identify_bordering_cells: identify_bordering_cells

In TrigosTeam/SPIAT: Spatial Image Analysis of Tissues

identify_bordering_cells

Description

Identify the cells bordering a group of cells of a particular phenotype, and calculate the number of clustered groups of this cell type.

Usage

identify_bordering_cells(
  spe_object,
  reference_cell,
  feature_colname = "Cell.Type",
  ahull_alpha = NULL,
  n_to_exclude = 10,
  plot_final_border = TRUE
)

Arguments

spe_object	SpatialExperiment object in the form of the output of format_image_to_spe.
reference_cell	String. Cells of this cell type will be used for border detection.
feature_colname	String that specifies the column of 'reference_cell'.
ahull_alpha	Number specifying the parameter for the alpha hull algorithm. The larger the number, the more cells will be included in one cell cluster.
n_to_exclude	Integer. Clusters with cell count under this number will be deleted.
plot_final_border	Boolean if plot the identified bordering cells.

Details

The bordering cell detection algorithm is based on computing an alpha hull (Hemmer et al., 2020), a generalization of convex hull (Green and Silverman, 1979). The cells detected to be on the alpha hull are identified as the bordering cells.

Value

A new SPE object is returned. The SPE object has a 'Region' column with "Border", "Inside" and "Outside" categories. The returned object also has an attribute saving the number of clusters.

Examples

spe_border <- identify_bordering_cells(SPIAT::defined_image,
reference_cell = "Tumour", feature_colname = "Cell.Type", n_to_exclude = 10)
n_clusters <- attr(spe_border, "n_of_clusters") # get the number of clusters
n_clusters

TrigosTeam/SPIAT documentation built on Aug. 22, 2024, 7:50 p.m.