Bar plot of cluster statistics for cells inside boundaries or ring regions

Creates a bar plot to visualize the distribution of cells inside spatial regions (e.g., boundaries or rings), either as raw counts or proportions per cluster. The plot is faceted by region_id to show statistics across multiple spatial subregions.

Usage

plotStatsBar(
  cell_stats = NULL,
  stat_column = c("proportion", "count"),
  colors = colors15_cheng,
  angle_x_label = 0,
  theme_ggplot = theme_spneigh()
)

Arguments

cell_stats

A data frame containing summarized cell statistics, typically the output from statsCellsInside(). Must include columns region_id, cluster, and the specified stat_column.

stat_column

Character. Column name in cell_stats to use for the y-axis. Options are "count" (number of cells) or "proportion" (relative fraction per region).

colors

A vector of cluster colors. Default uses colors15_cheng.

angle_x_label

Numeric angle (in degrees) to rotate the x-axis labels. Useful for improving label readability in faceted or dense plots. Default is 0 (no rotation).

theme_ggplot

A ggplot2 theme object. Default is theme_spneigh().

Value

A ggplot2 object showing a faceted bar plot of cell statistics per region.

Examples

coords <- readRDS(system.file("extdata", "MouseBrainCoords.rds",
    package = "SpNeigh"
))

boundary_points <- getBoundary(
    data = coords, one_cluster = 2,
    eps = 120, minPts = 10
)
boundary_points <- subset(boundary_points, region_id == 2) # (Optional)
cells_inside <- getCellsInside(data = coords, boundary = boundary_points)
stats_cells <- statsCellsInside(cells_inside)

plotStatsBar(stats_cells, stat_column = "proportion")

plotStatsBar(stats_cells, stat_column = "count")