diff --git a/docs/user-guide/devries.rst b/docs/user-guide/devries.rst
new file mode 100644
index 000000000..74e5cd26e
--- /dev/null
+++ b/docs/user-guide/devries.rst
@@ -0,0 +1,155 @@
+.. _devries:
+
+==============
+De Vries Score
+==============
+
+
+The De Vries score was developed as a relatively simple phenotypic severity
+score for individuals with intellectual disability in which points are given
+for (severity of) intellectual disability,
+growth abnormalities (prenatal and postnatal), facial dysmorphisms,
+nonfacial dysmorphisms, and other congenital anomalies
+(`Dingemans et al. (2022) `_).
+Statistical significance of a difference in the De Vries score between groups can be
+determined using the Mann–Whitney-U test.
+
+We refer to `Feenstra et al. (2011) `_ for
+the original description of the adjusted De Vries score. Here we offer a version of the
+score that leverages the structure of the Human Phenotype Ontology to assess the phenotype.
+
+The De Vries score has several sections, each of which is scored on a point system. The
+final score is obtained as the sum of the points of each of the sections.
+
+Developmental delay
+~~~~~~~~~~~~~~~~~~~
+
+The original score assigns one point for mild or moderate developmental delay
+and two points for severe developmental delay.
+
++----------------------------------------------------------------------------------------------------------+-----------+
+| HPO term | Score |
++==========================================================================================================+===========+
+| `Mild global developmental delay (HP:0011342) `_ | 1 |
++----------------------------------------------------------------------------------------------------------+-----------+
+| `Moderate global developmental delay (HP:0011343) `_ | 1 |
++----------------------------------------------------------------------------------------------------------+-----------+
+| `Severe global developmental delay (HP:0011344) `_ | 2 |
++----------------------------------------------------------------------------------------------------------+-----------+
+| `Profound global developmental delay (HP:0011344) `_ | 2 |
++----------------------------------------------------------------------------------------------------------+-----------+
+| `Global developmental delay (HP:0001263) `_ | 1 |
++----------------------------------------------------------------------------------------------------------+-----------+
+
+Note that one point is assigned for the term Global developmental delay (HP:0001263), which is the
+parent of the other terms, because no information was provided about the degree of delay.
+
+If none of the above terms is found, then the scorer assigns terms based on the Intellectual Disability terms.
+
++----------------------------------------------------------------------------------------------------------+-----------+
+| HPO term | Score |
++==========================================================================================================+===========+
+| `Intellectual disability, borderline (HP:0006889) `_ | 0.5 |
++----------------------------------------------------------------------------------------------------------+-----------+
+| `Intellectual disability, mild (HP:0001256) `_ | 1 |
++----------------------------------------------------------------------------------------------------------+-----------+
+| `Intellectual disability, moderate (HP:0002342) `_ | 1 |
++----------------------------------------------------------------------------------------------------------+-----------+
+| `Intellectual disability, severe (HP:0010864) `_ | 2 |
++----------------------------------------------------------------------------------------------------------+-----------+
+| `Intellectual disability, profound (HP:0002187) `_ | 2 |
++----------------------------------------------------------------------------------------------------------+-----------+
+| `Intellectual disability (HP:0001249) `_ | 1 |
++----------------------------------------------------------------------------------------------------------+-----------+
+
+If none of these terms is found, a score of zero is assigned for this section.
+
+
+Prenatal-onset growth retardation
+~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
+In the original score, two points are assigned if Prenatal-onset growth retardation is present. In our implementation,
+we assign two points if either of the following terms is present (the score is thus either zero or two).
+
++----------------------------------------------------------------------------------------------------------+-----------+
+| HPO term | Score |
++==========================================================================================================+===========+
+| `Small for gestational age (HP:0001518) `_ | 2 |
++----------------------------------------------------------------------------------------------------------+-----------+
+| `Intrauterine growth retardation (HP:0001511) `_ | 2 |
++----------------------------------------------------------------------------------------------------------+-----------+
+
+
+
+
+Postnatal growth abnormalities
+~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
+
+In the original score, one point is assigned for each of Microcephaly, Short stature, Macrocephaly, and Tall stature,
+with the maximum score for the section being limited to 2 points. We implement this as adding one point for either the
+corresponding HPO terms or any of their descendents (for instance, `Disproportionate short stature (HP:0003498) `_ would
+be counted for `Short stature (HP:0004322) `_).
