refactor: rename gene_index to target_index in tests

tests/gentropy/conftest.py

@@ -15,7 +15,6 @@
 from gentropy.common.session import Session
 from gentropy.dataset.biosample_index import BiosampleIndex
 from gentropy.dataset.colocalisation import Colocalisation
-from gentropy.dataset.gene_index import GeneIndex
 from gentropy.dataset.intervals import Intervals
 from gentropy.dataset.l2g_feature_matrix import L2GFeatureMatrix
 from gentropy.dataset.l2g_gold_standard import L2GGoldStandard
@@ -25,6 +24,7 @@
 from gentropy.dataset.study_locus import StudyLocus
 from gentropy.dataset.study_locus_overlap import StudyLocusOverlap
 from gentropy.dataset.summary_statistics import SummaryStatistics
+from gentropy.dataset.target_index import TargetIndex
 from gentropy.dataset.variant_index import VariantIndex
 from gentropy.datasource.eqtl_catalogue.finemapping import EqtlCatalogueFinemapping
 from gentropy.datasource.eqtl_catalogue.study_index import EqtlCatalogueStudyIndex
@@ -379,7 +379,7 @@ def mock_summary_statistics(
 
 @pytest.fixture()
 def mock_ld_index(spark: SparkSession) -> LDIndex:
-    """Mock gene index."""
+    """Mock ld index."""
     ld_schema = LDIndex.get_schema()
 
     data_spec = (
@@ -519,9 +519,9 @@ def sample_target_index(spark: SparkSession) -> DataFrame:
 
 
 @pytest.fixture()
-def mock_gene_index(spark: SparkSession) -> GeneIndex:
-    """Mock gene index dataset."""
-    gi_schema = GeneIndex.get_schema()
+def mock_target_index(spark: SparkSession) -> TargetIndex:
+    """Mock target index dataset."""
+    gi_schema = TargetIndex.get_schema()
 
     data_spec = (
         dg.DataGenerator(
@@ -540,7 +540,7 @@ def mock_gene_index(spark: SparkSession) -> GeneIndex:
         .withColumnSpec("strand", percentNulls=0.1)
     )
 
-    return GeneIndex(_df=data_spec.build(), _schema=gi_schema)
+    return TargetIndex(_df=data_spec.build(), _schema=gi_schema)
 
 
 @pytest.fixture()

tests/gentropy/dataset/test_l2g_feature.py

@@ -21,7 +21,7 @@
 )
 
 from gentropy.dataset.colocalisation import Colocalisation
-from gentropy.dataset.gene_index import GeneIndex
+from gentropy.dataset.target_index import TargetIndex
 from gentropy.dataset.l2g_features.colocalisation import (
     EQtlColocClppMaximumFeature,
     EQtlColocClppMaximumNeighbourhoodFeature,
@@ -116,15 +116,15 @@ def test_feature_factory_return_type(
     mock_colocalisation: Colocalisation,
     mock_study_index: StudyIndex,
     mock_variant_index: VariantIndex,
-    mock_gene_index: GeneIndex,
+    mock_target_index: TargetIndex,
 ) -> None:
     """Test that every feature factory returns a L2GFeature dataset."""
     loader = L2GFeatureInputLoader(
         colocalisation=mock_colocalisation,
         study_index=mock_study_index,
         variant_index=mock_variant_index,
         study_locus=mock_study_locus,
-        gene_index=mock_gene_index,
+        target_index=mock_target_index,
     )
     feature_dataset = feature_class.compute(
         study_loci_to_annotate=mock_study_locus,
@@ -136,9 +136,9 @@ def test_feature_factory_return_type(
 
 
 @pytest.fixture(scope="module")
-def sample_gene_index(spark: SparkSession) -> GeneIndex:
-    """Create a sample gene index for testing."""
-    return GeneIndex(
+def sample_target_index(spark: SparkSession) -> TargetIndex:
+    """Create a sample target index for testing."""
+    return TargetIndex(
         _df=spark.createDataFrame(
             [
                 {
@@ -157,9 +157,9 @@ def sample_gene_index(spark: SparkSession) -> GeneIndex:
                     "chromosome": "1",
                 },
             ],
-            GeneIndex.get_schema(),
+            TargetIndex.get_schema(),
         ),
-        _schema=GeneIndex.get_schema(),
+        _schema=TargetIndex.get_schema(),
     )
 
