#' animal_layer_point_ggplot_func
#'
#' Create a dot plot ggplot object layer on a base canvas plot. This function makes a dot plot by calculating the average value for each animal based on the cellular level, so it shows the average wave for each animal. Note: this function is wrapped inside the final superplot function.
#'
#' @param ggplot_obj A ggplot object. the base canvas plot which you want to add the layer to.
#' @param dataset A dataframe object. The dataset for analysis, eg wave kinetics or wave occurrence df.
#' @param xaxe A string. The variable you want to compare with. Default to `Animal`.
#' @param colored_by A string. The criteria to assigning color to the dots. Options possibles are by `animal_no` and by `animal_type`. Default to `animal_type`.
#' @param yaxe A string. The variable name of interest to plot.
#' @param my_grouping_vars Character vector. A character vector of groups names assigned to perform the cell aggregation. Don't change at least you know what you are doing!
#' @param jitter_width A double. Value assigned to the jitter width. Default to `3.5`.
#' @param animal_size A double. Value assigned to the size of the dots. Default to `2`.
#' @param animal_alpha A double. Value assigned to the transparency of the dots. Default to `0.4`.
#'
#' @return A ggplot object with a dotplot additional layer of individual Animal datapoints.
#' @export
#'
#' @examples # the example is missing
animal_layer_point_ggplot_func <- function(ggplot_obj,
dataset,
xaxe = "Animal",
my_grouping_vars = c("Animal_No", "Animal", "Condition", "Treatment", "Experiment"),
colored_by = "animal_type",
yaxe,
jitter_width = 3.5,
animal_size = 2,
animal_alpha = 0.4){
xaxe <- sym(xaxe)
yaxe <- sym(yaxe)
WT_fct <- dataset$Animal %>%
levels() %>%
dplyr::nth(1)
CPVT_fct <- dataset$Animal %>%
levels() %>%
dplyr::nth(2)
animal_level_data <- dataset %>%
# group_by(.data$Animal_No,
# .data$Animal,
# .data$Condition,
# .data$Experiment) %>%
group_by(across(any_of(my_grouping_vars))) %>%
summarise(across(where(is.double), # aggregate (averaging) by cells
~ mean(.x, na.rm = TRUE)), .groups = "drop_last") %>%
# group_by(.data$Animal_No,
# .data$Animal,
# .data$Condition) %>%
group_by(across(any_of(my_grouping_vars[!my_grouping_vars %in% "Experiment"]))) %>%
summarise(across(where(is.double), # aggregate (averaging) by Animal
~ mean(.x, na.rm = TRUE)), .groups = "drop_last")
switch (colored_by,
animal_no = ggplot_obj <- ggplot_obj +
ggnewscale::new_scale("fill") +
ggbeeswarm::geom_beeswarm(data = {animal_level_data %>%
filter(.data$Animal == WT_fct)},
ggplot2::aes(y = {{yaxe}},
fill = interaction({{xaxe}}, .data$Animal_No, sep = "_")),
priority = "density",
cex= jitter_width,
size = animal_size,
shape = 21,
alpha = animal_alpha) +
colorspace::scale_fill_discrete_sequential(palette = "Blues",
l2 = 50,
c2 = 10,
h2 = 200) +
ggnewscale::new_scale("fill") +
ggbeeswarm::geom_beeswarm(data = {animal_level_data %>%
filter(.data$Animal == CPVT_fct)},
ggplot2::aes(y = {{yaxe}},
fill = interaction({{xaxe}}, .data$Animal_No, sep = "_")),
priority = "density",
cex= jitter_width,
size = animal_size,
shape = 21,
alpha = animal_alpha) +
colorspace::scale_fill_discrete_sequential(palette ="Reds",
l1 = 10, l2 = 80,
c1 = 150, c2 = 200),
animal_type = ggplot_obj <- ggplot_obj +
ggnewscale::new_scale("fill") +
ggplot2::geom_point(data = animal_level_data,
shape = 21,
size = animal_size,
ggplot2::aes(fill = {{xaxe}},
group = {{xaxe}}),
color = "black",
alpha = animal_alpha,
position = ggplot2::position_jitterdodge(jitter.width = jitter_width, # add jitter
seed = 999)) +
ggplot2::scale_fill_manual(values = c("#666666", "#CC0000")),
stop("Invalid `colored_by` value. You must select a valid criteria for assigning color to the Animal plot layer. Options are: 1. `animal_type`, 2. `animal_no`")
)
rm(animal_level_data, xaxe, yaxe, WT_fct, CPVT_fct)
return(ggplot_obj)
}
Add the following code to your website.
For more information on customizing the embed code, read Embedding Snippets.