+
++----------------------------------------------------------------------------------------------------------+-----------+
+| HPO term | Score |
++==========================================================================================================+===========+
+| `Microcephaly (HP:0000252) `_ | 1 |
++----------------------------------------------------------------------------------------------------------+-----------+
+| `Short stature (HP:0004322) `_ | 1 |
++----------------------------------------------------------------------------------------------------------+-----------+
+| `Macrocephaly (HP:0000256) `_ | 1 |
++----------------------------------------------------------------------------------------------------------+-----------+
+| `Tall stature (HP:0000098) `_ | 1 |
++----------------------------------------------------------------------------------------------------------+-----------+
+
+If none of these terms is found, a score of zero is assigned for this section. Logically, the maximum score obtainable
+is 2 because the same individual cannot have both tall and short stature or both micro- and macrocephaly.
+
+
+Facial dysmorphic features
+~~~~~~~~~~~~~~~~~~~~~~~~~~
+
+This section assigns two points if two or more anomalies are identified in the following
+categories: hypertelorism, nasal anomalies and ear anomalies. Our implementation of this feature counts the total
+number of terms or descendents of the following HPO terms.
+
++----------------------------------------------------------------------------------------------------------+-----------+
+| HPO term | Score |
++==========================================================================================================+===========+
+| `Hypertelorism (HP:0000316) `_ | 1 |
++----------------------------------------------------------------------------------------------------------+-----------+
+| `Abnormal external nose morphology (HP:0010938) `_ | 1 each |
++----------------------------------------------------------------------------------------------------------+-----------+
+| `Abnormal pinna morphology (HP:0000377) `_ | 1 each |
++----------------------------------------------------------------------------------------------------------+-----------+
+
+If two or more terms are found, the score is 2, otherwise a score of zero is assigned.
+
+
+Non-facial dysmorphism and congenital abnormalities
+~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
+One point is assigned for either the
+corresponding HPO terms or any of their descendents up to a maximum of two points.
+
++----------------------------------------------------------------------------------------------------------+-----------+
+| HPO term | Score |
++==========================================================================================================+===========+
+| `Abnormal hand morphology (HP:0005922) `_ | 1 each |
++----------------------------------------------------------------------------------------------------------+-----------+
+| `Abnormal heart morphology (HP:0001627) `_ | 1 each |
++----------------------------------------------------------------------------------------------------------+-----------+
+| `Hypospadias (HP:0000047) `_ | 1 |
++----------------------------------------------------------------------------------------------------------+-----------+
+
+Final score
+~~~~~~~~~~~
+
+The final score is obtained by summing the scores from each of the sections. The final score ranges from 0 to 10, with
+higher scores being considered a proxy for higher clinical severity.
+
+
+Using the De Vries Scorer in code
+~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
+
+TODO
+
+
diff --git a/docs/user-guide/index.rst b/docs/user-guide/index.rst
index 9f7933eea..f3e0569ab 100644
--- a/docs/user-guide/index.rst
+++ b/docs/user-guide/index.rst
@@ -13,6 +13,7 @@ TODO - write high level overview and bridge to individual sections.
input-data
exploratory
predicates
+ phenotype_predicates
stats
mtc
glossary
diff --git a/docs/user-guide/phenotype_predicates.rst b/docs/user-guide/phenotype_predicates.rst
new file mode 100644
index 000000000..86572657f
--- /dev/null
+++ b/docs/user-guide/phenotype_predicates.rst
@@ -0,0 +1,18 @@
+.. _phenotype_predicates:
+
+====================
+Phenotype Predicates
+====================
+
+GPSEA offers several phenotype predicates.
