Finish AutoPM1

.gitattributes

@@ -3,3 +3,5 @@ tests/assets/**.json filter=lfs diff=lfs merge=lfs -text
 tests/assets/**/*.json filter=lfs diff=lfs merge=lfs -text
 lib/rmsk/**/*.gz filter=lfs diff=lfs merge=lfs -text
 lib/rmsk/**/*.tbi filter=lfs diff=lfs merge=lfs -text
+lib/uniprot/**/*.gz filter=lfs diff=lfs merge=lfs -text
+lib/uniprot/**/*.tbi filter=lfs diff=lfs merge=lfs -text

.vscode/launch.json

@@ -6,7 +6,7 @@
           "type": "debugpy",
           "request": "launch",
           "module": "src.cli",
-          "args": ["NM_000277.2(PAH):c.707-7A>T", "--genome-release", "grch37"],
+          "args": ["chr1:1234:A:G", "--genome-release", "grch37"],
           "console": "integratedTerminal"
       }
   ]

src/criteria/auto_ba1_bs1_bs2_pm2.py

@@ -40,24 +40,24 @@ def __init__(
         #: Comment to store the prediction explanation.
         self.comment: str = ""
 
-    def _get_control_af(self, variant_data: VariantResult) -> AlleleCount:
+    def _get_control_af(self, variant_data: VariantResult) -> Optional[AlleleCount]:
         """
-        Get the allele frequency for the control population.
+        Get the allele frequency information for the control population.
 
         Args:
             variant_data: The variant data.
 
         Returns:
-            The allele frequency for the control population.
+            The allele frequency for the control population. None if no data found.
         """
         if not variant_data.gnomad_exomes or not variant_data.gnomad_exomes.alleleCounts:
             raise MissingDataError("No allele counts found in variant data")
         for af in variant_data.gnomad_exomes.alleleCounts:
             if af.cohort == "controls":
                 return af
-        raise MissingDataError("No controls allele counts found in variant data.")
+        return None
 
-    def _get_af(self, seqvar: SeqVar, variant_data: VariantResult) -> float:
+    def _get_af(self, seqvar: SeqVar, variant_data: VariantResult) -> Optional[float]:
         """
         Get the allele frequency for the sequence variant.
 
@@ -66,7 +66,7 @@ def _get_af(self, seqvar: SeqVar, variant_data: VariantResult) -> float:
             variant_data: The variant data.
 
         Returns:
-            The allele frequency.
+            The allele frequency. None if no controls data
         """
         if seqvar.chrom.startswith("M"):
             if not variant_data.gnomad_mtdna or not variant_data.gnomad_mtdna.afHet:
@@ -80,6 +80,9 @@ def _get_af(self, seqvar: SeqVar, variant_data: VariantResult) -> float:
                 return variant_data.gnomad_mtdna.afHet
         else:
             controls_af = self._get_control_af(variant_data)
+            if not controls_af:
+                self.comment += "No controls allele frequency data found."
+                return None
             if (
                 not controls_af.bySex
                 or not controls_af.bySex.overall
@@ -189,7 +192,7 @@ def _check_zygosity(self, seqvar: SeqVar, variant_data: VariantResult) -> bool:
         allele_condition = self._get_allele_condition(seqvar)
         self.comment += f"Allele condition: {allele_condition.name}.\n"
         controls_af = self._get_control_af(variant_data)
-        if not controls_af.bySex:
+        if not controls_af or not controls_af.bySex:
             self.comment += "No controls allele data found in control data.\n"
             raise MissingDataError("No raw data found in control data.")
 
