diff --git a/src/gentropy/dataset/l2g_feature_matrix.py b/src/gentropy/dataset/l2g_feature_matrix.py
index 948477600..e5be1a019 100644
--- a/src/gentropy/dataset/l2g_feature_matrix.py
+++ b/src/gentropy/dataset/l2g_feature_matrix.py
@@ -5,8 +5,6 @@
 from functools import reduce
 from typing import TYPE_CHECKING, Type
 
-from pyspark.sql.functions import col
-
 from gentropy.common.schemas import parse_spark_schema
 from gentropy.common.spark_helpers import convert_from_long_to_wide
 from gentropy.dataset.dataset import Dataset
@@ -62,22 +60,13 @@ def generate_features(
         Raises:
             ValueError: If the feature matrix is empty
         """
-        coloc_methods = (
-            colocalisation.df.select("colocalisationMethod")
-            .distinct()
-            .toPandas()["colocalisationMethod"]
-            .tolist()
-        )
         if features_dfs := [
             # Extract features
             ColocalisationFactory._get_max_coloc_per_credible_set(
+                colocalisation,
                 credible_set,
                 study_index,
-                colocalisation.filter(col("colocalisationMethod") == method),
-                method,
-            ).df
-            for method in coloc_methods
-        ] + [
+            ).df,
             StudyLocusFactory._get_tss_distance_features(credible_set, variant_gene).df,
             StudyLocusFactory._get_vep_features(credible_set, variant_gene).df,
         ]:
diff --git a/src/gentropy/method/l2g/feature_factory.py b/src/gentropy/method/l2g/feature_factory.py
index 4c6d05a81..3b9b5b278 100644
--- a/src/gentropy/method/l2g/feature_factory.py
+++ b/src/gentropy/method/l2g/feature_factory.py
@@ -26,16 +26,16 @@ class ColocalisationFactory:
 
     @staticmethod
     def _get_max_coloc_per_credible_set(
+        colocalisation: Colocalisation,
         credible_set: StudyLocus,
         studies: StudyIndex,
-        colocalisation: Colocalisation,
     ) -> L2GFeature:
         """Get the maximum colocalisation posterior probability for each pair of overlapping study-locus per type of colocalisation method and QTL type.
 
         Args:
+            colocalisation (Colocalisation): Colocalisation dataset
             credible_set (StudyLocus): Study locus dataset
             studies (StudyIndex): Study index dataset
-            colocalisation (Colocalisation): Colocalisation dataset
 
         Returns:
             L2GFeature: Stores the features with the max coloc probabilities for each pair of study-locus
@@ -62,7 +62,9 @@ def _get_max_coloc_per_credible_set(
                 credible_set.df.join(
                     studies.df.select("studyId", "studyType", "geneId"), "studyId"
                 ).selectExpr(
-                    "studyLocusId as rightStudyLocusId", "studyType as right_studyType"
+                    "studyLocusId as rightStudyLocusId",
+                    "studyType as right_studyType",
+                    "geneId",
                 ),
                 on="rightStudyLocusId",
                 how="inner",
@@ -135,9 +137,9 @@ def _get_max_coloc_per_credible_set(
                         f.lit("Coloc"),
                         f.col("colocalisationMetric"),
                         f.lit("Maximum"),
-                        f.col("score_type"),
+                        f.regexp_replace(f.col("score_type"), "Local", ""),
                     ).alias("featureName"),
-                    f.col("max_score").alias("featureValue"),
+                    f.col("max_score").cast("float").alias("featureValue"),
                 )
             ),
             _schema=L2GFeature.get_schema(),
diff --git a/tests/gentropy/method/test_locus_to_gene.py b/tests/gentropy/method/test_locus_to_gene.py
index 3976406c9..898252f9f 100644
--- a/tests/gentropy/method/test_locus_to_gene.py
+++ b/tests/gentropy/method/test_locus_to_gene.py
@@ -80,30 +80,21 @@ def test_train(
 class TestColocalisationFactory:
     """Test the ColocalisationFactory methods."""
 
-    @pytest.mark.parametrize(
-        "colocalisation_method",
-        [
-            "COLOC",
-            "eCAVIAR",
-        ],
-    )
     def test_get_max_coloc_per_credible_set(
         self: TestColocalisationFactory,
         mock_study_locus: StudyLocus,
         mock_study_index: StudyIndex,
         mock_colocalisation: Colocalisation,
-        colocalisation_method: str,
     ) -> None:
         """Test the function that extracts the maximum log likelihood ratio for each pair of overlapping study-locus returns the right data type."""
         coloc_features = ColocalisationFactory._get_max_coloc_per_credible_set(
+            mock_colocalisation,
             mock_study_locus,
             mock_study_index,
-            mock_colocalisation,
-            colocalisation_method,
         )
         assert isinstance(
             coloc_features, L2GFeature
-        ), "Unexpected model type returned from _get_max_coloc_per_credible_set"
+        ), "Unexpected type returned from _get_max_coloc_per_credible_set"
 
     def test_get_max_coloc_per_credible_set_semantic(
         self: TestColocalisationFactory,
@@ -169,8 +160,10 @@ def test_get_max_coloc_per_credible_set_semantic(
                         "colocalisationMethod": "eCAVIAR",
                         "numberColocalisingVariants": 1,
                         "clpp": 0.81,  # 0.9*0.9
+                        "log2h4h3": None,
                     }
-                ]
+                ],
+                schema=Colocalisation.get_schema(),
             ),
             _schema=Colocalisation.get_schema(),
         )
@@ -183,10 +176,9 @@ def test_get_max_coloc_per_credible_set_semantic(
         )
         # Test
         coloc_features = ColocalisationFactory._get_max_coloc_per_credible_set(
+            coloc,
             credset,
             studies,
-            coloc,
-            "eCAVIAR",
         )
         assert coloc_features.df.collect() == expected_coloc_features_df.collect()