diff --git a/templates/aggregate_organisms.py b/templates/aggregate_organisms.py
index 5859fd8..250c5b8 100755
--- a/templates/aggregate_organisms.py
+++ b/templates/aggregate_organisms.py
@@ -85,8 +85,9 @@ def __init__(self):
             ).applymap(
                 bool
             )
+            self.has_edgeR_hits = True
         else:
-            self.edgeR_hits = False
+            self.has_edgeR_hits = False
 
         # Group the replicates by sample
         self.logger.info("Grouping replicates by sample")
@@ -253,7 +254,7 @@ def group_replicates(self) -> pd.DataFrame:
             hit=df.apply(self.classify_hit, axis=1),
             edgeR_hit=(
                 self.edgeR_hits.apply(self.classify_edgeR_hit, axis=1)
-                if self.edgeR_hits
+                if self.has_edgeR_hits
                 else None
             ),
             sample='!{sample_id}'
@@ -262,7 +263,7 @@ def group_replicates(self) -> pd.DataFrame:
             columns=dict(index="peptide")
         ).drop(
             columns=replicates + (
-                ["edgeR_hit"] if self.edgeR_hits else []
+                ["edgeR_hit"] if not self.has_edgeR_hits else []
             )
         )
 
@@ -290,7 +291,7 @@ def classify_hit(self, r):
         else:
             return "DISCORDANT"
 
-    def classify_edgeR_hit(self, r):
+    def classify_edgeR_hit(self, r: pd.Series) -> str:
         """
         Determine whether a peptide is a hit, or discordant - 
         based on edgeR hits.
@@ -430,7 +431,7 @@ def group_sample_organisms(
                         (f"n_edgeR_hits_{label}", (d["edgeR_hit"] == "TRUE").sum()),
                         (f"n_edgeR_discordant_{label}", (d["edgeR_hit"] == "DISCORDANT").sum()),
                     ]
-                    if self.edgeR_hits
+                    if self.has_edgeR_hits
                     else []
                 )
                 if k not in [