+
+TODO -- separate explanations for HPO (Fisher), scores (Mann Whitney) and survival (log rank test).
+
+
+
+
+.. toctree::
+ :maxdepth: 1
+ :caption: Contents:
+
+ devries
diff --git a/src/gpsea/analysis/pscore/__init__.py b/src/gpsea/analysis/pscore/__init__.py
index d03f6fd99..ce9c0e89d 100644
--- a/src/gpsea/analysis/pscore/__init__.py
+++ b/src/gpsea/analysis/pscore/__init__.py
@@ -1,7 +1,7 @@
from ._api import PhenotypeScorer, PhenotypeScoreAnalysis, PhenotypeScoreAnalysisResult
-from ._impl import CountingPhenotypeScorer
+from ._impl import CountingPhenotypeScorer, DeVriesPhenotypeScorer
__all__ = [
'PhenotypeScorer', 'PhenotypeScoreAnalysis', 'PhenotypeScoreAnalysisResult',
- 'CountingPhenotypeScorer',
+ 'CountingPhenotypeScorer', 'DeVriesPhenotypeScorer',
]
diff --git a/src/gpsea/analysis/pscore/_api.py b/src/gpsea/analysis/pscore/_api.py
index a2899734f..36caa0e93 100644
--- a/src/gpsea/analysis/pscore/_api.py
+++ b/src/gpsea/analysis/pscore/_api.py
@@ -11,8 +11,35 @@
class PhenotypeScorer(metaclass=abc.ABCMeta):
"""
`PhenotypeScorer` assigns the patient with a phenotype score.
+
+ The score can be :attr:`math.nan` if it is not possible to compute the score for a patient.
+
+ The scorer can be created by wrapping a scoring function (see :func:`~PhenotypeScorer.wrap_scoring_function`).
"""
+ @staticmethod
+ def wrap_scoring_function(
+ func: typing.Callable[[Patient], float],
+ ) -> "PhenotypeScorer":
+ """
+ Create a `PhenotypeScorer` by wrap the provided scoring function `func`.
+
+ The function must take exactly one argument of type :class:`~gpsea.model.Patient`
+ and return a `float` with the corresponding phenotype score.
+
+ Example
+ ^^^^^^^
+
+ >>> from gpsea.analysis.pscore import PhenotypeScorer
+ >>> def f(p): 123.4
+ >>> phenotype_scorer = PhenotypeScorer.wrap_scoring_function(f)
+
+ `phenotype_scorer` will assign all patients a score of `123.4`.
+
+ :param func: the scoring function.
+ """
+ return FunctionPhenotypeScorer(func=func)
+
def score(self, patient: Patient) -> float:
"""
Compute the score for the `patient`.
@@ -20,6 +47,25 @@ def score(self, patient: Patient) -> float:
pass
+class FunctionPhenotypeScorer(PhenotypeScorer):
+ """
+ `FunctionPhenotypeScorer` computes the phenotype score using the provided function/closure.
+ """
+ # NOT PART OF THE PUBLIC API
+
+ def __init__(
+ self,
+ func: typing.Callable[[Patient], float],
+ ):
+ self._func = func
+
+ def score(self, patient: Patient) -> float:
+ """
+ Apply the function to compute the phenotype score.
+ """
+ return self._func(patient)
+
+
class PhenotypeScoreAnalysisResult:
"""
`PhenotypeScoreAnalysisResult` is a container for :class:`PhenotypeScoreAnalysis` results.
