From 512a80aa13de404ead7940b0fe95e035241e8dc7 Mon Sep 17 00:00:00 2001
From: xyg123 <33658607+xyg123@users.noreply.github.com>
Date: Thu, 21 Mar 2024 11:23:52 +0000
Subject: [PATCH] test(method): improved performance in coloc tests (#536)
MIME-Version: 1.0
Content-Type: text/plain; charset=UTF-8
Content-Transfer-Encoding: 8bit

* fix: pytest for coloc unit tests

* fix: removed unused coloc tests

* test(coloc): add coloc semantic test (#538)

* test(coloc): define fixtures and parametrise coloc tests

* test(coloc): compare dfs with assert_frame_equal

* fix: remove unused threshold variable

---------

Co-authored-by: Irene López <45119610+ireneisdoomed@users.noreply.github.com>
Co-authored-by: David Ochoa <ochoa@ebi.ac.uk>
---
 .../coloc_test_data.snappy.parquet            | Bin 11927 -> 0 bytes
 .../method/test_colocalisation_method.py      | 233 ++++++------------
 2 files changed, 81 insertions(+), 152 deletions(-)
 delete mode 100644 tests/gentropy/data_samples/coloc_test_data.snappy.parquet

diff --git a/tests/gentropy/data_samples/coloc_test_data.snappy.parquet b/tests/gentropy/data_samples/coloc_test_data.snappy.parquet
deleted file mode 100644
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diff --git a/tests/gentropy/method/test_colocalisation_method.py b/tests/gentropy/method/test_colocalisation_method.py
index f90d54b3f..37613354c 100644
--- a/tests/gentropy/method/test_colocalisation_method.py
+++ b/tests/gentropy/method/test_colocalisation_method.py
@@ -2,11 +2,14 @@
 
 from __future__ import annotations
 
+from typing import Any
+
+import pytest
 from gentropy.dataset.colocalisation import Colocalisation
 from gentropy.dataset.study_locus_overlap import StudyLocusOverlap
 from gentropy.method.colocalisation import Coloc, ECaviar
+from pandas.testing import assert_frame_equal
 from pyspark.sql import SparkSession
-from pyspark.sql import functions as f
 
 
 def test_coloc(mock_study_locus_overlap: StudyLocusOverlap) -> None:
@@ -14,165 +17,91 @@ def test_coloc(mock_study_locus_overlap: StudyLocusOverlap) -> None:
     assert isinstance(Coloc.colocalise(mock_study_locus_overlap), Colocalisation)
 
