Plot cell2location spatial results

Usage

Cell2locationPlot(
  object,
  plot_type = c("proportion", "abundance", "dominant", "pie"),
  cell_types = NULL,
  prefix = "Cell2location",
  tool_name = "Cell2location",
  image = NULL,
  overlay_image = TRUE,
  coord.cols = c("col", "row"),
  combine = TRUE,
  nrow = NULL,
  ncol = NULL,
  byrow = TRUE,
  image.scale = c("lowres", "hires"),
  srt = NULL,
  ...
)

Arguments

object: A Seurat object returned by RunCell2location().
plot_type: Result to draw: normalized proportion, q05 absolute abundance, dominant cell type, or a spot-level proportion pie.
cell_types: Optional cell types to display for abundance, proportion, or pie plots.
prefix: Metadata prefix used by RunCell2location().
tool_name: Name of the srt@tools result entry.
image: Spatial image name. Required when multiple images are present; a single image is selected automatically when NULL.
overlay_image: Whether to draw the selected spatial image.
coord.cols: Metadata coordinate columns used when no image is available.
combine: Whether to combine matrix or dominant point maps. If FALSE, return a named list of plots.
nrow, ncol, byrow: Point-map layout controls.
image.scale: Image scale factor matching the raster stored in the selected image. Use "hires" for a hires raster; do not modify Seurat scale-factor slots.
srt: Deprecated alias for object; supply exactly one of the two. It will be removed in scop 1.0.0.
...: Arguments passed to other functions.

Value

A ggplot, patchwork, or list of plots.

Details

Abundance plots use posterior q05 values. Proportion plots normalize these values across cell types within each spot. Matrix point maps share a default display range. Explicit cutoff or quantile arguments passed through ... retain the scales computed by SpatialSpotPlot(), including when returning separate panels. Saved plotting matrices retain every original spot; filtered observations have NA values, while cells records only the modeled spots. Older compact results are expanded only when their modeled IDs and dropped_spots record account for all missing rows. Unexplained missing or unknown IDs are errors.