Plot geometries without coloring — plotGeometry • Voyager

Different samples are plotted in separate facets.

Usage

plotGeometry(
  sfe,
  type,
  MARGIN = 2L,
  sample_id = "all",
  fill = TRUE,
  ncol = NULL,
  bbox = NULL,
  image_id = NULL,
  channel = NULL,
  maxcell = 5e+05,
  show_axes = FALSE,
  dark = FALSE,
  palette = colorRampPalette(c("black", "white"))(255)
)

Arguments

sfe: A SpatialFeatureExperiment object.
type: Name of the geometry associated with the MARGIN of interest for which to compute the graph.
MARGIN: Just like in apply, where 1 stands for row, 2 stands for column. Here, in addition, 3 stands for annotation, to query the annotGeometries, such as nuclei segmentation in a Visium data
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.
fill: Logical, whether to fill polygons.
ncol: Number of columns if plotting multiple features. Defaults to NULL, which means using the same logic as facet_wrap, which is used by patchwork's wrap_plots by default.
bbox: A bounding box to specify a smaller region to plot, useful when the dataset is large. Can be a named numeric vector with names "xmin", "xmax", "ymin", and "ymax", in any order. If plotting multiple samples, it should be a matrix with sample IDs as column names and "xmin", "ymin", "xmax", and "ymax" as row names. If multiple samples are plotted but bbox is a vector rather than a matrix, then the same bounding box will be used for all samples. You may see points at the edge of the geometries if the intersection between the bounding box and a geometry happens to be a point there. If NULL, then the entire tissue is plotted.
image_id: ID of the image to plot behind the geometries. If NULL, then not plotting images. Use imgData to see image IDs present. To plot multiple grayscale images as different RGB channels, use a named vector here, whose names are channel names (r, g, b), and values are image_ids of the corresponding images. The RGB colorization may not be colorblind friendly. When plotting multiple samples, it is assumed that the same image_id is used for each channel across different samples.
channel: Numeric vector indicating which channels in a multi-channel image to plot. If NULL, grayscale is plotted if there is 1 channel and RGB for the first 3 channels. The numeric vector can be named (r, g, b) to indicate which channel maps to which color. The RGB colorization may not be colorblind friendly. This argument cannot be specified while image_id is a named vector to plot different grayscale images as different channels.
maxcell: Maximum number of pixels to plot in the image. If the image is larger, it will be resampled so it have less than this number of pixels to save memory and for faster plotting. We recommend reducing this number when plotting multiple facets.
show_axes: Logical, whether to show axes.
dark: Logical, whether to use dark theme. When using dark theme, the palette will have lighter color represent higher values as if glowing in the dark. This is intended for plotting gene expression on top of fluorescent images.
palette: Vector of colors to use to color grayscale images.

Value

A ggplot object.

Examples

library(SFEData)
sfe1 <- McKellarMuscleData("small")
#> see ?SFEData and browseVignettes('SFEData') for documentation
#> loading from cache
sfe2 <- McKellarMuscleData("small2")
#> see ?SFEData and browseVignettes('SFEData') for documentation
#> downloading 1 resources
#> retrieving 1 resource
#> loading from cache
sfe <- cbind(sfe1, sfe2)
sfe <- removeEmptySpace(sfe)
plotGeometry(sfe, "spotPoly")

plotGeometry(sfe, "myofiber_simplified", MARGIN = 3)