@@ -76,8 +122,13 @@ def plot_boxplots(
# skip the patients with unassigned genotype group
not_na_gts = self._genotype_phenotype_scores["genotype"].notna()
data = self._genotype_phenotype_scores.loc[not_na_gts]
+
+ # Check that the provided genotype predicate defines the same categories
+ # as those found in `data.`
actual = set(data["genotype"].unique())
- expected = gt_predicate.get_categorizations()
+ expected = set(c.cat_id for c in gt_predicate.get_categories())
+ assert actual == expected, 'Mismatch in the genotype categories'
+
x = [
data.loc[data["genotype"] == c.category.cat_id, "phenotype"].to_list()
for c in gt_predicate.get_categorizations()
diff --git a/src/gpsea/analysis/pscore/_impl.py b/src/gpsea/analysis/pscore/_impl.py
index 3d3adbaa5..16931c398 100644
--- a/src/gpsea/analysis/pscore/_impl.py
+++ b/src/gpsea/analysis/pscore/_impl.py
@@ -12,7 +12,7 @@ class CountingPhenotypeScorer(PhenotypeScorer):
that is equivalent to the count of present phenotypes that are either
an exact match to the `query` terms or their descendants.
- For instance, we may want to count whether an individual has brain, liver, kidney, and skin abormalities.
+ For instance, we may want to count whether an individual has brain, liver, kidney, and skin abnormalities.
In the case, the query would include the corresponding terms (e.g., Abnormal brain morphology HP:0012443).
An individual can then have between 0 and 4 phenotype group abnormalities.
This predicate is intended to be used with the Mann Whitney U test.
@@ -20,8 +20,8 @@ class CountingPhenotypeScorer(PhenotypeScorer):
@staticmethod
def from_query_curies(
- hpo: hpotk.MinimalOntology,
- query: typing.Iterable[typing.Union[str, hpotk.TermId]],
+ hpo: hpotk.MinimalOntology,
+ query: typing.Iterable[typing.Union[str, hpotk.TermId]],
):
"""
Create a scorer to test for the number of phenotype terms that fall into the phenotype groups.
@@ -42,7 +42,7 @@ def from_query_curies(
f"query argument must be iterable of hpotk TermId's or strings but we found {type(q)}"
)
- # Now chack that the term IDs are HPO term IDs.
+ # Now check that the term IDs are HPO term IDs.
if q not in hpo:
raise ValueError(f"The query {q} was not found in the HPO")
query_term_ids.add(q)
@@ -65,9 +65,9 @@ def from_query_curies(
)
def __init__(
- self,
- hpo: hpotk.MinimalOntology,
- query: typing.Iterable[hpotk.TermId],
+ self,
+ hpo: hpotk.MinimalOntology,
+ query: typing.Iterable[hpotk.TermId],
):
self._hpo = hpo
self._query = set(query)
@@ -76,8 +76,8 @@ def get_question(self) -> str:
return "How many of the query HPO terms (or their descendants) does the individual display"
def score(
- self,
- patient: Patient,
+ self,
+ patient: Patient,
) -> float:
"""
Get the count (number) of terms in the query set
@@ -101,12 +101,213 @@ def score(
return count
- # def __call__(
- # self,
- # *args: typing.Any,
- # **kwds: typing.Any,
- # ) -> float:
- # # TODO: move to `PhenotypeScorer` API.
- # assert len(args) == 1 and isinstance(args[0], Patient), 'The first argument must be an instance of `Patient`'
- # assert len(kwds) == 0, 'We do not take any key-word arguments'
- # return self.score(args[0])
+
+class DeVriesPhenotypeScorer(PhenotypeScorer):
+ """
+ `DeVriesPhenotypeScorer` computes "adapted De Vries Score"
+ as described in `Feenstra et al. `_.
+ """
+
+ def __init__(
+ self,
+ hpo: hpotk.MinimalOntology,
+ ):
+ self._hpo = hpo
+
+ # severe and profound GDD
+ self._gdd_tids = {
+ 'HP:0011344': 2, 'HP:0012736': 2,
+ 'HP:0011342': 1, 'HP:0011343': 1, 'HP:0001263': 1,
+ }
+
+ # mild, moderate, and unspecified GDD (borderline has 0.5)
+ self._idd_tids = {
+ 'HP:0010864': 2, 'HP:0002187': 2,
+ 'HP:0001256': 1, 'HP:0002342': 1, 'HP:0001249': 1,
+ 'HP:0006889': 0.5,
+ }
+
+ def _developmental_delay_score(
+ self,
+ observed_term_ids: typing.Iterable[str],
+ ) -> float:
+ """
+ Calculate the dev delay component of the score
+
+ Args:
+ observed_term_ids: terms observed in patient
+
+ Returns: a score between 0 and 2
+ """
+ # Check GDD terms with higher priority than ID terms.
