets the random seed.
`verbose`	Logical. If `TRUE`, informative messages regarding the computational progress will be printed. (Warning messages will always be printed.)
`...`	Used to absorb deprecated arguments or functions.

Value

An object of class SpatialAnnotationScreening.

Tutorials

Extensive tutorials for how to use this function can be found on our website https://themilolab.github.io/SPATA2/ .

Examples

library(SPATA2)

data("example_data")

object <- example_data$object_UKF313T_diet

object <- identifyTissueOutline(object)

ids <- getSpatAnnIds(object, tags = c("necrotic", "compr"), test = "all")

# opt 1 prefiltering by SPARKX is recommended, but not required
object <- runSPARKX(object)
genes <- getSparkxGenes(object, threshold_pval = 0.05)

# opt 2
genes <- getGenes(object)

sas_out <-
 spatialAnnotationScreening(
   object = object,
   ids = ids,
   variables = genes,
   core = FALSE
   )

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