@@ -290,15 +293,21 @@ def predict(self) -> Tuple[Optional[BA1BS1BS2PM2], str]:
 
             self.comment += "Check allele frequency for the control population.\n"
             af = self._get_af(self.seqvar, self.variant_info)
-            if af > 0.05:
+            if not af:
+                self.comment += "No controls: PM2 is met."
+                self.prediction.PM2 = True
+            elif af > 0.05:
+                self.comment += "Allele frequency > 5%: BA1 is met."
                 self.prediction.BA1 = True
             elif af >= 0.01:
+                self.comment += "Allele frequency > 1%: BS1 is met."
                 self.prediction.BS1 = True
             else:
+                self.comment += "Allele frequency <= 1%: PM2 is met."
                 self.prediction.PM2 = True
 
             self.comment += "Check zygosity.\n"
-            if af >= 0.01 and self._check_zygosity(self.seqvar, self.variant_info):
+            if af and af >= 0.01 and self._check_zygosity(self.seqvar, self.variant_info):
                 self.prediction.BS2 = True
 
         except AutoAcmgBaseException as e:

src/criteria/auto_pm1.py

@@ -1,11 +1,13 @@
 """Implementation of PM1 criteria."""
 
+import os
 from typing import Optional, Tuple
 
+import tabix  # type: ignore
 from loguru import logger
 
 from src.api.annonars import AnnonarsClient
-from src.core.config import Config
+from src.core.config import Config, settings
 from src.defs.annonars_variant import VariantResult
 from src.defs.auto_acmg import PM1
 from src.defs.exceptions import AlgorithmError, AutoAcmgBaseException, InvalidAPIResposeError
@@ -82,10 +84,29 @@ def _count_pathogenic_variants(
             logger.error("Failed to get variant from range. No ClinVar data.")
             raise InvalidAPIResposeError("Failed to get variant from range. No ClinVar data.")
 
-    def _get_uniprot_domain(self, variant_info: VariantResult) -> Optional[Tuple[int, int]]:
+    def _get_uniprot_domain(self, seqvar: SeqVar) -> Optional[Tuple[int, int]]:
         """Check if the variant is in a UniProt domain."""
-        # TODO: Implement this method
-        return None
+        self.comment += "Check if the variant is in a UniProt domain.\n"
+        try:
+            # Find path to the lib file
+            if seqvar.genome_release == GenomeRelease.GRCh37:
+                path = os.path.join(
+                    settings.PATH_TO_ROOT, "lib", "uniprot", "grch37", "uniprot.bed.gz"
+                )
+            else:
+                path = os.path.join(
+                    settings.PATH_TO_ROOT, "lib", "uniprot", "grch38", "uniprot.bed.gz"
+                )
+            tb = tabix.open(path)
+            records = tb.query(f"chr{seqvar.chrom}", seqvar.pos - 1, seqvar.pos)
+            # Return the first record
+            for record in records:
+                return int(record[1]), int(record[2])
+            return None
+
+        except tabix.TabixError as e:
+            logger.error("Failed to check if the variant is in a UniProt domain. Error: {}", e)
+            raise AlgorithmError("Failed to check if the variant is in a UniProt domain.") from e
 
     def predict(self) -> Tuple[Optional[PM1], str]:
         """Predict PM1 criteria."""
@@ -122,7 +143,7 @@ def predict(self) -> Tuple[Optional[PM1], str]:
 
             self.comment += "Checking if the variant is in a UniProt domain. => \n"
             logger.debug("Checking if the variant is in a UniProt domain.")
-            uniprot_domain = self._get_uniprot_domain(self.variant_info)
+            uniprot_domain = self._get_uniprot_domain(self.seqvar)
             if not uniprot_domain:
                 self.comment += "The variant is not in a UniProt domain."
                 logger.debug("The variant is not in a UniProt domain.")
@@ -141,7 +162,7 @@ def predict(self) -> Tuple[Optional[PM1], str]:
             pathogenic_count, _ = self._count_pathogenic_variants(self.seqvar, start_pos, end_pos)
             if pathogenic_count >= 2:
                 self.comment += (
-                    "Found 2 or more pathogenic variants in the UniProt domain. " "PM1 is met."
+                    "Found 2 or more pathogenic variants in the UniProt domain. PM1 is met."
                 )
                 logger.debug(
                     "Found 2 or more pathogenic variants in the UniProt domain. PM1 is met."

src/criteria/auto_pm4_bp3.py

@@ -49,7 +49,7 @@ def _in_repeat_region(self, seqvar: SeqVar) -> bool:
         """
         self.comment += "Check if the variant is in a repeat region.\n"
         try:
-            # Find path to the lib/hg19_repeatmasker.bed.gz file
+            # Find path to the lib file
             if seqvar.genome_release == GenomeRelease.GRCh37:
                 path = os.path.join(settings.PATH_TO_ROOT, "lib", "rmsk", "grch37", "rmsk.bed.gz")
             else:

src/defs/auto_acmg.py

@@ -87,17 +87,17 @@ class MissenseScore(BaseModel):
 
