diff dose_response.R @ 3:2aa9da0a84a4 draft default tip

planemo upload for repository https://github.com/Helmholtz-UFZ/galaxy-tools/tree/main/tools/tox_tools/dose_responses commit 707eca86fc2de2e563fb5c89889f54eb13f529d0

--- a/dose_response.R	Wed Dec 18 09:11:40 2024 +0000
+++ b/dose_response.R	Tue Jan 21 12:26:00 2025 +0000
@@ -26,7 +26,7 @@
     return(list(EC50 = ec50, EC25 = ec25, EC10 = ec10))
 }
 
-plot_dose_response <- function(model, data, ec_values, concentration_col, response_col, plot_file, compound_name, concentration_unit) {
+plot_dose_response <- function(model, data, ec_values, concentration_col, response_col, replicate_col, plot_file, compound_name, concentration_unit) {
     # Generate a grid of concentration values for predictions
     concentration_grid <- seq(min(data[[concentration_col]]), max(data[[concentration_col]]), length.out = 100)
     prediction_data <- data.frame(concentration_grid)
@@ -40,19 +40,21 @@
 
     print(prediction_data)
 
-    data$rep <- factor(data$rep)
+    # Ensure replicate_col is treated as a factor
+    data[[replicate_col]] <- factor(data[[replicate_col]])
 
     # Create the plot
     p <- ggplot(data, aes_string(x = concentration_col, y = response_col)) +
-        geom_point(aes(colour = rep)) + # Original data points
-        geom_line(data = prediction_data, aes_string(x = "conc", y = "resp"), color = "blue") + # Predicted curve
-        geom_ribbon(data = prediction_data, aes_string(x = "conc", ymin = "lower", ymax = "upper"), alpha = 0.2, fill = "blue") + # Confidence intervals
+        geom_point(aes_string(colour = replicate_col)) + # Original data points
+        geom_line(data = prediction_data, aes_string(x = concentration_col, y = response_col), color = "blue") + # Predicted curve
+        geom_ribbon(data = prediction_data, aes_string(x = concentration_col, ymin = "lower", ymax = "upper"), alpha = 0.2, fill = "blue") + # Confidence intervals
         geom_vline(xintercept = ec_values$EC10[1], color = "green", linetype = "dashed") +
         geom_vline(xintercept = ec_values$EC50[1], color = "red", linetype = "dashed") +
         labs(
             title = paste(compound_name, "- Dose-Response Curve"),
             x = paste("Dose [", concentration_unit, "]"),
-            y = "Response %"
+            y = "Response %",
+            colour = "Replicates"
         ) +
         theme_minimal() +
         theme(
@@ -66,10 +68,11 @@
     dev.off()
 }
 
-dose_response_analysis <- function(data, concentration_col, response_col, plot_file, ec_file, compound_name, concentration_unit) {
+dose_response_analysis <- function(data, concentration_col, response_col, replicate_col, plot_file, ec_file, compound_name, concentration_unit) {
     # Ensure column names are correctly selected
     concentration_col <- colnames(data)[as.integer(concentration_col)]
     response_col <- colnames(data)[as.integer(response_col)]
+    replicate_col <- colnames(data)[as.integer(replicate_col)]
 
     # Fit models and select the best one
     models <- fit_models(data, concentration_col, response_col)
@@ -81,7 +84,7 @@
     ec_values <- calculate_ec_values(best_model)
 
     # Plot the dose-response curve
-    plot_dose_response(best_model, data, ec_values, concentration_col, response_col, plot_file, compound_name, concentration_unit)
+    plot_dose_response(best_model, data, ec_values, concentration_col, response_col, replicate_col, plot_file, compound_name, concentration_unit)
 
     # Get model summary and AIC value
     model_summary <- summary(best_model)
@@ -108,11 +111,12 @@
 data_file <- args[1]
 concentration_col <- args[2]
 response_col <- args[3]
-plot_file <- args[4]
-ec_file <- args[5]
-compound_name <- args[6]
-concentration_unit <- args[7]
+replicate_col <- args[4]
+plot_file <- args[5]
+ec_file <- args[6]
+compound_name <- args[7]
+concentration_unit <- args[8]
 
 data <- read.csv(data_file, header = TRUE, sep = "\t")
 print(data)
-dose_response_analysis(data, concentration_col, response_col, plot_file, ec_file, compound_name, concentration_unit)
+dose_response_analysis(data, concentration_col, response_col, replicate_col, plot_file, ec_file, compound_name, concentration_unit)