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Set the cell plot node color scale

cell_node_scale_color.Rd

Controls how a column mapped with cell_plot(color = ...) is represented. Continuous versus categorical scales can be selected explicitly, or inferred from the mapped column. Palette, limits, and missing-value color are recorded here. Color scales are trained once across all panels, and continuous scales span the observed range unless limits are supplied. A continuous scale is therefore centered on zero only when limits are symmetric around zero, as in limits = c(-2, 2). Palette and missing-value colors must be fully opaque. Node opacity is controlled with cell_node_scale_alpha().

Usage

cell_node_scale_color(
  object,
  colors = NULL,
  limits = NULL,
  na_color = "grey50",
  type = c("auto", "continuous", "categorical")
)

Arguments

object

A cell_plot recipe.

colors

Optional vector of valid, fully opaque colors used for the scale. When NULL, the builder uses its default palette.

limits

Optional scale limits. Supply two ordered numeric values for a continuous scale or a character vector of levels for a categorical scale.

na_color

Fully opaque color used for missing values.

type

Scale type. "auto" determines the type from the mapped column.

Value

A modified cell_plot recipe.

Details

This modifier requires a color mapping. One color shared by every point is set with cell_plot(color = "red") instead.

See also

cell_plot()

Other cell-plot-modifiers: cell_annotation(), cell_grid(), cell_illuminate(), cell_node_depth(), cell_node_scale_alpha(), cell_node_scale_size(), cell_theme()

Examples

se <- ReadPNA_Seurat(minimal_pna_pxl_file())
#> ✔ Created a <Seurat> object with 5 cells and 158 targeted surface proteins
se <- LoadCellGraphs(se, cells = colnames(se)[4], verbose = FALSE) |>
  ComputeLayout(layout_method = "spectral")
#> ℹ Computing layouts for 1 graphs

cell_graph <- CellGraphs(se)[[4]]

layout_data <- FetchLayoutData(cell_graph, vars = "CD82", layout_method = "spectral_3d") |>
  # Downsample to speed up tests
  dplyr::slice_sample(n = 5000)

cell_plot(layout_data, color = CD82) |>
  cell_node_scale_color(colors = c("blue", "red"))


# One color for every point
cell_plot(layout_data, color = "red")