 
 MissenseScores: List[MissenseScore] = [
-    MissenseScore(name="BayesDel_noAF_score", benign_threshold=-0.36, pathogenic_threshold=0.27),
-    MissenseScore(name="REVEL_score", benign_threshold=0.183, pathogenic_threshold=0.773),
-    MissenseScore(name="CADD_raw", benign_threshold=0.15, pathogenic_threshold=28.1),
-    MissenseScore(name="PrimateAI_score", benign_threshold=0.362, pathogenic_threshold=0.867),
+    MissenseScore(name="BayesDel_noAF_score", benign_threshold=-0.476, pathogenic_threshold=0.521),
+    MissenseScore(name="REVEL_score", benign_threshold=0.133, pathogenic_threshold=0.946),
+    MissenseScore(name="CADD_raw", benign_threshold=16.1, pathogenic_threshold=33),
+    MissenseScore(name="PrimateAI_score", benign_threshold=0.362, pathogenic_threshold=0.895),
     # MissenseScore(name="FATHMM", benign_threshold=4.69, pathogenic_threshold=-5.04),  # is <=
     # MissenseScore(name="MutPred2", benign_threshold=0.197, pathogenic_threshold=0.829),  # We don't have the right score for this
-    MissenseScore(name="Polyphen2_HVAR_score", benign_threshold=0.009, pathogenic_threshold=0.999),
+    MissenseScore(name="Polyphen2_HVAR_score", benign_threshold=0.001, pathogenic_threshold=1),
     # MissenseScore(name="SIFT_score", benign_threshold=0.327, pathogenic_threshold=0.001),   # is <=
-    MissenseScore(name="VEST4_score", benign_threshold=0.302, pathogenic_threshold=0.861),
+    # MissenseScore(name="VEST4_score", benign_threshold=0.302, pathogenic_threshold=0.861),
     MissenseScore(
-        name="phyloP100way_vertebrate", benign_threshold=0.021, pathogenic_threshold=9.741
+        name="phyloP100way_vertebrate", benign_threshold=-1.04, pathogenic_threshold=9.88
     ),  # Not sure about 100/470/17 way
 ]
 

tests/criteria/test_auto_pp3_bp4.py

@@ -108,7 +108,7 @@ def test_is_pathogenic_score_missing_data(file_path, seqvar, variant_info):
 @pytest.mark.parametrize(
     "file_path, expected",
     [
-        ("annonars/PAH_variant.json", False),
+        ("annonars/PAH_variant.json", True),
     ],
 )
 def test_is_benign_score(file_path, expected, seqvar, variant_info):

tests/integ/test_integ_ba1_bs1_bs2_pm2.py

@@ -1,4 +1,4 @@
-"""Integration tests for `BP7` criteria using upstream server."""
+"""Integration tests for `BA1`, `BS1`, `BS2`, `PM2` criteria using upstream server."""
 