+ # Global developmental delay
+ for t in observed_term_ids:
+ if t in self._gdd_tids:
+ return self._gdd_tids[t]
+
+ # Intellectual disability
+ for t in observed_term_ids:
+ if t in self._idd_tids:
+ return self._idd_tids[t]
+
+ return 0
+
+ def _term_or_descendant(
+ self,
+ target_tid: str,
+ observed_term_ids: typing.Iterable[str],
+ ) -> int:
+ """
+ Args:
+ target_tid: term of interest
+ observed_term_ids: all terms observed in patient
+
+ Returns:
+ 1 if the term or any descendant is present in the patient, otherwise 0
+ """
+ for term_id in observed_term_ids:
+ if term_id == target_tid \
+ or any(ancestor == target_tid for ancestor in self._hpo.graph.get_ancestors(term_id)):
+ return 1
+
+ return 0
+
+ def _term_or_descendant_count(
+ self,
+ target_tid: str,
+ observed_term_ids: typing.Iterable[str],
+ ) -> int:
+ """
+ Args:
+ target_tid: term of interest
+ observed_term_ids: all terms observed in patient
+
+ Returns:
+ the total count of the terms equal to or descending from the target_tid
+ """
+ total_count = 0
+ for term_id in observed_term_ids:
+ for desc_tid in self._hpo.graph.get_ancestors(term_id, include_source=True):
+ if desc_tid.value == target_tid:
+ total_count += 1
+ return total_count
+
+ def _postnatal_growth_score(
+ self,
+ observed_term_ids: typing.Iterable[str],
+ ) -> int:
+ """
+ Calculate the postnatal growth component of the score.
+
+ Args:
+ observed_term_ids: terms observed in patient
+
+ Returns: an `int` (between 0 and 2)
+ """
+ microcephaly = 'HP:0000252'
+ short_stature = 'HP:0004322'
+ macrocephaly = 'HP:0000256'
+ tall_stature = 'HP:0000098'
+ total_count = 0
+ for tid in (microcephaly, short_stature, macrocephaly, tall_stature):
+ total_count += self._term_or_descendant(tid, observed_term_ids)
+ if total_count > 2:
+ raise ValueError(f"Inconsistent annotations for postnatal growth score {total_count}: {observed_term_ids}")
+ return total_count
+
+ def _facial_dysmorphism_score(
+ self,
+ observed_term_ids: typing.Collection[str],
+ ) -> int:
+ """
+ This section assigns two points if two or more anomalies are identified in the following
+ categories: hypertelorism, nasal anomalies and ear anomalies. Our implementation counts the total
+ number of terms or descendants of the hypertelorism, Abnormal external nose morphology, and
+ Abnormal pinna morphology.
+
+ Args:
+ observed_term_ids: terms observed in patient
+
+ Returns: facial dysmorphism score (between 0 and 2)
+
+ """
+ hypertelorism = 'HP:0000316'
+ external_nose = 'HP:0010938'
+ pinna_morphology = 'HP:0000377'
+
+ # No need to inspect descendants since Hypertelorism has none.
+ total_count = 1 if hypertelorism in observed_term_ids else 0
+ total_count += self._term_or_descendant_count(target_tid=external_nose, observed_term_ids=observed_term_ids)
+ total_count += self._term_or_descendant_count(target_tid=pinna_morphology, observed_term_ids=observed_term_ids)
+ if total_count > 1:
+ return 2
+ else:
+ return 0
+
+ def _congenital_score(
+ self,
+ observed_term_ids: typing.Iterable[str],
+ ) -> int:
+ """
+ Non-facial dysmorphism and congenital abnormalities component.
+ One point is assigned for either the corresponding HPO terms or any of their descendents up to a maximum of 2.
