Plot geometries without coloring

Different samples are plotted in separate facets. When multiple geometries are plotted at the same time, they will be differentiated by color, by default using the dittoSeq palette, but this can be overridden with scale_color_* functions. Transcript spots of different genes are differentiated by point shape if plotted, so the number of genes plotted shouldn't exceed about 6 or a warning will be issued.

Usage

plotGeometry(
  sfe,
  type = deprecated(),
  MARGIN = deprecated(),
  colGeometryName = NULL,
  annotGeometryName = NULL,
  rowGeometryName = NULL,
  gene = "all",
  sample_id = "all",
  fill = TRUE,
  ncol = NULL,
  bbox = NULL,
  tx_alpha = 1,
  tx_size = 1,
  tx_file = NULL,
  image_id = NULL,
  channel = NULL,
  maxcell = 5e+05,
  show_axes = FALSE,
  dark = FALSE,
  palette = colorRampPalette(c("black", "white"))(255),
  normalize_channels = FALSE
)

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

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.

rowGeometryName

Name of a rowGeometry of the SFE object to plot.

gene

Character vector of names of genes to plot. If "all" then transcript spots of all genes are plotted.

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.

tx_alpha

Transparency for transcript spots, helpful when the transcript spots are overplotting.

tx_size

Point size for transcript spots.

tx_file

File path to GeoParquet file of the transcript spots if you don't wish to load all transcript spots into the SFE object. See formatTxSpots on generating such a GeoParquet file.

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.

normalize_channels

Logical, whether to normalize each channel of the image individually. Should be FALSE for bright field color images such as H&E but should set to TRUE for fluorescent 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, colGeometryName = "spotPoly")

plotGeometry(sfe, annotGeometryName = "myofiber_simplified")