Remove aes_string()

workflow/apps/r/calculate_interaction_zscores5.R

@@ -311,90 +311,14 @@ calculate_interaction_scores <- function(df_ref, df, max_conc, variables, group_
 }
 
 
-# generate_rf_plots <- function(df_calculations, df_interactions, output_dir, file_prefix = "RF") {
-#   variables <- c("Delta_L", "Delta_K", "Delta_r", "Delta_AUC")
-#   WT_sds <- list(WT_sd_l = 2, WT_sd_K = 2, WT_sd_r = 0.65, WT_sd_AUC = 6500)
-  
-#   plot_list <- lapply(seq_along(variables), function(i) {
-#     var <- variables[i]
-#     WT_sd <- WT_sds[[i]]
-    
-#     ggplot(df_calculations, aes(conc_num_factor, !!sym(var))) +
-#       geom_point() + geom_smooth(method = "lm", formula = y ~ x, se = FALSE) +
-#       coord_cartesian(ylim = c(-WT_sd, WT_sd)) +
-#       geom_errorbar(aes(ymin = 0 - (2 * WT_sd), ymax = 0 + (2 * WT_sd)), alpha = 0.3) +
-#       ggtitle(paste(df_calculations$OrfRep[1], df_calculations$Gene[1], sep = " ")) +
-#       annotate("text", x = 1, y = 0.9 * WT_sd, label = paste("ZShift =", round(df_interactions[[paste0("Z_Shift_", var)]], 2))) +
-#       annotate("text", x = 1, y = 0.7 * WT_sd, label = paste("lm Zscore =", round(df_interactions[[paste0("Z_lm_", var)]], 2))) +
-#       annotate("text", x = 1, y = -0.7 * WT_sd, label = paste("NG =", df_interactions$NG)) +
-#       annotate("text", x = 1, y = -0.9 * WT_sd, label = paste("DB =", df_interactions$DB)) +
-#       annotate("text", x = 1, y = -1.1 * WT_sd, label = paste("SM =", df_interactions$SM)) +
-#       scale_x_continuous(
-#         name = unique(df_calculations$Drug[1]),
-#         breaks = unique(df_calculations$conc_num_factor),
-#         labels = unique(as.character(df_calculations$conc_num))) +
-#       theme_publication()
-#   })
-  
-#   save_plots(file_prefix, plot_list, output_dir)
-# }
-
-# generate_summary_plots <- function(df, output_dir) {
-#   variables <- c("L", "K", "r", "AUC")
-#   plot_list <- lapply(variables, function(var) {
-#     generate_plot(df, x_var = "conc_num_factor", y_var = var, plot_type = "scatter", title = paste("Summary Plot for", var))
-#   })
-  
-#   save_plots("Summary_Plots", plot_list, output_dir)
-# }
-
-
-# # Generate ranked plots for a specific metric
-# generate_ranked_plot <- function(df, rank_var, zscore_var, sd_threshold, title_prefix) {
-#   ggplot(df, aes(x = {{rank_var}}, y = {{zscore_var}})) +
-#     ggtitle(paste(title_prefix, "above", sd_threshold, "SD")) +
-#     xlab("Rank") + ylab(paste("Avg Z score", title_prefix)) +
-#     annotate("rect", xmin = -Inf, xmax = Inf, ymin = sd_threshold, ymax = Inf, fill = "#542788", alpha = 0.3) +
-#     annotate("rect", xmin = -Inf, xmax = Inf, ymin = -sd_threshold, ymax = -Inf, fill = "orange", alpha = 0.3) +
-#     geom_hline(yintercept = c(-sd_threshold, sd_threshold)) +
-#     geom_point(size = 0.1, shape = 3) +
-#     theme_publication()
-# }
-
-# # Generate and save all ranked plots
-# generate_and_save_ranked_plots <- function(df, output_dir, prefix) {
-#   rank_metrics <- list(
-#     list("L_Rank", "Avg_Zscore_L", "L"),
-#     list("K_Rank", "Avg_Zscore_K", "K"),
-#     list("r_Rank", "Avg_Zscore_r", "r"),
-#     list("AUC_Rank", "Avg_Zscore_AUC", "AUC"),
-#     list("L_Rank_lm", "Z_lm_L", "L"),
-#     list("K_Rank_lm", "Z_lm_K", "K"),
-#     list("r_Rank_lm", "Z_lm_r", "r"),
-#     list("AUC_Rank_lm", "Z_lm_AUC", "AUC")
-#   )
-  
-#   pdf(file.path(output_dir, paste0(prefix, ".pdf")), width = 18, height = 12, onefile = TRUE)
-  
-#   for (sd_threshold in c(1, 2, 3)) {
-#     for (metric in rank_metrics) {
-#       plot <- generate_ranked_plot(df, sym(metric[[1]]), sym(metric[[2]]), sd_threshold, metric[[3]])
-#       print(plot)
-#     }
-#   }
-  
-#   dev.off()
-# }
-
-
-
-
 generate_plot <- function(df, x_var, y_var = NULL, plot_type, color_var = "conc_num",
   title, x_label = NULL, y_label = NULL, ylim_vals = NULL) {
-  plot <- ggplot(df, aes_string(x = x_var, color = color_var))
+
+  # Use tidy evaluation with aes() and !!sym() for dynamic column names
+  plot <- ggplot(df, aes(x = !!sym(x_var), color = !!sym(color_var)))
   
   if (!is.null(y_var)) {
-    plot <- plot + aes_string(y = y_var)
+    plot <- plot + aes(y = !!sym(y_var))
   }
   
   # Set up the plot based on the requested plot type