plotRaster

Function based on ggplot2::geom_tile to visualize a rasterized spatial omics dataset represented as a SpatialExperiment object.

Usage

plotRaster(
  input,
  assay_name = NULL,
  feature_name = "sum",
  factor_levels = NULL,
  showLegend = TRUE,
  plotTitle = NULL,
  showAxis = FALSE,
  ...
)

Arguments

input

SpatialExperiment: Input data represented as a SpatialExperiment. The given SpatialExperiment is assumed to have an assay slot containing a features-by-observations matrix as dgCmatrix or matrix and a colData slot containing sfc_POLYGON geometry of pixels. The features-by-observations matrix is assumed to have either genes or cell types as features and pixels as observations.

assay_name

character: Name of the assay slot of the input that you want to visualize. If no argument is given, the first assay of the input would be visualized. This argument is useful when you have multiple assays stored in the input, and you want to visualize a specific assay. Default is NULL.

feature_name

character: Name of the feature in the input that you want to visualize. This argument is useful when you want to specify a feature you want to visualize. You can also use "sum" to visualize sum of all feature values per observation or "mean" to visualize mean of all feature values per observation. Default is "sum".

factor_levels

character or numeric or factor: An optional vector to convert and plot the input data as factor. This argument is useful if you want to plot categorical/ordinal variables, such as binarized occurrence of a specific cell type. factor_levels is fed into levels argument of the factor function in base R. Default is NULL.

showLegend

logical: Boolean to show the legend. Default is TRUE.

plotTitle

character: An optional argument to add a title to the resulting plot. Default is NULL.

showAxis

logical: Boolean to show axis title, texts, and ticks. Default is FALSE.

...

Additional parameters to pass to ggplot2::scale_fill_viridis_c if no argument is provided to factor_levels or ggplot2::scale_fill_viridis_d if a vector is provided to factor_levels. If you wish to use other color maps, we recommend overriding the resulting ggplot object.

Value

The output is returned as a ggplot object, where the input is visualized as ggplot2::geom_sf. Each pixel is plotted based on sfc_POLYGON geometry stored in the colData slot. Coloring of pixel represent the corresponding values of summarized (sum or mean) or specific feature (e.g. rasterized gene expression) per observation (pixel).

Examples

data("merfish_mousePOA")

# rasterize gene expression
out <- rasterizeGeneExpression(merfish_mousePOA, assay_name = "volnorm", fun = "mean")

# plot total rasterized gene expression per pixel (there is only one assay_name 
# in out and default for feature_name argument is "sum"; therefore, these arguments 
# are not specified)
plotRaster(out, name = "total rasterized gexp")


# plot rasterized expression of a specific gene/feature per pixel
plotRaster(out, feature_name = "Esr1", name = "Esr1")


# rasterize cell-type labels with user-defined resolution and hexagonal pixels
out <- rasterizeCellType(merfish_mousePOA, col_name = "celltype", resolution = 50, 
square = FALSE, fun = "sum")

# plot total cell counts per pixel (there is only one assay_name in out and default 
# for feature_name argument is "sum"; therefore, these arguments are not specified)
# here, let's use additional parameters for ggplot2::scale_fill_viridis_c so 
# that it would have a different color scheme from gene expression plots
plotRaster(out, name = "total cell counts", option = "inferno")


# plot specific cell type's cell counts per pixel
plotRaster(out, feature_name = "Inhibitory", name = "Inhibitory neuron counts", option = "inferno")