Perform kernel density estimation on SpatialExperiment for cell types of interest

Usage

gridDensity(
  spe,
  id = if (isVisium != "none") NULL else "cell_type",
  coi = NULL,
  feature = NULL,
  assay = "counts",
  kernel = "gaussian",
  bandwidth = NULL,
  ngrid.x = NULL,
  grid.length.x = NULL,
  diggle = FALSE,
  grid.type = c("hex", "square"),
  isVisium = c("none", "visium", "visiumHD")
)

Arguments

spe: A SpatialExperiment object.
id: A character. The name of the column of colData(spe) containing the cell type identifiers. Set to cell_type by default. Set to NULL for overall density.
coi: A character vector of cell types of interest (COIs). Default to all cell types.
feature: Feature(s) to calculate density with. Must be in rownames(spe).
assay: Name of assay to use for finding feature(s).
kernel: The smoothing kernel. Options are "gaussian", "epanechnikov", "quartic" or "disc". For hexagonal grid, only Gaussian is implemented
bandwidth: The smoothing bandwidth. By default performing automatic bandwidth selection using cross-validation using function spatstat.explore::bw.diggle.
ngrid.x: Number of grids in the x-direction. Ignored when 'grid.length.x' is specified. Default to NULL.
grid.length.x: Grid length in the x-direction. If both 'ngrid.x' and 'grid.length.x' are NULL, then 'grid.length.x' is set to 100 (micron) by default.
diggle: Logical. If TRUE, use the Jones-Diggle improved edge correction. See spatstat.explore::density.ppp() for details.
grid.type: Type of grid can be either hexagon or square.
isVisium: Options of 'none','visium', and 'visiumHD'. If TRUE, converts coordinates from pixel to um and fit the density grid to the same Visium spots arrangement. visium will use hexagonal while visiumHD will use rectangular grid.

Value

A SpatialExperiment object. Grid density estimates for all cell type of interest are stored in spe@metadata$grid_density. Grid information is stored in spe@metadata$grid_info

Examples


data("xenium_bc_spe")

spe <- gridDensity(spe)