Calculate global Moran for 1 to 2 variables.

Usage

globalMoran(
  spe,
  data1,
  data2 = data1[],
  at = c("grid", "cell"),
  nbrs_name = NULL,
  permutations = 999,
  seed = 123456789,
  cpu_threads = 6
)

Arguments

spe: A SpatialExperiment object.
data1: Numeric vector 1. Must be same length as nrow(spe@metadata$grid_density) or spatialCoords(spe), depending on 'at'.
data2: Numeric vector 2 for bivariate local Moran. Must be same length as data1.
at: Option of grid or cell for where to look for neighbour list
nbrs_name: Name of the neighbour list in spe@metadata$grid[[at]] for Moran's I
permutations: Number of permutations for p-value.
seed: Integer. For random permutations.
cpu_threads: (optional) The number of cpu threads used for parallel LISA computation

Value

List with global lisa, p.value, and vector of permuted lisa.

Examples

data("xenium_bc_spe")

## At grid.
spe <- gridDensity(spe, coi = "Breast cancer")
dat <- spe@metadata$grid_density$density_breast_cancer
spe <- findNbrsGrid(spe)
res <- globalMoran(spe,data1 = dat,at="grid")
res$lisa
#> [1] 0.9949741
## At cell.
dat <- as.numeric(spe$cell_type=="Breast cancer")
spe <- findNbrsSpatial(spe,k=10)
res <- globalMoran(spe,data1 = dat,at="cell")
res$lisa
#> [1] 0.09577329