+
+ Args:
+ observed_term_ids: terms observed in patient
+
+ Returns: Non-facial dysmorphism and congenital abnormalities score (between 0 and 2)
+
+ """
+ hypospadias = 'HP:0000047'
+ abnormal_hand_morphology = 'HP:0005922'
+ abnormal_heart_morphology = 'HP:0001627'
+ # total_count = len([t for t in observed_term_ids if t == hypospadias])
+ total_count = self._term_or_descendant_count(
+ target_tid=hypospadias, observed_term_ids=observed_term_ids,
+ )
+ total_count += self._term_or_descendant_count(target_tid=abnormal_hand_morphology,
+ observed_term_ids=observed_term_ids)
+ total_count += self._term_or_descendant_count(target_tid=abnormal_heart_morphology,
+ observed_term_ids=observed_term_ids)
+ return min(2, total_count)
+
+ def _prenatal_growth_score(
+ self,
+ observed_term_ids: typing.Iterable[str],
+ ) -> int:
+ """
+ Two points are assigned if Prenatal-onset growth retardation is present.
+
+ Args:
+ observed_term_ids: list of strings with term identifiers or observed HPO terms
+
+ Returns: score between 0 and 2
+
+ """
+ small_for_gestational_age = 'HP:0001518'
+ intrauterine_growth_retardation = 'HP:0001511'
+ targets = (small_for_gestational_age, intrauterine_growth_retardation)
+ for tid in observed_term_ids:
+ if tid in targets:
+ return 2
+ return 0
+
+ def score(self, patient: Patient) -> float:
+ """
+ Calculate score based on list of strings with term identifiers or observed HPO terms.
+
+ Args:
+ patient: list of strings with term identifiers or observed HPO terms
+
+ Returns: de Vries score between 0 and 10
+
+ """
+ observed_term_ids = tuple(tid.identifier.value for tid in patient.present_phenotypes())
+
+ delay_score = self._developmental_delay_score(observed_term_ids)
+ growth_score = self._postnatal_growth_score(observed_term_ids)
+ facial_score = self._facial_dysmorphism_score(observed_term_ids)
+ congen_score = self._congenital_score(observed_term_ids)
+ prenatal_score = self._prenatal_growth_score(observed_term_ids)
+
+ return delay_score + growth_score + facial_score + congen_score + prenatal_score
diff --git a/src/gpsea/model/_phenotype.py b/src/gpsea/model/_phenotype.py
index def0ec9c4..267f0ec48 100644
--- a/src/gpsea/model/_phenotype.py
+++ b/src/gpsea/model/_phenotype.py
@@ -13,7 +13,30 @@ class Phenotype(hpotk.model.Identified, hpotk.model.ObservableFeature):
@staticmethod
def from_term(term: hpotk.model.MinimalTerm, is_observed: bool):
- return Phenotype(term.identifier, is_observed)
+ return Phenotype.from_raw_parts(term.identifier, is_observed)
+
+ @staticmethod
+ def from_raw_parts(
+ term_id: typing.Union[str, hpotk.TermId],
+ is_observed: bool,
+ ) -> "Phenotype":
+ """
+ Create `Phenotype` from a term ID and observation state.
+
+ :param term_id: a `str` with CURIE (e.g. `HP:0001250`) or a :class:`~hpotk.TermId`.
+ :param is_observed: `True` if the term ID was observed in patient or `False` if it was explicitly excluded.