 
@@ -294,7 +294,7 @@ def test__common_colocalisation_feature_logic(
     def test_extend_missing_colocalisation_to_neighbourhood_genes(
         self: TestCommonColocalisationFeatureLogic,
         spark: SparkSession,
-        sample_gene_index: GeneIndex,
+        sample_target_index: TargetIndex,
         sample_variant_index: VariantIndex,
     ) -> None:
         """Test the extend_missing_colocalisation_to_neighbourhood_genes function."""
@@ -316,7 +316,7 @@ def test_extend_missing_colocalisation_to_neighbourhood_genes(
             feature_name="eQtlColocH4Maximum",
             local_features=local_features,
             variant_index=sample_variant_index,
-            gene_index=sample_gene_index,
+            target_index=sample_target_index,
             study_locus=self.sample_study_locus,
         ).select("studyLocusId", "geneId", "eQtlColocH4Maximum")
         expected_df = spark.createDataFrame(
@@ -329,7 +329,7 @@ def test_extend_missing_colocalisation_to_neighbourhood_genes(
     def test_common_neighbourhood_colocalisation_feature_logic(
         self: TestCommonColocalisationFeatureLogic,
         spark: SparkSession,
-        sample_gene_index: GeneIndex,
+        sample_target_index: TargetIndex,
         sample_variant_index: VariantIndex,
     ) -> None:
         """Test the common logic of the neighbourhood colocalisation features."""
@@ -343,7 +343,7 @@ def test_common_neighbourhood_colocalisation_feature_logic(
             colocalisation=self.sample_colocalisation,
             study_index=self.sample_studies,
             study_locus=self.sample_study_locus,
-            gene_index=sample_gene_index,
+            target_index=sample_target_index,
             variant_index=sample_variant_index,
         ).withColumn(feature_name, f.round(f.col(feature_name), 3))
         # expected max is 0.81
@@ -561,7 +561,7 @@ def test_common_neighbourhood_distance_feature_logic(
             common_neighbourhood_distance_feature_logic(
                 self.sample_study_locus,
                 variant_index=self.sample_variant_index,
-                gene_index=self.sample_gene_index,
+                target_index=self.sample_target_index,
                 feature_name=feature_name,
                 distance_type=self.distance_type,
                 genomic_window=10,
@@ -653,7 +653,7 @@ def _setup(
             ),
             _schema=VariantIndex.get_schema(),
         )
-        self.sample_gene_index = GeneIndex(
+        self.sample_target_index = TargetIndex(
             _df=spark.createDataFrame(
                 [
                     {
@@ -675,9 +675,9 @@ def _setup(
                         "biotype": "non_coding",
                     },
                 ],
-                GeneIndex.get_schema(),
+                TargetIndex.get_schema(),
             ),
-            _schema=GeneIndex.get_schema(),
+            _schema=TargetIndex.get_schema(),
         )
 
 
@@ -760,7 +760,7 @@ def test_common_vep_feature_logic(
         def test_common_neighbourhood_vep_feature_logic(
             self: TestCommonVepFeatureLogic,
             spark: SparkSession,
-            sample_gene_index: GeneIndex,
+            sample_target_index: TargetIndex,
             sample_variant_index: VariantIndex,
         ) -> None:
             """Test the logic of the function that extracts the maximum severity score for a gene given the maximum of the maximum scores for all protein coding genes in the vicinity."""
@@ -769,7 +769,7 @@ def test_common_neighbourhood_vep_feature_logic(
                 common_neighbourhood_vep_feature_logic(
                     self.sample_study_locus,
                     variant_index=sample_variant_index,
-                    gene_index=sample_gene_index,
+                    target_index=sample_target_index,
                     feature_name=feature_name,
                 )
                 .withColumn(feature_name, f.round(f.col(feature_name), 2))
@@ -859,7 +859,7 @@ def test_common_genecount_feature_logic(
         """Test the common logic of the gene count features."""
         observed_df = common_genecount_feature_logic(
             study_loci_to_annotate=self.sample_study_locus,
-            gene_index=self.sample_gene_index,
+            target_index=self.sample_target_index,
             feature_name=feature_name,
             genomic_window=500000,
             protein_coding_only=protein_coding_only,
@@ -892,7 +892,7 @@ def _setup(self: TestCommonGeneCountFeatureLogic, spark: SparkSession) -> None:
             ),
             _schema=StudyLocus.get_schema(),
         )
-        self.sample_gene_index = GeneIndex(
+        self.sample_target_index = TargetIndex(
             _df=spark.createDataFrame(
                 [
                     {
@@ -914,9 +914,9 @@ def _setup(self: TestCommonGeneCountFeatureLogic, spark: SparkSession) -> None:
                         "biotype": "non_coding",
                     },
                 ],
-                GeneIndex.get_schema(),
+                TargetIndex.get_schema(),
             ),
-            _schema=GeneIndex.get_schema(),
+            _schema=TargetIndex.get_schema(),
         )
 