 
-def test_coloc_colocalise(
-    spark: SparkSession,
-    threshold: float = 1e-5,
-) -> None:
-    """Compare COLOC results with R implementation, using provided sample dataset from R package (StudyLocusOverlap)."""
-    test_overlap_df = spark.read.parquet(
-        "tests/gentropy/data_samples/coloc_test_data.snappy.parquet", header=True
-    )
-    test_overlap = StudyLocusOverlap(test_overlap_df, StudyLocusOverlap.get_schema())
-    test_result = Coloc.colocalise(test_overlap)
-
-    expected = spark.createDataFrame(
-        [
-            {
-                "h0": 1.3769995397857477e-18,
-                "h1": 2.937336451601565e-10,
-                "h2": 8.593226431647826e-12,
-                "h3": 8.338916748775843e-4,
-                "h4": 0.9991661080227981,
-            }
-        ]
-    )
-    difference = test_result.df.select("h0", "h1", "h2", "h3", "h4").subtract(expected)
-    for col in difference.columns:
-        assert difference.filter(f.abs(f.col(col)) > threshold).count() == 0
-
-
-def test_single_snp_coloc(
-    spark: SparkSession,
-    threshold: float = 1e-5,
-) -> None:
-    """Test edge case of coloc where only one causal SNP is present in the StudyLocusOverlap."""
-    test_overlap_df = spark.createDataFrame(
-        [
-            {
-                "leftStudyLocusId": 1,
-                "rightStudyLocusId": 2,
-                "chromosome": "1",
-                "tagVariantId": "snp",
-                "left_logBF": 10.3,
-                "right_logBF": 10.5,
-            }
-        ]
-    )
-    test_overlap = StudyLocusOverlap(
-        test_overlap_df.select(
-            "leftStudyLocusId",
-            "rightStudyLocusId",
-            "chromosome",
-            "tagVariantId",
-            f.struct(f.col("left_logBF"), f.col("right_logBF")).alias("statistics"),
+@pytest.mark.parametrize(
+    "observed_data, expected_data",
+    [
+        # associations with a single overlapping SNP
+        (
+            # observed overlap
+            [
+                {
+                    "leftStudyLocusId": 1,
+                    "rightStudyLocusId": 2,
+                    "chromosome": "1",
+                    "tagVariantId": "snp",
+                    "statistics": {"left_logBF": 10.3, "right_logBF": 10.5},
+                },
+            ],
+            # expected coloc
+            [
+                {
+                    "h0": 9.254841951638903e-5,
+                    "h1": 2.7517068829182966e-4,
+                    "h2": 3.3609423764447284e-4,
+                    "h3": 9.254841952564387e-13,
+                    "h4": 0.9992961866536217,
+                },
+            ],
         ),
-        StudyLocusOverlap.get_schema(),
-    )
-    test_result = Coloc.colocalise(test_overlap)
-
-    expected = spark.createDataFrame(
-        [
-            {
-                "h0": 9.254841951638903e-5,
-                "h1": 2.7517068829182966e-4,
-                "h2": 3.3609423764447284e-4,
-                "h3": 9.254841952564387e-13,
-                "h4": 0.9992961866536217,
-            }
-        ]
-    )
-    difference = test_result.df.select("h0", "h1", "h2", "h3", "h4").subtract(expected)
-    for col in difference.columns:
-        assert difference.filter(f.abs(f.col(col)) > threshold).count() == 0
-
-
-def test_single_snp_coloc_one_negative(
+        # associations with multiple overlapping SNPs
+        (
+            # observed overlap
+            [
+                {
+                    "leftStudyLocusId": 1,
+                    "rightStudyLocusId": 2,
+                    "chromosome": "1",
+                    "tagVariantId": "snp1",
+                    "statistics": {"left_logBF": 10.3, "right_logBF": 10.5},
+                },
+                {
+                    "leftStudyLocusId": 1,
+                    "rightStudyLocusId": 2,
+                    "chromosome": "1",
+                    "tagVariantId": "snp2",
+                    "statistics": {"left_logBF": 10.3, "right_logBF": 10.5},
+                },
+            ],
+            # expected coloc
+            [
+                {
+                    "h0": 4.6230151407950416e-5,
+                    "h1": 2.749086942648107e-4,
+                    "h2": 3.357742374172504e-4,
+                    "h3": 9.983447421747411e-4,
+                    "h4": 0.9983447421747356,
+                },
+            ],
+        ),
+    ],
+)
+def test_coloc_semantic(
     spark: SparkSession,
-    threshold: float = 1e-5,
+    observed_data: list[Any],
+    expected_data: list[Any],
 ) -> None:
-    """Test edge case of coloc where only one causal SNP is present (On one side!) in the StudyLocusOverlap."""
-    test_overlap_df = spark.createDataFrame(
-        [
-            {
-                "leftStudyLocusId": 1,
-                "rightStudyLocusId": 2,
-                "chromosome": "1",
-                "tagVariantId": "snp",
-                "left_logBF": 18.3,
-                "right_logBF": 0.01,
-            }
-        ]
+    """Test our COLOC with the implementation in R."""
+    observed_overlap = StudyLocusOverlap(
+        _df=spark.createDataFrame(observed_data, schema=StudyLocusOverlap.get_schema()),
+        _schema=StudyLocusOverlap.get_schema(),
     )
-    test_overlap = StudyLocusOverlap(
-        test_overlap_df.select(
-            "leftStudyLocusId",
-            "rightStudyLocusId",
-            "chromosome",
-            "tagVariantId",
-            f.struct(f.col("left_logBF"), f.col("right_logBF")).alias("statistics"),
-        ),
-        StudyLocusOverlap.get_schema(),
+    observed_coloc_pdf = (
+        Coloc.colocalise(observed_overlap)
+        .df.select("h0", "h1", "h2", "h3", "h4")
+        .toPandas()
     )
-    test_result = Coloc.colocalise(test_overlap)
-    test_result.df.show(1, False)
-    expected = spark.createDataFrame(
-        [
-            {
-                "h0": 1.0246538505087709e-4,
-                "h1": 0.9081680002273896,
-                "h2": 1.0349517929098209e-8,
-                "h3": 1.0246538506112363e-12,
-                "h4": 0.09172952403701702,
-            }
-        ]
+    expected_coloc_pdf = (
+        spark.createDataFrame(expected_data)
+        .select("h0", "h1", "h2", "h3", "h4")
+        .toPandas()
     )
-    difference = test_result.df.select("h0", "h1", "h2", "h3", "h4").subtract(expected)
-    for col in difference.columns:
-        assert difference.filter(f.abs(f.col(col)) > threshold).count() == 0
 
-
-def test_single_snp_coloc_both_negative(
-    spark: SparkSession,
-    threshold: float = 1e-5,
-) -> None:
-    """Test edge case of coloc where only one non-causal SNP overlaps in the StudyLocusOverlap."""
-    test_overlap_df = spark.createDataFrame(
-        [
-            {
-                "leftStudyLocusId": 1,
-                "rightStudyLocusId": 2,
-                "chromosome": "1",
-                "tagVariantId": "snp",
-                "left_logBF": 0.03,
-                "right_logBF": 0.01,
-            }
-        ]
-    )
-    test_overlap = StudyLocusOverlap(
-        test_overlap_df.select(
-            "leftStudyLocusId",
-            "rightStudyLocusId",
-            "chromosome",
-            "tagVariantId",
-            f.struct(f.col("left_logBF"), f.col("right_logBF")).alias("statistics"),
-        ),
-        StudyLocusOverlap.get_schema(),
-    )
-    test_result = Coloc.colocalise(test_overlap)
-    expected = spark.createDataFrame(
-        [
-            {
-                "h0": 0.9997855774090624,
-                "h1": 1.0302335812225042e-4,
-                "h2": 1.0098335895103664e-4,
-                "h3": 9.9978557750904e-9,
-                "h4": 1.0405876008495098e-5,
-            }
-        ]
+    assert_frame_equal(
+        observed_coloc_pdf,
+        expected_coloc_pdf,
+        check_exact=False,
+        check_dtype=True,
     )
-    difference = test_result.df.select("h0", "h1", "h2", "h3", "h4").subtract(expected)
-    for col in difference.columns:
-        assert difference.filter(f.abs(f.col(col)) > threshold).count() == 0
 
 
 def test_ecaviar(mock_study_locus_overlap: StudyLocusOverlap) -> None: