Summarize linear model coefficeints for correlation plots

qhtcp-workflow/apps/r/calculate_interaction_zscores.R

@@ -416,6 +416,18 @@ calculate_interaction_scores <- function(df, df_bg, type, overlap_threshold = 2)
       R_Squared_r = first(R_Squared_r),
       R_Squared_AUC = first(R_Squared_AUC),
 
+      # lm intercepts
+      lm_intercept_L = first(lm_intercept_L),
+      lm_intercept_K = first(lm_intercept_K),
+      lm_intercept_r = first(lm_intercept_r),
+      lm_intercept_AUC = first(lm_intercept_AUC),
+
+      # lm slopes
+      lm_slope_L = first(lm_slope_L),
+      lm_slope_K = first(lm_slope_K),
+      lm_slope_r = first(lm_slope_r),
+      lm_slope_AUC = first(lm_slope_AUC),
+
       # NG, DB, SM values
       NG = first(NG),
       DB = first(DB),
@@ -439,7 +451,7 @@ calculate_interaction_scores <- function(df, df_bg, type, overlap_threshold = 2)
         TRUE ~ "No Effect"
       ),
       
-      # For correlations
+      # For correlation plots
       lm_R_squared_L = if (!all(is.na(Z_lm_L)) && !all(is.na(Avg_Zscore_L))) summary(lm(Z_lm_L ~ Avg_Zscore_L))$r.squared else NA,
       lm_R_squared_K = if (!all(is.na(Z_lm_K)) && !all(is.na(Avg_Zscore_K))) summary(lm(Z_lm_K ~ Avg_Zscore_K))$r.squared else NA,
       lm_R_squared_r = if (!all(is.na(Z_lm_r)) && !all(is.na(Avg_Zscore_r))) summary(lm(Z_lm_r ~ Avg_Zscore_r))$r.squared else NA,
@@ -1208,12 +1220,11 @@ generate_correlation_plot_configs <- function(df) {
       x_var <- paste0("Z_lm_", rel$x)
       y_var <- paste0("Z_lm_", rel$y)
 
-      # Access the correlation statistics from the correlation_stats list
+      # Extract the R-squared, intercept, and slope from the df
       relationship_name <- paste0(rel$x, "_vs_", rel$y)  # Example: L_vs_K
-      stats <- correlation_stats[[relationship_name]]
-      intercept <- stats$intercept
-      slope <- stats$slope
-      r_squared <- stats$r_squared
+      intercept <- mean(df[[paste0("lm_intercept_", rel$x)]], na.rm = TRUE)
+      slope <- mean(df[[paste0("lm_slope_", rel$x)]], na.rm = TRUE)
+      r_squared <- mean(df[[paste0("lm_R_squared_", rel$x)]], na.rm = TRUE)
 
       # Generate the label for the plot
       plot_label <- paste("Interaction", rel$x, "vs.", rel$y)