 
@@ -944,7 +944,7 @@ def test_is_protein_coding_feature_logic(
         observed_df = (
             is_protein_coding_feature_logic(
                 study_loci_to_annotate=self.sample_study_locus,
-                gene_index=self.sample_gene_index,
+                target_index=self.sample_target_index,
                 feature_name="isProteinCoding500kb",
                 genomic_window=500000,
             )
@@ -981,8 +981,8 @@ def _setup(self: TestCommonProteinCodingFeatureLogic, spark: SparkSession) -> No
             _schema=StudyLocus.get_schema(),
         )
 
-        # Sample gene index data with biotype
-        self.sample_gene_index = GeneIndex(
+        # Sample target index data with biotype
+        self.sample_target_index = TargetIndex(
             _df=spark.createDataFrame(
                 [
                     {
@@ -1004,9 +1004,9 @@ def _setup(self: TestCommonProteinCodingFeatureLogic, spark: SparkSession) -> No
                         "biotype": "non_coding",
                     },
                 ],
-                GeneIndex.get_schema(),
+                TargetIndex.get_schema(),
             ),
-            _schema=GeneIndex.get_schema(),
+            _schema=TargetIndex.get_schema(),
         )
 
 

tests/gentropy/dataset/test_l2g_feature_matrix.py

@@ -16,11 +16,11 @@
 )
 
 from gentropy.dataset.colocalisation import Colocalisation
-from gentropy.dataset.gene_index import GeneIndex
 from gentropy.dataset.l2g_feature_matrix import L2GFeatureMatrix
 from gentropy.dataset.l2g_gold_standard import L2GGoldStandard
 from gentropy.dataset.study_index import StudyIndex
 from gentropy.dataset.study_locus import StudyLocus
+from gentropy.dataset.target_index import TargetIndex
 from gentropy.method.l2g.feature_factory import L2GFeatureInputLoader
 
 if TYPE_CHECKING:
@@ -54,7 +54,7 @@ def test_study_locus(
             colocalisation=self.sample_colocalisation,
             study_index=self.sample_study_index,
             study_locus=self.sample_study_locus,
-            gene_index=self.sample_gene_index,
+            target_index=self.sample_target_index,
         )
         fm = L2GFeatureMatrix.from_features_list(
             self.sample_study_locus, features_list, loader
@@ -170,7 +170,7 @@ def _setup(self: TestFromFeaturesList, spark: SparkSession) -> None:
             ),
             _schema=Colocalisation.get_schema(),
         )
-        self.sample_gene_index = GeneIndex(
+        self.sample_target_index = TargetIndex(
             _df=spark.createDataFrame(
                 [
                     ("g1", "X", "protein_coding", 200),
@@ -183,7 +183,7 @@ def _setup(self: TestFromFeaturesList, spark: SparkSession) -> None:
                     "tss",
                 ],
             ),
-            _schema=GeneIndex.get_schema(),
+            _schema=TargetIndex.get_schema(),
         )
 
 

tests/gentropy/dataset/test_study_index.py

@@ -7,8 +7,8 @@
 from pyspark.sql import functions as f
 
 from gentropy.dataset.biosample_index import BiosampleIndex
-from gentropy.dataset.gene_index import GeneIndex
 from gentropy.dataset.study_index import StudyIndex
+from gentropy.dataset.target_index import TargetIndex
 
 
 def test_study_index_creation(mock_study_index: StudyIndex) -> None:
@@ -188,9 +188,9 @@ def create_study_index(drop_column: str) -> StudyIndex:
         self.study_index_no_gene = create_study_index("geneId")
         self.study_index_no_biosample_id = create_study_index("biosampleFromSourceId")
 
