modify network visualization plots to properly subset method tables a…

…ccording to required schemes. for dialect the subsetting is done based on the marginal driver mutation rates as specified in the manuscript and for mutual exclusivity only to include the pairs with rho values less than 0. MEGSA subsetting is done by retaining values with LRT s-score values greater than 0. the remaining p-value methods are modified to retain p-values less than 0.05

src/dialect/utils/plotting.py

@@ -34,6 +34,7 @@
 DECOY_GENE_COLOR = "#FFB3B3"  # Pastel red for decoy genes
 DRIVER_GENE_COLOR = "#A3C1DA"  # Blue-gray for driver genes
 EDGE_COLOR = "black"
+EPSILON = 0.02  # DIALECT Threshold for Tau_1X and Tau_X1
 
 
 # ---------------------------------------------------------------------------- #
@@ -160,6 +161,22 @@ def draw_network_gridplot_across_methods(
         top_ranking_pairs = results_df.sort_values(
             col, ascending=col != "MEGSA S-Score (LRT)"
         ).head(top_k)
+
+        if method == "DIALECT":
+            top_ranking_pairs = top_ranking_pairs[
+                (top_ranking_pairs["Rho"] < 0)
+                & (top_ranking_pairs["Tau_1X"] > EPSILON)
+                & (top_ranking_pairs["Tau_X1"] > EPSILON)
+            ]
+        elif method == "MEGSA":
+            top_ranking_pairs = top_ranking_pairs[top_ranking_pairs["MEGSA S-Score (LRT)"] > 0]
+        elif method == "DISCOVER":
+            top_ranking_pairs = top_ranking_pairs[top_ranking_pairs["Discover ME P-Val"] < 0.05]
+        elif method == "Fisher's Exact Test":
+            top_ranking_pairs = top_ranking_pairs[top_ranking_pairs["Fisher's ME P-Val"] < 0.05]
+        elif method == "WeSME":
+            top_ranking_pairs = top_ranking_pairs[top_ranking_pairs["WeSME P-Val"] < 0.05]
+
         edges = top_ranking_pairs[["Gene A", "Gene B"]].values
         G = nx.Graph()
         G.add_edges_from(edges)