Replace existing summary stats in df

workflow/apps/r/calculate_interaction_zscores5.R

@@ -195,20 +195,22 @@ calculate_summary_stats <- function(df, variables, group_vars = c("conc_num", "c
         min = ~ifelse(all(is.na(.)), NA, min(., na.rm = TRUE)),
         sd = ~sd(., na.rm = TRUE),
         se = ~ifelse(sum(!is.na(.)) > 1, sd(., na.rm = TRUE) / sqrt(sum(!is.na(.)) - 1), NA)
-        # TODO: not in original stats but better to do here than in calculate_interactions?
-        # z_max = ~ifelse(sd(., na.rm = TRUE) == 0 | all(is.na(.)), NA,
-        #   (max(., na.rm = TRUE) - mean(., na.rm = TRUE)) / sd(., na.rm = TRUE))  # Z-score
       ), .names = "{.fn}_{.col}")
     )
 
-  # Join the summary stats back to the original dataframe
-  df_with_stats <- left_join(df, summary_stats, by = group_vars)
+  # Get the column names from the summary_stats dataframe (excluding the group_vars)
+  stat_columns <- setdiff(names(summary_stats), group_vars)
+
+  # Remove existing stats columns from df if they already exist
+  df_cleaned <- df %>% select(-any_of(stat_columns))
+
+  # Join the summary stats back to the cleaned original dataframe
+  df_with_stats <- left_join(df_cleaned, summary_stats, by = group_vars)
 
   # Return both the summary stats and the updated dataframe
   return(list(summary_stats = summary_stats, df_with_stats = df_with_stats))
 }
 
-
 # Calculate interaction scores
 calculate_interaction_scores <- function(df, max_conc, variables, group_vars = c("OrfRep", "Gene", "num")) {
 
@@ -651,9 +653,9 @@ main <- function() {
 
     # Filter data within and outside 2SD
     message("Filtering by 2SD of K")
-    df_na_within_2sd_k <- df_na %>%
+    df_na_within_2sd_k <- df_na_stats %>%
       filter(K >= (mean_K - 2 * sd_K) & K <= (mean_K + 2 * sd_K))
-    df_na_outside_2sd_k <- df_na %>%
+    df_na_outside_2sd_k <- df_na_stats %>%
       filter(K < (mean_K - 2 * sd_K) | K > (mean_K + 2 * sd_K))
 
     # Summary statistics for within and outside 2SD of K