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Plot variogram

Source: R/gstat.R
plotVariogram.Rd

This function plots the variogram of a feature and its fitted variogram models, showing the nugget, range, and sill of the model. Unlike the plotting functions in package automap that uses lattice, this function uses ggplot2 to make prettier and more customizable plots.

Usage

plotVariogram(
  sfe,
  features,
  sample_id = "all",
  color_by = NULL,
  group = c("none", "sample_id", "features", "angles"),
  use_lty = TRUE,
  show_np = TRUE,
  ncol = NULL,
  colGeometryName = NULL,
  annotGeometryName = NULL,
  reducedDimName = NULL,
  divergent = FALSE,
  diverge_center = NULL,
  swap_rownames = NULL,
  name = "variogram"
)

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.

color_by

Name of a column in rowData(sfe) or in the featureData of colData (see colFeatureData), colGeometry, or annotGeometry by which to color the correlogram of each feature. Alternatively, a vector of the same length as features, or a data frame from clusterCorrelograms.

group

Which of samples, features, and angles to show in the same facet for comparison when there are multiple. Default to "none", meaning each facet will contain one variogram. When grouping multiple variograms in the same facet, the text with model, nugget, sill, and range of the variograms will not be shown.

use_lty

Logical, whether to use linetype or point shape to distinguish between the different features or samples in the same facet. If FALSE, then the different features or samples are not distinguished and the patterns are shown only.

show_np

Logical, whether to show number of pairs of cells at each distance bin.

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.

divergent

Logical, whether a divergent palette should be used.

diverge_center

If divergent = TRUE, the center from which the palette should diverge. If NULL, then not centering.

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. The empirical variogram at each distance bin is plotted as points, and the fitted variogram model is plotted as a line for each feature. The number next to each point is the number of pairs of cells in that distance bin.

See also

plotVariogramMap

Examples

library(SFEData)
sfe <- McKellarMuscleData()
#> see ?SFEData and browseVignettes('SFEData') for documentation
#> loading from cache
sfe <- colDataUnivariate(sfe, "variogram", features = "nCounts", model = "Sph")
plotVariogram(sfe, "nCounts")

# Anisotropy, will get a message
sfe <- colDataUnivariate(sfe, "variogram", features = "nCounts",
model = "Sph", alpha = c(30, 90, 150), name = "variogram_anis")
#> gstat does not fit anisotropic variograms. Variogram model is fitted to the whole dataset.
# Facet by angles by default
plotVariogram(sfe, "nCounts", name = "variogram_anis")

# Plot angles with different colors
plotVariogram(sfe, "nCounts", group = "angles", name = "variogram_anis")