+ """
+ if isinstance(term_id, str):
+ term_id = hpotk.TermId.from_curie(term_id)
+ elif isinstance(term_id, hpotk.TermId):
+ pass
+ else:
+ raise ValueError('`term_id` must be either a `str` or a `hpotk.TermId`')
+
+ return Phenotype(
+ term_id,
+ is_observed,
+ )
def __init__(
self,
diff --git a/tests/analysis/test_de_vries_scorer.py b/tests/analysis/test_de_vries_scorer.py
new file mode 100644
index 000000000..220dd18b0
--- /dev/null
+++ b/tests/analysis/test_de_vries_scorer.py
@@ -0,0 +1,85 @@
+import typing
+
+import hpotk
+import pytest
+
+from gpsea.analysis.pscore import DeVriesPhenotypeScorer
+from gpsea.model import Patient, SampleLabels, Phenotype
+
+intrauterine_growth_retardation = 'HP:0001511'
+small_for_gestational_age = 'HP:0001518'
+arachnodactyly = "HP:0001166"
+seizure = "HP:0001250"
+sensorineural_hearing_impairment = 'HP:0000407'
+intellectual_disability_mild = 'HP:0001256'
+intellectual_disability_profound = 'HP:0002187'
+microcephaly = 'HP:0000252'
+short_stature = 'HP:0004322'
+hypertelorism = 'HP:0000316'
+posteriorly_rotated_ears = 'HP:0000358'
+underdeveloped_crus_of_the_helix = 'HP:0009898' # external ear morphology
+ventricular_septal_defect = 'HP:0001629'
+metacarpal_synostosis = 'HP:0009701' # hand morphology
+hypospadias = 'HP:0000047'
+
+
+class TestDeVriesScorer:
+
+ @pytest.fixture
+ def devries_scorer(
+ self,
+ hpo: hpotk.MinimalOntology,
+ ) -> DeVriesPhenotypeScorer:
+ return DeVriesPhenotypeScorer(hpo=hpo)
+
+ @pytest.mark.parametrize(
+ "term_set, expected",
+ [
+ ([intrauterine_growth_retardation], 2,),
+ ([intrauterine_growth_retardation, small_for_gestational_age], 2,), # superfluous, still should be 2
+ ([sensorineural_hearing_impairment, ], 0,), # Unrelated
+ ([seizure, arachnodactyly], 0,), # Unrelated
+ ([intrauterine_growth_retardation, intellectual_disability_mild], 3,),
+ ([intrauterine_growth_retardation, intellectual_disability_profound], 4,),
+ ([intrauterine_growth_retardation, intellectual_disability_profound, microcephaly], 5,),
+ ([intrauterine_growth_retardation, intellectual_disability_profound, microcephaly, short_stature], 6,),
+ ([intrauterine_growth_retardation, intellectual_disability_profound, microcephaly, short_stature,
+ hypertelorism], 6,),
+ ([intrauterine_growth_retardation, intellectual_disability_profound, microcephaly, short_stature,
+ hypertelorism, posteriorly_rotated_ears], 8,),
+ ([intrauterine_growth_retardation, intellectual_disability_profound, microcephaly, short_stature,
+ hypertelorism, posteriorly_rotated_ears, underdeveloped_crus_of_the_helix], 8,),
+ ([intrauterine_growth_retardation, intellectual_disability_profound, microcephaly, short_stature,
+ hypertelorism, posteriorly_rotated_ears, underdeveloped_crus_of_the_helix,
+ ventricular_septal_defect], 9,),
+ ([intrauterine_growth_retardation, intellectual_disability_profound, microcephaly, short_stature,
+ hypertelorism, posteriorly_rotated_ears, underdeveloped_crus_of_the_helix,
+ ventricular_septal_defect, hypospadias], 10,),
+ ([intrauterine_growth_retardation, intellectual_disability_profound, microcephaly, short_stature,
+ hypertelorism, posteriorly_rotated_ears, underdeveloped_crus_of_the_helix,
+ ventricular_septal_defect, hypospadias, metacarpal_synostosis], 10,),
+
+ ],
+ )
+ def test_a_patient(
+ self,
+ term_set: typing.Sequence[str],
+ expected: int,
+ devries_scorer: DeVriesPhenotypeScorer,
+ ):
+ patient = Patient(
+ labels=SampleLabels("test"),
+ phenotypes=(
+ Phenotype.from_raw_parts(
+ term_id=curie,
+ is_observed=True,
+ )
+ for curie in term_set
+ ),
+ diseases=(),
+ variants=(),
+ )
+
+ actual = devries_scorer.score(patient)
+
+ assert actual == expected