-        self.gene_index = GeneIndex(
+        self.target_index = TargetIndex(
             _df=spark.createDataFrame(self.GENE_DATA, self.GENE_COLUMNS),
-            _schema=GeneIndex.get_schema(),
+            _schema=TargetIndex.get_schema(),
         )
         self.biosample_index = BiosampleIndex(
             _df=spark.createDataFrame(self.BIOSAMPLE_DATA, self.BIOSAMPLE_COLUMNS),
@@ -199,7 +199,7 @@ def create_study_index(drop_column: str) -> StudyIndex:
 
     def test_gene_validation_type(self: TestQTLValidation) -> None:
         """Testing if the target validation runs and returns the expected type."""
-        validated = self.study_index.validate_target(self.gene_index)
+        validated = self.study_index.validate_target(self.target_index)
         assert isinstance(validated, StudyIndex)
 
     def test_biosample_validation_type(self: TestQTLValidation) -> None:
@@ -211,7 +211,7 @@ def test_biosample_validation_type(self: TestQTLValidation) -> None:
     def test_qtl_validation_correctness(self: TestQTLValidation, test: str) -> None:
         """Testing if the QTL validation only flags the expected studies."""
         if test == "gene":
-            validated = self.study_index.validate_target(self.gene_index).persist()
+            validated = self.study_index.validate_target(self.target_index).persist()
             bad_study = "s2"
         if test == "biosample":
             validated = self.study_index.validate_biosample(
@@ -252,15 +252,15 @@ def test_qtl_validation_drop_relevant_column(
         """Testing what happens if an expected column is not present."""
         if drop == "gene":
             if test == "gene":
-                validated = self.study_index_no_gene.validate_target(self.gene_index)
+                validated = self.study_index_no_gene.validate_target(self.target_index)
             if test == "biosample":
                 validated = self.study_index_no_gene.validate_biosample(
                     self.biosample_index
                 )
         if drop == "biosample":
             if test == "gene":
                 validated = self.study_index_no_biosample_id.validate_target(
-                    self.gene_index
+                    self.target_index
                 )
             if test == "biosample":
                 validated = self.study_index_no_biosample_id.validate_biosample(

tests/gentropy/dataset/test_summary_statistics.py

@@ -17,7 +17,7 @@
 def test_summary_statistics__creation(
     mock_summary_statistics: SummaryStatistics,
 ) -> None:
-    """Test gene index creation with mock gene index."""
+    """Test summary statistics creation with mock summary statistics."""
     assert isinstance(mock_summary_statistics, SummaryStatistics)
 
 

tests/gentropy/dataset/test_target_index.py

@@ -4,29 +4,29 @@
 
 from pyspark.sql import DataFrame
 
-from gentropy.dataset.gene_index import GeneIndex
+from gentropy.dataset.target_index import TargetIndex
 
 
-def test_gene_index_creation(mock_gene_index: GeneIndex) -> None:
-    """Test gene index creation with mock gene index."""
-    assert isinstance(mock_gene_index, GeneIndex)
+def test_target_index_creation(mock_target_index: TargetIndex) -> None:
+    """Test target index creation with mock target index."""
+    assert isinstance(mock_target_index, TargetIndex)
 
 
-def test_gene_index_location_lut(mock_gene_index: GeneIndex) -> None:
-    """Test gene index location lut."""
-    assert isinstance(mock_gene_index.locations_lut(), DataFrame)
+def test_target_index_location_lut(mock_target_index: TargetIndex) -> None:
+    """Test target index location lut."""
+    assert isinstance(mock_target_index.locations_lut(), DataFrame)
 
 
-def test_gene_index_symbols_lut(mock_gene_index: GeneIndex) -> None:
-    """Test gene index symbols lut."""
-    assert isinstance(mock_gene_index.symbols_lut(), DataFrame)
+def test_target_index_symbols_lut(mock_target_index: TargetIndex) -> None:
+    """Test target index symbols lut."""
+    assert isinstance(mock_target_index.symbols_lut(), DataFrame)
 
 
-def test_gene_index_filter_by_biotypes(mock_gene_index: GeneIndex) -> None:
-    """Test gene index filter by biotypes."""
+def test_target_index_filter_by_biotypes(mock_target_index: TargetIndex) -> None:
+    """Test target index filter by biotypes."""
     assert isinstance(
-        mock_gene_index.filter_by_biotypes(
+        mock_target_index.filter_by_biotypes(
             biotypes=["protein_coding", "3prime_overlapping_ncRNA", "antisense"]
         ),
-        GeneIndex,
+        TargetIndex,
     )