Remove existing df calls for single dplyr

qhtcp-workflow/apps/r/calculate_interaction_zscores.R

@@ -805,6 +805,17 @@ generate_correlation_plot_configs <- function(df, variables) {
   return(configs)
 }
 
+filter_and_print_non_finite <- function(df, vars_to_check, print_vars) {
+  non_finite_rows <- df %>% filter(if_any(all_of(vars_to_check), ~ !is.finite(.)))
+  
+  if (nrow(non_finite_rows) > 0) {
+    message("Removing the following non-finite rows:")
+    print(non_finite_rows %>% select(all_of(print_vars)), n = 200)
+  }
+  
+  df %>% filter(if_all(all_of(vars_to_check), is.finite))
+}
+
 main <- function() {
   lapply(names(args$experiments), function(exp_name) {
     exp <- args$experiments[[exp_name]]
@@ -821,18 +832,14 @@ main <- function() {
     print_vars <- c("OrfRep", "Plate", "scan", "Col", "Row", "num", "OrfRep", "conc_num", "conc_num_factor",
       "delta_bg_tolerance", "delta_bg", "Gene", "L", "K", "r", "AUC", "NG", "DB")
     
-    message("Loading and filtering data")
-    df <- load_and_process_data(args$easy_results_file, sd = exp_sd)
-    df <- update_gene_names(df, args$sgd_gene_list)
-    df <- as_tibble(df)
+    message("Loading and filtering data for experiment: ", exp_name)
+    df <- load_and_process_data(args$easy_results_file, sd = exp_sd) %>%
+      update_gene_names(args$sgd_gene_list) %>%
+      as_tibble()
 
-    # Filter rows that are above tolerance for quality control plots
+    # Quality Control: Filter rows above tolerance
     df_above_tolerance <- df %>% filter(DB == 1)
-
-    # Set L, r, K, AUC (and delta_bg?) to NA for rows that are above tolerance
     df_na <- df %>% mutate(across(all_of(summary_vars), ~ ifelse(DB == 1, NA, .)))
-
-    # Remove rows with 0 values in L
     df_no_zeros <- df_na %>% filter(L > 0)
     
     # Save some constants
@@ -842,17 +849,8 @@ main <- function() {
 
     message("Calculating summary statistics before quality control")
     ss <- calculate_summary_stats(df, summary_vars, group_vars = group_vars)
-    # df_ss <- ss$summary_stats
     df_stats <- ss$df_with_stats
-    df_filtered_stats <- df_stats %>%
-      {
-        non_finite_rows <- filter(., if_any(c(L), ~ !is.finite(.)))
-        if (nrow(non_finite_rows) > 0) {
-          message("Filtering out the following non-finite rows:")
-          print(non_finite_rows %>% select(any_of(print_vars)), n = 200)
-        }
-        filter(., if_all(c(L), is.finite))
-      }
+    df_filtered_stats <- filter_and_print_non_finite(df_stats, "L", print_vars)
 
     message("Calculating summary statistics after quality control")
     ss <- calculate_summary_stats(df_na, summary_vars, group_vars = group_vars)
@@ -860,28 +858,12 @@ main <- function() {
     df_na_stats <- ss$df_with_stats
     write.csv(df_na_ss, file = file.path(out_dir, "summary_stats_all_strains.csv"), row.names = FALSE)
     # Filter out non-finite rows for plotting
-    df_na_filtered_stats <- df_na_stats %>%
-      {
-        non_finite_rows <- filter(., if_any(c(L), ~ !is.finite(.)))
-        if (nrow(non_finite_rows) > 0) {
-          message("Removed the following non-finite rows:")
-          print(non_finite_rows %>% select(any_of(print_vars)), n = 200)
-        }
-        filter(., if_all(c(L), is.finite))
-      }
+    df_na_filtered_stats <- filter_and_print_non_finite(df_na_stats, "L", print_vars)
 
     message("Calculating summary statistics after quality control excluding zero values")
     ss <- calculate_summary_stats(df_no_zeros, summary_vars, group_vars = group_vars)
     df_no_zeros_stats <- ss$df_with_stats
-    df_no_zeros_filtered_stats <- df_no_zeros_stats %>%
-      {
-        non_finite_rows <- filter(., if_any(c(L), ~ !is.finite(.)))
-        if (nrow(non_finite_rows) > 0) {
-          message("Removed the following non-finite rows:")
-          print(non_finite_rows %>% select(any_of(print_vars)), n = 200)
-        }
-        filter(., if_all(c(L), is.finite))
-      }
+    df_no_zeros_filtered_stats <- filter_and_print_non_finite(df_no_zeros_stats, "L", print_vars)
 
     message("Filtering by 2SD of K")
     df_na_within_2sd_k <- df_na_stats %>%
@@ -892,18 +874,12 @@ main <- function() {
     message("Calculating summary statistics for L within 2SD of K")
     # TODO We're omitting the original z_max calculation, not sure if needed?
     ss <- calculate_summary_stats(df_na_within_2sd_k, "L", group_vars = c("conc_num", "conc_num_factor"))
-    l_within_2sd_k_ss <- ss$summary_stats
-    df_na_l_within_2sd_k_stats <- ss$df_with_stats
-    write.csv(l_within_2sd_k_ss,
-      file = file.path(out_dir_qc, "max_observed_L_vals_for_spots_within_2sd_K.csv"), row.names = FALSE)
+    write.csv(ss$summary_stats, file = file.path(out_dir_qc, "max_observed_L_vals_for_spots_within_2sd_K.csv"), row.names = FALSE)
     
     message("Calculating summary statistics for L outside 2SD of K")
     ss <- calculate_summary_stats(df_na_outside_2sd_k, "L", group_vars = c("conc_num", "conc_num_factor"))
-    l_outside_2sd_k_ss <- ss$summary_stats
-    df_na_l_outside_2sd_k_stats <- ss$df_with_stats
-    write.csv(l_outside_2sd_k_ss,
-      file = file.path(out_dir, "max_observed_L_vals_for_spots_outside_2sd_K.csv"), row.names = FALSE)
-
+    write.csv(ss$summary_stats, file = file.path(out_dir, "max_observed_L_vals_for_spots_outside_2sd_K.csv"), row.names = FALSE)
+    
     # Each plots list corresponds to a file
     message("Generating quality control plot configurations")
     l_vs_k_plots <- list(