Merge pull request #302 from monarch-initiative/fix-gt-category-refactor

Update tests to reflect the genotype category label changes

docs/tutorial.rst

@@ -315,10 +315,10 @@ and these are the tested HPO terms ordered by the p value corrected with the Ben
    :file: report/tbx5_frameshift_vs_missense.csv
    :header-rows: 2
 
-  .. doctest:: tutorial
-    :hide:
+.. doctest:: tutorial
+  :hide:
 
-    >>> summary_df.to_csv('docs/report/tbx5_frameshift_vs_missense.csv')  # doctest: +SKIP
+  >>> summary_df.to_csv('docs/report/tbx5_frameshift_vs_missense.csv')  # doctest: +SKIP
 
 We see that several HPO terms are significantly associated
 with presence of a frameshift variant in *TBX5*.

docs/user-guide/analyses/phenotype-groups.rst

@@ -126,10 +126,10 @@ we expect the autosomal dominant mode of inheritance:
 >>> from gpsea.analysis.predicate.genotype import autosomal_dominant
 >>> gt_predicate = autosomal_dominant(is_frameshift)
 >>> gt_predicate.display_question()
-'What is the genotype group: HOM_REF, HET'
+'What is the genotype group: No allele, Monoallelic'
 
-`gt_predicate` will assign the patients with no frameshift variant allele into `HOM_REF` group
-and the patients with one frameshift allele will be assigned into `HET` group.
+`gt_predicate` will assign the patients with no frameshift variant allele into `No allele` group
+and the patients with one frameshift allele will be assigned into `Monoallelic` group.
 Note, any patient with 2 or more alleles will be *omitted* from the analysis.
 
 .. note::
@@ -239,13 +239,16 @@ We can learn more by showing the MTC filter report:
 >>> from gpsea.view import MtcStatsViewer
 >>> mtc_viewer = MtcStatsViewer()
 >>> mtc_report = mtc_viewer.process(result)
->>> with open('docs/user-guide/report/tbx5_frameshift.mtc_report.html', 'w') as fh:  # doctest: +SKIP
-...     _ = fh.write(mtc_report)
-
+>>> mtc_report  # doctest: +SKIP
 
 .. raw:: html
   :file: report/tbx5_frameshift.mtc_report.html
 
+.. doctest:: phenotype-groups
+   :hide:
+
+   >>> mtc_report.write('docs/user-guide/analyses/report/tbx5_frameshift.mtc_report.html')  # doctest: +SKIP
+
 
 Genotype phenotype associations
 ===============================
@@ -255,12 +258,17 @@ ordered by the corrected p value (Benjamini-Hochberg FDR):
 
 >>> from gpsea.view import summarize_hpo_analysis
 >>> summary_df = summarize_hpo_analysis(hpo, result)
->>> summary_df.to_csv('docs/user-guide/report/tbx5_frameshift.csv')  # doctest: +SKIP
+>>> summary_df  # doctest: +SKIP
 
 .. csv-table:: *TBX5* frameshift vs rest
    :file: report/tbx5_frameshift.csv
    :header-rows: 2
 
+.. doctest:: phenotype-groups
+   :hide:
+
+   >>> summary_df.to_csv('docs/user-guide/analyses/report/tbx5_frameshift.csv')  # doctest: +SKIP
+
 
 The table shows that several HPO terms are significantly associated
 with presence of a heterozygous (`HET`) frameshift variant in *TBX5*.

docs/user-guide/analyses/report/tbx5_frameshift.csv

@@ -1,4 +1,4 @@
-What is the genotype group,HOM_REF,HOM_REF,HET,HET,,
+What is the genotype group,No allele,No allele,Monoallelic,Monoallelic,,
 ,Count,Percent,Count,Percent,Corrected p values,p values
 Ventricular septal defect [HP:0001629],42/71,59%,19/19,100%,0.003870827221893892,0.00024192670136836825
 Abnormal atrioventricular conduction [HP:0005150],1/23,4%,3/3,100%,0.01230769230769231,0.0015384615384615387

docs/user-guide/predicates/mode_of_inheritance_predicate.rst

@@ -29,15 +29,15 @@ to assign an individual into one of the following categories:
 