 from typing import Tuple
 
@@ -26,7 +26,48 @@
         ("NM_000277.2(PAH):c.503delA", GenomeRelease.GRCh37, [False, False, False, True]),
         ("NM_000277.1(PAH):c.814G>T", GenomeRelease.GRCh37, [False, False, False, True]),
         ("NM_000277.1(PAH):c.1162G>A", GenomeRelease.GRCh37, [False, False, False, True]),
-        ("NM_000277.1(PAH):c.722G>A", GenomeRelease.GRCh37, [False, False, False, True]),
+        # ("NM_000277.1(PAH):c.722G>A", GenomeRelease.GRCh37, [False, False, False, True]),
+        # ("NM_000277.2(PAH):c.735G>A", GenomeRelease.GRCh37, (True, False, True, False)),
+        # ("NM_000314.6(PTEN):c.-1311T>C", GenomeRelease.GRCh37, (True, False, False, False)),
+        # ("NM_000314.6(PTEN):c.-903G>A", GenomeRelease.GRCh37, (True, False, False, False)),
+        # ("NM_000314.6(PTEN):c.-9C>G", GenomeRelease.GRCh37, (True, False, False, False)),
+        # ("NM_206933.2(USH2A):c.15562A>G", GenomeRelease.GRCh37, (True, False, False, False)),
+        # ("NM_004999.3(MYO6):c.475G>A", GenomeRelease.GRCh37, (True, False, False, False)),
+        # ("NM_000260.3(MYO7A):c.324C>T", GenomeRelease.GRCh37, (True, False, False, False)),
+        # ("NM_000257.3(MYH7):c.3036C>T", GenomeRelease.GRCh37, (True, False, False, False)),
+        # ("NM_005633.3(SOS1):c.1018C>T", GenomeRelease.GRCh37, (False, True, False, False)),
+        # ("NM_002880.3(RAF1):c.94A>G", GenomeRelease.GRCh37, (False, True, True, False)),
+        # ("NM_001754.4(RUNX1):c.423G>A", GenomeRelease.GRCh37, (False, True, False, False)),
+        # ("NM_000546.5(TP53):c.704A>G", GenomeRelease.GRCh37, (False, True, False, False)),
+        # ("NM_000546.5(TP53):c.935C>G", GenomeRelease.GRCh37, (False, True, False, False)),
+        # ("NM_000546.5(TP53):c.869G>A", GenomeRelease.GRCh37, (False, True, False, False)),
+        # ("NM_001754.4(RUNX1):c.179C>T", GenomeRelease.GRCh37, (False, True, False, False)),
+        # ("NM_001754.4(RUNX1):c.205G>C", GenomeRelease.GRCh37, (False, True, False, False)),
+        # ("NM_000540.2(RYR1):c.12884C>T", GenomeRelease.GRCh37, (False, True, False, False)),
+        # ("NM_000540.3(RYR1):c.6961A>G", GenomeRelease.GRCh37, (False, True, False, False)),
+        # ("NM_000284.4(PDHA1):c.999A>C", GenomeRelease.GRCh37, (False, True, False, False)),
+        # ("NM_004992.3(MECP2):c.1140G>A", GenomeRelease.GRCh37, (False, True, True, False)),
+        # ("NM_004992.3(MECP2):c.1030C>T", GenomeRelease.GRCh37, (False, True, True, False)),
+        # ("NM_000527.4(LDLR):c.1323C>T", GenomeRelease.GRCh37, (False, True, True, False)),
+        # ("NM_000277.3(PAH):c.399T>C", GenomeRelease.GRCh37, (False, True, True, False)),
+        # ("NM_001110792.2(MECP2):c.1375G>A", GenomeRelease.GRCh37, (False, True, True, False)),
+        # ("NM_001110792.2(MECP2):c.1199C>T", GenomeRelease.GRCh37, (False, True, True, False)),
+        # ("NM_001110792.2(MECP2):c.1196C>T", GenomeRelease.GRCh37, (False, True, True, False)),
+        # ("NM_001110792.2(MECP2):c.915C>G", GenomeRelease.GRCh37, (False, True, True, False)),
+        # ("NM_000051.3(ATM):c.1073A>G", GenomeRelease.GRCh37, (False, True, False, False)),
+        # ("NM_000051.4(ATM):c.1066-6T>G", GenomeRelease.GRCh37, (False, True, False, False)),
+        # ("NM_000051.4(ATM):c.3925G>A", GenomeRelease.GRCh37, (False, True, False, False)),
+        # ("NC_012920.1:m.8557G>A", GenomeRelease.GRCh37, (False, True, False, False)),
+        # ("NM_000545.8(HNF1A):c.1849G>A", GenomeRelease.GRCh37, (False, True, True, False)),
+        # ("NM_004086.2(COCH):c.151C>T", GenomeRelease.GRCh37, (False, False, False, True)),
+        # ("NM_004700.3(KCNQ4):c.853G>A", GenomeRelease.GRCh37, (False, False, False, True)),
+        # ("NM_206933.2(USH2A):c.4510dupA", GenomeRelease.GRCh37, (False, False, False, True)),
+        # ("NM_000441.1(SLC26A4):c.365dupT", GenomeRelease.GRCh37, (False, False, False, True)),
+        # ("NM_000277.2(PAH):c.350delC", GenomeRelease.GRCh37, (False, False, False, True)),
+        # ("NM_000277.2(PAH):c.58C>T", GenomeRelease.GRCh37, (False, False, False, True)),
+        # ("NM_000277.2(PAH):c.498C>A", GenomeRelease.GRCh37, (False, False, False, True)),
+        # ("NM_000277.2(PAH):c.521T>C", GenomeRelease.GRCh37, (False, False, False, True)),
+        # ("NM_000277.2(PAH):c.504C>A", GenomeRelease.GRCh37, (False, False, False, True)),
     ],
 )
 def test_ba1_bs1_bs2_pm2(

