featurePlot: Plot spatial gene expression.

In BayesSpace: Clustering and Resolution Enhancement of Spatial Transcriptomes

Description

Plot spatial gene expression.

Usage

featurePlot(
  sce,
  feature,
  assay.type = "logcounts",
  diverging = FALSE,
  low = NULL,
  high = NULL,
  mid = NULL,
  color = NULL,
  platform = NULL,
  is.enhanced = NULL,
  ...
)

Arguments

sce	SingleCellExperiment. If feature is specified and is a string, it must exist as a row in the specified assay of sce.
feature	Feature vector used to color each spot. May be the name of a gene/row in an assay of sce, or a vector of continuous values.
assay.type	String indicating which assay in sce the expression vector should be taken from.
diverging	If true, use a diverging color gradient in featurePlot() (e.g. when plotting a fold change) instead of a sequential gradient (e.g. when plotting expression).
low, mid, high	Optional hex codes for low, mid, and high values of the color gradient used for continuous spot values.
color	Optional hex code to set color of borders around spots. Set to NA to remove borders.
platform	Spatial sequencing platform. If "Visium", the hex spot layout will be used, otherwise square spots will be plotted. NOTE: specifying this argument is only necessary if sce was not created by spatialCluster() or spatialEnhance().
is.enhanced	True if sce contains subspot-level data instead of spots. Spatial sequencing platform. If true, the respective subspot lattice for each platform will be plotted. NOTE: specifying this argument is only necessary if sce was not created by spatialCluster() or spatialEnhance().
...	Additional arguments for geom_polygon(). size, to specify the linewidth of these borders, is likely the most useful.

Value

Returns a ggplot object.

See Also

Other spatial plotting functions: clusterPlot()

Examples

sce <- exampleSCE()
featurePlot(sce, "gene_2")

BayesSpace documentation built on Nov. 8, 2020, 8:03 p.m.