Prevent interactive variable collision

qhtcp-workflow/apps/r/calculate_interaction_zscores.R

@@ -357,23 +357,6 @@ calculate_interaction_scores <- function(df, max_conc, variables, group_vars = c
   calculations_joined <- df %>% select(-any_of(setdiff(names(calculations), c("OrfRep", "Gene", "num", "conc_num", "conc_num_factor"))))
   calculations_joined <- left_join(calculations_joined, calculations, by = c("OrfRep", "Gene", "num", "conc_num", "conc_num_factor"))
 
-
-
-  # # TODO for debug
-  # df_duplicates <- df %>%
-  # group_by(OrfRep, Gene, num) %>%
-  # filter(n() > 1)
-
-  # interactions_duplicates <- interactions %>%
-  #   group_by(OrfRep, Gene, num) %>%
-  #   filter(n() > 1)
-
-  # print(df_duplicates)
-  # print(interactions_duplicates)
-
-  
-
-
   interactions_joined <- df %>% select(-any_of(setdiff(names(interactions), c("OrfRep", "Gene", "num", "conc_num", "conc_num_factor"))))
   interactions_joined <- left_join(interactions_joined, interactions, by = c("OrfRep", "Gene", "num", "conc_num", "conc_num_factor"))
 
@@ -411,10 +394,10 @@ generate_and_save_plots <- function(output_dir, file_name, plot_configs, grid_la
     plot_base <- ggplot(df, aes_mapping)
 
     # Function to generate the plot
-    generate_plot <- function(interactive) {
+    generate_plot <- function(is_interactive) {
       # Use appropriate helper function based on plot type
       plot <- switch(config$plot_type,
-        "scatter" = generate_scatter_plot(plot_base, config, interactive = interactive),
+        "scatter" = generate_scatter_plot(plot_base, config, is_interactive = is_interactive),
         "box" = generate_box_plot(plot_base, config),
         "density" = plot_base + geom_density(),
         "bar" = plot_base + geom_bar(),
@@ -442,10 +425,10 @@ generate_and_save_plots <- function(output_dir, file_name, plot_configs, grid_la
     }
 
     # Generate the static plot
-    static_plot <- generate_plot(interactive = FALSE)
+    static_plot <- generate_plot(is_interactive = FALSE)
 
     # Generate the interactive plot
-    interactive_plot <- generate_plot(interactive = TRUE)
+    interactive_plot <- generate_plot(is_interactive = TRUE)
 
     # Convert to plotly object
     plotly_plot <- ggplotly(interactive_plot, tooltip = "text")
@@ -468,8 +451,7 @@ generate_and_save_plots <- function(output_dir, file_name, plot_configs, grid_la
   saveWidget(combined_plot, file = file.path(output_dir, paste0(file_name, ".html")), selfcontained = TRUE)
 }
 
-
-generate_scatter_plot <- function(plot, config, interactive = FALSE) {
+generate_scatter_plot <- function(plot, config, is_interactive = FALSE) {
   # Check for missing or out-of-range data
   missing_data <- config$df %>%
     filter(
@@ -497,8 +479,8 @@ generate_scatter_plot <- function(plot, config, interactive = FALSE) {
     )
   }
 
-  # Add the interactive `text` aesthetic if `interactive` is TRUE
-  if (interactive) {
+  # Add the interactive `text` aesthetic if `is_interactive` is TRUE
+  if (is_interactive) {
     if (!is.null(config$delta_bg_point) && config$delta_bg_point) {
       plot <- plot + geom_point(
         aes(text = paste("ORF:", OrfRep, "Gene:", Gene, "delta_bg:", delta_bg)),