get_QC_plots_and_stats.R 7.17 KiB
#' Plot some QC plots for the bound data
#' @description
#' This plot can show trends within the dataset and run some basic statistics.
#'
#' @param .data The preprocessed data (after running make_count_dataframe() and change_data_format_to_longer()) merged data.frame that should be visualized
#' @param list_of_columns_to_plot The preprocessed data (after running make_count_dataframe() and change_data_format_to_longer()) merged data.frame that should be visualized
#' @param save_plots Boolean, TRUE if plots should be saved (default is FALSE)
#' @param saving_plots_folder String indicating the folder where the plots should be stored (default is "figures")
#' @param PID_column_name String, indicating the name of the sample to subset (default is "PID")
#' @param isolate_specific_drug String, indicating if there should be a Treatment specific data subset (default is NULL)
#' @param isolate_specific_patient String, indicating a spacific sample to plot only (default is NULL)
#' @param PID_column_name String, indicating the name of the sample to subset (default is "Treatment")
#' @param save_list_of_plots Boolean, if TRUE returns a named list of all the plots ran (default is TRUE), this can be usefult to isolate specific plots
#' @param save_plots_in_patient_specific_subfolders Boolean, if TRUE the plots will be saved (if `save_plots` TRUE) in sample specific folders (default is TRUE)
#' @param fill_color_variable Boolean, String, indicating the name of the variable (discrete) to use for the plot's filling
#' @param p_height Integer, indicate the plot's height (default is 10 inches)
#' @param p_width Integer, indicate the plot's width (default is 10 inches)
#' @param drug_column_name String, indicate the column indicating the Drug/Treament (default is "Treatment")
#'
#' @import ggplot2
#' @import ggpubr
#' @importFrom readr write_excel_csv
#' @importFrom dplyr filter
#' @return A `list`/`NULL`.
#' @example
#' ui <- get_QC_plots_parsed_merged_data(bind_data, save_plots = TRUE, save_list_of_plots = TRUE)
#' @export
get_QC_plots_parsed_merged_data <- function(.data,
list_of_columns_to_plot = NULL,
save_plots = FALSE,
saving_plots_folder = "figures",
save_plots_in_patient_specific_subfolders = TRUE,
fill_color_variable = NULL,
PID_column_name = "PID",
isolate_specific_drug = NULL,
isolate_specific_patient = NULL,
drug_column_name = "Treatment",
save_list_of_plots = TRUE,
p_height = 10,
p_width = 10) {
# List where plots could be stored
list_plottos <- list()
if (!is.data.frame(.data) | nrow(.data) < 1) stop("ERROR: the data provided must be not empty of dataframe type.")
# get the number of possible plotting variables
if (is.null(list_of_columns_to_plot)) {
list_of_columns_to_plot <- colnames(.data)[which(sapply(.data, is.numeric))]
}
# check that the fill_color_variable is in the dataset and not null
if (!is.null(fill_color_variable) & !fill_color_variable %in% colnames(.data)) stop("ERROR: the fill_color_variable must be in the colum names variables.")
# if the user decides to isolate a specific sample only
if (!is.null(isolate_specific_patient)) .data <- .data[.data[[PID_column_name]] == isolate_specific_patient, ]
for (pid in unique(.data[[PID_column_name]])) {
subset_data <- .data[.data[[PID_column_name]] == pid, ]
for (i in list_of_columns_to_plot) {
# if (!isolate_specific_drug %in% subset_data[[drug_column_name]] |> unique()) stop("ERROR: The `isolate_specific_drug` is not included in the name of the availble treaments.")
if (!is.null(isolate_specific_drug)) subset_data <- subset_data[subset_data[[drug_column_name]] %in% isolate_specific_drug, ]
if (nrow(subset_data) < 1) {
print(unique(subset_data[[PID_column_name]]))
print(unique(subset_data[[drug_column_name]]))
stop("ERROR: Your filtering query has returned no observations")
}
# browser()
# Function to dynamically add layers to a ggplot object based on conditions
add_violin_layers <- function(p, fill_color_variable) {
if (!is.null(fill_color_variable)) {
p <- p + geom_violin(trim = FALSE, aes_string(fill = fill_color_variable), color = NA) +
geom_boxplot(width = 0.1, fill = "white")
} else {
p <- p + geom_violin(trim = FALSE, fill = "#A4A4A4", color = "darkred") +
geom_boxplot(width = 0.1, fill = "white")
}
return(p)
}
# Initialize ggplot
p <- ggplot(subset_data, aes(x = Name, y = log2(unlist(subset_data[[i]]))))
# Add violin and boxplot layers
p <- add_violin_layers(p, fill_color_variable)
# More layers on top
p <- p + facet_wrap(~Treatment) +
theme(axis.text.x = element_text(angle = 45, hjust = 1)) +
labs(
title = colnames(subset_data[i]),
x = "Cell Markers",
y = paste0("Intensity of ", colnames(subset_data[i]), " (log2)"),
subtitle = paste0(pid, ".", isolate_specific_drug)
) +
geom_jitter(shape = 16, position = position_jitter(0.01)) +
stat_summary(geom = "crossbar", fun = mean, colour = "red", width = 0.21)
# Conditionally add to list of plots
if (save_list_of_plots) {
list_plottos[[paste0(isolate_specific_drug, ".", pid, ".", i)]] <- p
}
if (save_plots) {
if (save_plots_in_patient_specific_subfolders) {
if (!dir.exists(paste0(saving_plots_folder, "/", pid))) dir.create(paste0(saving_plots_folder, "/", pid), showWarnings = F, recursive = T)
ggsave(
plot = p,
filename = paste0(
paste0(saving_plots_folder, "/", pid),
"/",
Sys.Date(),
"_",
pid,
".",
isolate_specific_drug,
".",
colnames(.data[i]),
".pdf"
),
device = "pdf",
dpi = 600
)
} else {
# Saving plots in .pdf at 600 dpi
if (!dir.exists(saving_plots_folder)) dir.create(saving_plots_folder, showWarnings = F, recursive = T)
ggsave(
plot = p,
width = p_width,
height = p_height,
filename = paste0(
saving_plots_folder,
"/",
Sys.Date(), "_",
pid,
".",
isolate_specific_drug,
".",
colnames(.data[i]),
".pdf"
),
device = "pdf",
dpi = 600,
)
}
message(paste0(
"plots for: ",
pid,
".",
isolate_specific_drug,
".",
colnames(.data[i]), " saved"
))
}
}
}
}