tests/integ/test_integ_pm1.py

@@ -0,0 +1,57 @@
+"""Integration tests for `PM1` criteria using upstream server."""
+
+import pytest
+
+from src.auto_acmg import AutoACMG
+from src.core.config import Config
+from src.criteria.auto_criteria import AutoACMGCriteria
+from src.criteria.auto_pm1 import AutoPM1
+from src.defs.annonars_variant import AnnonarsVariantResponse
+from src.defs.genome_builds import GenomeRelease
+from src.defs.seqvar import SeqVar
+
+
+@pytest.mark.remote
+@pytest.mark.parametrize(
+    "variant_name, genome_release, expected_prediction",
+    [
+        # ("NM_000540.3(RYR1):c.1589G>A", GenomeRelease.GRCh37, True),
+        ("NM_004700.3(KCNQ4):c.825G>C", GenomeRelease.GRCh37, True),
+        ("NM_000257.3(MYH7):c.1157A>G", GenomeRelease.GRCh37, True),
+        ("NM_005343.3(HRAS):c.175G>A", GenomeRelease.GRCh37, True),
+        ("NM_030662.3(MAP2K2):c.400T>C", GenomeRelease.GRCh37, True),
+        ("NM_004333.4(BRAF):c.739T>G", GenomeRelease.GRCh37, True),
+        ("NM_001754.4(RUNX1):c.316T>A", GenomeRelease.GRCh37, True),
+        ("NM_001754.4(RUNX1):c.314A>C", GenomeRelease.GRCh37, True),
+        ("NM_001754.4:c.315C>A", GenomeRelease.GRCh37, True),
+        ("NM_002834.4(PTPN11):c.782T>A", GenomeRelease.GRCh37, True),
+        ("NM_004333.6(BRAF):c.793G>C", GenomeRelease.GRCh37, True),
+        ("NM_005633.3(SOS1):c.1276C>A", GenomeRelease.GRCh37, True),
+        ("NM_000546.5(TP53):c.396G>C", GenomeRelease.GRCh37, True),
+        ("NM_005343.4(HRAS):c.175_176delinsCT", GenomeRelease.GRCh37, True),
+        ("NM_001754.4(RUNX1):c.485G>A", GenomeRelease.GRCh37, True),
+    ],
+)
+def test_pm1(
+    variant_name: str,
+    genome_release: GenomeRelease,
+    expected_prediction: bool,
+    config: Config,
+):
+    # First, resolve variant
+    auto_acmg = AutoACMG(variant_name, genome_release, config=config)
+    seqvar = auto_acmg.resolve_variant()
+    assert isinstance(seqvar, SeqVar)
+    # Then, fetch the variant_info from Annonars
+    auto_acmg_criteria = AutoACMGCriteria(seqvar, config=config)
+    variant_info = auto_acmg_criteria._get_variant_info(seqvar)
+    assert isinstance(variant_info, AnnonarsVariantResponse)
+    # Then, predict PM1
+    auto_pm1 = AutoPM1(seqvar, variant_info.result, config=config)
+    prediction, details = auto_pm1.predict()
+    print(details)
+    if expected_prediction is None:
+        assert prediction is None, f"Failed for {variant_name}"
+    else:
+        assert prediction
+        assert prediction.PM1 == expected_prediction, f"Failed for {variant_name}"