diff --git a/src/gentropy/method/l2g/feature_factory.py b/src/gentropy/method/l2g/feature_factory.py
index b43125017..4c6d05a81 100644
--- a/src/gentropy/method/l2g/feature_factory.py
+++ b/src/gentropy/method/l2g/feature_factory.py
@@ -7,7 +7,6 @@
 import pyspark.sql.functions as f
 
 from gentropy.common.spark_helpers import (
-    convert_from_long_to_wide,
     convert_from_wide_to_long,
     get_record_with_maximum_value,
 )
@@ -121,12 +120,15 @@ def _get_max_coloc_per_credible_set(
             )
         ).drop("tmp_nbh_max_score", "local_max_score")
 
-        wide_df = convert_from_long_to_wide(
-            df=(
+        return L2GFeature(
+            _df=(
+                # Combine local and neighborhood metrics
                 local_max.unionByName(
                     neighbourhood_max, allowMissingColumns=True
-                ).withColumn(
-                    "featureName",
+                ).select(
+                    "studyLocusId",
+                    "geneId",
+                    # Feature name is a concatenation of the QTL type, colocalisation metric and if it's local or in the vicinity
                     f.concat_ws(
                         "",
                         f.col("right_studyType"),
@@ -134,31 +136,10 @@ def _get_max_coloc_per_credible_set(
                         f.col("colocalisationMetric"),
                         f.lit("Maximum"),
                         f.col("score_type"),
-                    ),
+                    ).alias("featureName"),
+                    f.col("max_score").alias("featureValue"),
                 )
             ),
-            id_vars=["studyLocusId", "geneId"],
-            var_name="featureName",
-            value_name="max_score",
-        )
-
-        return L2GFeature(
-            _df=convert_from_wide_to_long(
-                wide_df.groupBy("studyLocusId", "geneId").agg(
-                    *(
-                        f.first(f.col(c), ignorenulls=True).alias(c)
-                        for c in wide_df.columns
-                        if c
-                        not in [
-                            "studyLocusId",
-                            "geneId",
-                        ]
-                    )
-                ),
-                id_vars=("studyLocusId", "geneId"),
-                var_name="featureName",
-                value_name="featureValue",
-            ).filter(f.col("featureValue").isNotNull()),
             _schema=L2GFeature.get_schema(),
         )