This function allows for plotting of colabelled cells over either the "cfos" or "eyfp" channels. And allows for specification of specific brain regions to plot. Two different mouse attributes can be used as categorical variables to map to either the color or pattern aesthetics of the bar plot, e.g. sex and experimental group. The color aesthetic takes precedence over the pattern aesthetic so if you only want to use one mouse attribute, for plotting set it to the color_mapping parameter and set the pattern_mapping parameter to NULL.

This function allows for plotting of colabelled cells over either the "cfos" or "eyfp" channels. And allows for specification of specific brain regions to plot. Two different mouse attributes can be used as categorical variables to map to either the color or pattern aesthetics of the bar plot, e.g. sex and experimental group. The color aesthetic takes precedence over the pattern aesthetic so if you only want to use one mouse attribute, for plotting set it to the color_mapping parameter and set the pattern_mapping parameter to NULL.

Usage

plot_percent_colabel(
  e,
  colabel_channel = "colabel",
  channel = "eyfp",
  rois = c("AAA", "dDG", "HY"),
  color_mapping = "sex",
  colors = c("#952899", "#358a9c"),
  pattern_mapping = NULL,
  patterns = c("gray100", "hs_fdiagonal",
    "hs_horizontal\n                                              ", "gray90",
    "hs_vertical"),
  error_bar = "sem",
  ylim = c(0, 100),
  plot_individual = TRUE,
  height = 8,
  width = 8,
  print_plot = TRUE,
  save_plot = TRUE,
  image_ext = ".png"
)

Arguments

e

experiment object

channel

(str, default = "eyfp") The channel used as denominator in fraction counts.

rois

character vector of region acronyms, e.g. c("AAA", "DG)

color_mapping

(str, default = "sex") The name of the categorical variable (e.g., "sex", "age", etc.) to map to the color aesthetic of the bar plot.

colors

(str) character vector of the color values desired for the groups.

pattern_mapping

(str, default = "sex") The name of the categorical variable (e.g., "sex", "age", etc.) to map to the pattern aesthetic of the bar plot.

patterns

(str, default = c("gray100", 'hs_fdiagonal', "hs_horizontal", "gray90", "hs_vertical"), Pattern types to define subgroups.

error_bar

(str, c("sd", "sem)) options for which type of error bar to display, standard deviation or standard error of the mean.

Value

p Plot handle to the figure

Examples

plot_percentage_colabel
#> Error in eval(expr, envir, enclos): object 'plot_percentage_colabel' not found