Plot variogram maps

Plot variogram maps that show the variogram in all directions in a grid of distances in x and y coordinates.

Usage

plotVariogramMap(
  sfe,
  features,
  sample_id = "all",
  plot_np = FALSE,
  ncol = NULL,
  colGeometryName = NULL,
  annotGeometryName = NULL,
  reducedDimName = NULL,
  swap_rownames = NULL,
  name = "variogram_map"
)

Arguments

sfe

A SpatialFeatureExperiment object.

features

Features to plot, must be in rownames of the gene count matrix, colnames of colData or a colGeometry, colnames of cell embeddings in reducedDim, or numeric indices of dimension reduction components.

sample_id

Sample(s) in the SFE object whose cells/spots to use. Can be "all" to compute metric for all samples; the metric is computed separately for each sample.

plot_np

Logical, whether to plot the number of pairs in each distance bin instead of the variance.

ncol

Number of columns if facetting.

colGeometryName

Name of a colGeometry sf data frame whose numeric columns of interest are to be used to compute the metric. Use colGeometryNames to look up names of the sf data frames associated with cells/spots.

annotGeometryName

Name of a annotGeometry of the SFE object, to annotate the gene expression plot.

reducedDimName

Name of a dimension reduction, can be seen in reducedDimNames. colGeometryName and annotGeometryName have precedence over reducedDimName.

swap_rownames

Column name of rowData(object) to be used to identify features instead of rownames(object) when labeling plot elements. If not found in rowData, then rownames of the gene count matrix will be used.

name

Name under which the correlogram results are stored, which is by default "sp.correlogram".

Value

A ggplot object.

See also

plotVariogram

Examples

library(SFEData)
sfe <- McKellarMuscleData()
#> see ?SFEData and browseVignettes('SFEData') for documentation
#> loading from cache
sfe <- colDataUnivariate(sfe, "variogram_map", features = "nCounts",
width = 500, cutoff = 5000)
plotVariogramMap(sfe, "nCounts")