 .. table:: Autosomal dominant predicate categories
 
-    +------------------+-------------+
-    |   Allele count   |  Category   |
-    +==================+=============+
-    |   0              |  `HOM_REF`  |
-    +------------------+-------------+
-    |   1              |  `HET`      |
-    +------------------+-------------+
-    |   :math:`\ge 2`  |  ``None``   |
-    +------------------+-------------+
+    +------------------+----------------+
+    |   Allele count   |  Category      |
+    +==================+================+
+    |   0              |  `No allele`   |
+    +------------------+----------------+
+    |   1              |  `Monoallelic` |
+    +------------------+----------------+
+    |   :math:`\ge 2`  |  ``None``      |
+    +------------------+----------------+
 
 Examples
 ========
@@ -50,7 +50,7 @@ We can create the predicate with the :func:`~gpsea.analysis.predicate.genotype.a
 >>> from gpsea.analysis.predicate.genotype import autosomal_dominant
 >>> gt_predicate = autosomal_dominant()
 >>> gt_predicate.display_question()
-'What is the genotype group: HOM_REF, HET'
+'What is the genotype group: No allele, Monoallelic'
 
 
 Use a variant subset
@@ -80,18 +80,18 @@ an individual into one of the genotype categories:
     +------------------+-------------------+----------------+
     |   Allele count   |  Category         | Category index |
     +==================+===================+================+
-    |   0              |  `HOM_REF`        | 0              |
+    |   0              |  `No allele`      | 0              |
     +------------------+-------------------+----------------+
-    |   1              |  `HET`            | 1              |
+    |   1              |  `Monoallelic`    | 1              |
     +------------------+-------------------+----------------+
-    |   2              |  `BIALLELIC_ALT`  | 2              |
+    |   2              |  `Biallelic`      | 2              |
     +------------------+-------------------+----------------+
     |   :math:`\ge 3`  |  ``None``         |                |
     +------------------+-------------------+----------------+
 
 .. note::
 
-    `BIALLELIC_ALT` includes both homozygous and compound heterozygous genotypes.
+    `Biallelic` includes both homozygous and compound heterozygous genotypes.
 
 
 Partitions
@@ -100,7 +100,7 @@ Partitions
 Sometimes we are interested in lumping several genotype categories into a group or and then comparing the groups.
 For instance, to compare phenotype of the individuals with *at least one* frameshift allele
 with those with *no* frameshift allele. Alternatively, we may only want to analyze a subset of the genotype categories,
-such as `HET` vs. `BIALLELIC_ALT`.
+such as `Monoallelic` vs. `Biallelic`.
 
 The `partitions` option of the :func:`~gpsea.analysis.predicate.genotype.autosomal_recessive` function
 lets us do this.
@@ -127,7 +127,7 @@ with the :func:`~gpsea.analysis.predicate.genotype.autosomal_recessive` function
 >>> from gpsea.analysis.predicate.genotype import autosomal_recessive
 >>> gt_predicate = autosomal_recessive()
 >>> gt_predicate.display_question()
-'What is the genotype group: HOM_REF, HET, BIALLELIC_ALT'
+'What is the genotype group: No allele, Monoallelic, Biallelic'
 
 
 Use a variant subset
@@ -148,22 +148,22 @@ and then use it to create the autosomal recessive predicate:
 
 >>> gt_predicate = autosomal_recessive(is_missense)
 >>> gt_predicate.display_question()
-'What is the genotype group: HOM_REF, HET, BIALLELIC_ALT'
+'What is the genotype group: No allele, Monoallelic, Biallelic'
 
 This predicate will assign the individuals into one of the listed genotype categories
 based on the allele counts of the missense variants.
 
 
-Compare `HET` vs. `BIALLELIC_ALT`
----------------------------------
+Compare `Monoallelic` vs. `Biallelic`
+-------------------------------------
 
 We can provide ``partitions`` to only compare the heterozygotes with those carrying
 biallelic alt mutations (homozygous alternate or compound heterozygous):
 
 We consult the *Autosomal recessive predicate categories* table for the category indices
 and we create the genotype group partitions:
 
