get_QC_plots_parsed_merged_data {drugsens} | R Documentation |
Plot QC plots and calculate statistics for bound data
Description
This function creates quality control plots and calculates basic statistics for microscopy data. The plots provide visual insights into marker expression patterns and data quality.
Usage
get_QC_plots_parsed_merged_data(
.data,
list_of_columns_to_plot = NULL,
save_plots = FALSE,
saving_plots_folder = NULL,
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,
verbose = TRUE
)
Arguments
.data |
The preprocessed data frame to analyze |
list_of_columns_to_plot |
Columns to include in plots. If NULL, all numeric columns are used. |
save_plots |
Logical, whether to save plots to files. Defaults to FALSE. |
saving_plots_folder |
Directory for saving plots. If NULL and save_plots=TRUE, uses a subdirectory of tempdir(). |
save_plots_in_patient_specific_subfolders |
Logical, whether to create patient subdirectories. Defaults to TRUE. |
fill_color_variable |
Variable name for plot color filling |
PID_column_name |
Column name for patient IDs. Defaults to "PID". |
isolate_specific_drug |
Drug name to subset data |
isolate_specific_patient |
Patient ID to subset data |
drug_column_name |
Column name for drug information. Defaults to "Treatment". |
save_list_of_plots |
Logical, whether to return list of plot objects. Defaults to TRUE. |
p_height |
Plot height in inches. Defaults to 10. |
p_width |
Plot width in inches. Defaults to 10. |
verbose |
Logical, whether to show progress messages. Defaults to TRUE. |
Value
If save_list_of_plots=TRUE, returns a named list of ggplot objects. Otherwise returns invisible(NULL).
Examples
# First load and process example data
example_path <- system.file("extdata/to_merge/", package = "drugsens")
raw_data <- data_binding(path_to_the_projects_folder = example_path)
count_data <- make_count_dataframe(raw_data)
processed_data <- change_data_format_to_longer(count_data)
# Basic usage - create plots for all patients
plots <- get_QC_plots_parsed_merged_data(processed_data)
# Save plots to a temporary directory
temp_dir <- file.path(tempdir(), "qc_plots")
plots <- get_QC_plots_parsed_merged_data(
processed_data,
save_plots = TRUE,
saving_plots_folder = temp_dir
)
# Focus on a specific patient
plots <- get_QC_plots_parsed_merged_data(
processed_data,
isolate_specific_patient = "B39"
)
# Color plots by tissue type
plots <- get_QC_plots_parsed_merged_data(
processed_data,
fill_color_variable = "Tissue"
)