->>> # `1` for `HET` and `2` for `BIALLELIC_ALT`
+>>> # `1` for `Monoallelic` and `2` for `Biallelic`
 >>> partitions = ({1,}, {2,})
 
 which we use to create the autosomal recessive predicate:
@@ -172,4 +172,4 @@ which we use to create the autosomal recessive predicate:
 ...     partitions=partitions,    
 ... )
 >>> gt_predicate.display_question()
-'What is the genotype group: HET, BIALLELIC_ALT'
+'What is the genotype group: Monoallelic, Biallelic'

src/gpsea/analysis/predicate/genotype/_test__gt_predicates.py

@@ -66,25 +66,25 @@ def test_build_count_to_cat(
             [(0,), (1,)],
             ModeOfInheritanceInfo.autosomal_dominant(),
             {
-                0: "HOM_REF",
-                1: "HET",
+                0: "No allele",
+                1: "Monoallelic",
             },
         ),
         (
             [(0,), (1,), (2,)],
             ModeOfInheritanceInfo.autosomal_recessive(),
             {
-                0: "HOM_REF",
-                1: "HET",
-                2: "BIALLELIC_ALT",
+                0: "No allele",
+                1: "Monoallelic",
+                2: "Biallelic",
             },
         ),
         (
             [(1,), (2,)],
             ModeOfInheritanceInfo.autosomal_recessive(),
             {
-                1: "HET",
-                2: "BIALLELIC_ALT",
+                1: "Monoallelic",
+                2: "Biallelic",
             },
         ),
     ],

src/gpsea/preprocessing/_config.py

@@ -430,7 +430,7 @@ def load_phenopacket_files(
 
 
 def load_phenopackets(
-    phenopackets: typing.Iterator[Phenopacket],
+    phenopackets: typing.Iterable[Phenopacket],
     cohort_creator: CohortCreator[Phenopacket],
     validation_policy: typing.Literal["permissive", "lenient", "strict"] = "permissive",
 ) -> typing.Tuple[Cohort, PreprocessingValidationResult]:

src/gpsea/view/_report.py

@@ -43,11 +43,12 @@ def html(self) -> str:
 
     def write(self, fh: typing.Union[io.IOBase, str]):
         should_close = isinstance(fh, str)
+        fout = None
         try:
             fout = open_text_io_handle_for_writing(fh)
             fout.write(self._html)
         except Exception:
-            if should_close:
+            if should_close and fout is not None:
                 fout.close()
 
     def _repr_html_(self) -> str:

tests/analysis/predicate/genotype/test_gt_predicates.py

@@ -91,9 +91,9 @@ def variant_predicate(self) -> VariantPredicate:
     @pytest.mark.parametrize(
         "patient_name,name",
         [
-            ("adam", "HOM_REF"),
-            ("eve", "HET"),
-            ("cain", "HET"),
+            ("adam", "No allele"),
+            ("eve", "Monoallelic"),
+            ("cain", "Monoallelic"),
         ],
     )
     def test_autosomal_dominant(
@@ -115,9 +115,9 @@ def test_autosomal_dominant(
     @pytest.mark.parametrize(
         "patient_name,name",
         [
-            ("adam", "HET"),  # 0/0 & 0/1
-            ("eve", "HET"),  # 0/1 & 0/0
-            ("cain", "HET"),  # 0/1 & 0/0
+            ("adam", "Monoallelic"),  # 0/0 & 0/1
+            ("eve", "Monoallelic"),  # 0/1 & 0/0
+            ("cain", "Monoallelic"),  # 0/1 & 0/0
         ],
     )
     def test_autosomal_dominant__with_default_predicate(
@@ -138,10 +138,10 @@ def test_autosomal_dominant__with_default_predicate(
     @pytest.mark.parametrize(
         "patient_name,name",
         [
-            ("walt", "HET"),
-            ("skyler", "HET"),
-            ("flynn", "BIALLELIC_ALT"),
-            ("holly", "HOM_REF"),
+            ("walt", "Monoallelic"),
+            ("skyler", "Monoallelic"),
+            ("flynn", "Biallelic"),
+            ("holly", "No allele"),
         ],
     )
     def test_autosomal_recessive(
@@ -164,10 +164,10 @@ def test_autosomal_recessive(
         "patient_name,name",
         [
             # The White family has two variants:
-            ("walt", "BIALLELIC_ALT"),  # 0/1 & 0/1
-            ("skyler", "BIALLELIC_ALT"),  # 0/1 & 0/1
-            ("flynn", "BIALLELIC_ALT"),  # 1/1 & 0/0
-            ("holly", "BIALLELIC_ALT"),  # 0/0 & 1/1
+            ("walt", "Biallelic"),  # 0/1 & 0/1
+            ("skyler", "Biallelic"),  # 0/1 & 0/1
+            ("flynn", "Biallelic"),  # 1/1 & 0/0
+            ("holly", "Biallelic"),  # 0/0 & 1/1
         ],
     )
     def test_autosomal_recessive__with_default_predicate(