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fix bed/clinical file validation
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@rxu17
rxu17 committed Nov 16, 2023
1 parent 661ecb7 commit ab7e882
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Showing 2 changed files with 112 additions and 54 deletions.
34 changes: 25 additions & 9 deletions genie_registry/clinical.py
View file
Original file line number Diff line number Diff line change
Expand Up @@ -1012,28 +1012,43 @@ def _get_dataframe(self, filePathList):

return clinicaldf

def _cross_validate_bed_files_exist(self, clinicaldf) -> tuple:
def _cross_validate_bed_files_exist(self, clinicaldf) -> list:
"""Check that a bed file exist per SEQ_ASSAY_ID value in clinical file"""
errors = ""
warnings = ""
missing_files = []
seq_assay_ids = clinicaldf["SEQ_ASSAY_ID"].unique().tolist()
exception_params = {"ignore_case": True, "allow_underscore": True}

# standardize and get unique seq assay ids before searching bed files
seq_assay_ids = set([
validate.standardize_string_for_validation(sq_id, **exception_params)
for sq_id in clinicaldf["SEQ_ASSAY_ID"].unique()
])

for seq_assay_id in seq_assay_ids:
bed_files = validate.parse_file_info_in_nested_list(
nested_list=self.ancillary_files,
search_str=f"{seq_assay_id}.bed", # type: ignore[arg-type]
ignore_case=True,
allow_underscore=True,
**exception_params,
)
if not bed_files["files"]:
missing_files.append(f"{seq_assay_id}.bed")
return missing_files

def _cross_validate_bed_files_exist_message(self, missing_bed_files : list) -> tuple:
"""Gets the warning/error messages given the missing bed files list
Args:
missing_bed_files (list): list of missing bed files
if missing_files:
Returns:
tuple: error + warning
"""
errors = ""
warnings = ""
if missing_bed_files:
errors = (
"At least one SEQ_ASSAY_ID in your clinical file does not have an associated BED file. "
"Please update your file(s) to be consistent.\n"
f"Missing BED files: {', '.join(missing_files)}\n"
f"Missing BED files: {', '.join(missing_bed_files)}\n"
)
return errors, warnings

Expand Down Expand Up @@ -1087,7 +1102,8 @@ def _cross_validate(self, clinicaldf) -> tuple:
errors_assay, warnings_assay = self._cross_validate_assay_info_has_seq(
clinicaldf
)
errors_bed, warnings_bed = self._cross_validate_bed_files_exist(clinicaldf)
missing_bed_files = self._cross_validate_bed_files_exist(clinicaldf)
errors_bed, warnings_bed = self._cross_validate_bed_files_exist_message(missing_bed_files)

errors = errors_assay + errors_bed
warnings = warnings_assay + warnings_bed
Expand Down
132 changes: 87 additions & 45 deletions tests/test_clinical.py
View file
Original file line number Diff line number Diff line change
@@ -1,3 +1,4 @@
from collections import Counter
import datetime
import json
from unittest import mock
Expand Down Expand Up @@ -1061,65 +1062,73 @@ def test__check_int_dead_consistency_inconsistent(inconsistent_df):
)


@pytest.mark.parametrize(
"test_clinical_df,test_ancillary_files,expected_error,expected_warning",
[
(
pd.DataFrame(
{"SEQ_ASSAY_ID": ["SAGE-1-1", "SAGE-SAGE-1", "SAGE-1", "SAGE-1"]}
def get_cross_validate_bed_files_test_cases():
return [
{
"name": "all_match",
"test_clinical_df": pd.DataFrame(
{
"SEQ_ASSAY_ID": [
"SAGE-1-1",
"SAGE-SAGE-1",
"SAGE-1",
"SAGE-1",
"SaGe-1",
]
}
),
[
"test_ancillary_files": [
[{"name": "SAGE-SAGE-1.bed", "path": ""}],
[{"name": "SAGE-1-1.bed", "path": ""}],
[{"name": "SAGE-1.bed", "path": ""}],
],
"",
"",
),
(
pd.DataFrame({"SEQ_ASSAY_ID": ["SAGE-1-1", "SAGE-1-2"]}),
[
"expected_missing_files": [],
},
{
"name": "partial_match",
"test_clinical_df": pd.DataFrame(
{"SEQ_ASSAY_ID": ["SAGE-1-1", "SAGE-1-2", "SaGe-1_1"]}
),
"test_ancillary_files": [
[{"name": "SAGE-SAGE-1.bed", "path": ""}],
[{"name": "SAGE-1-1.bed", "path": ""}],
[{"name": "SAGE-1.bed", "path": ""}],
],
"At least one SEQ_ASSAY_ID in your clinical file does not have an associated BED file. "
"Please update your file(s) to be consistent.\n"
"Missing BED files: SAGE-1-2.bed\n",
"",
),
(
pd.DataFrame({"SEQ_ASSAY_ID": ["SAGE-1-2", "SAGE-1-3"]}),
[
"expected_missing_files": ["sage-1-2.bed"],
},
{
"name": "no_match",
"test_clinical_df": pd.DataFrame(
{"SEQ_ASSAY_ID": ["SAGE-1-2", "SAGE-1-3", "SaGe_1_2"]}
),
"test_ancillary_files": [
[{"name": "SAGE-SAGE-1.bed", "path": ""}],
[{"name": "SAGE-1-1.bed", "path": ""}],
[{"name": "SAGE-1.bed", "path": ""}],
],
"At least one SEQ_ASSAY_ID in your clinical file does not have an associated BED file. "
"Please update your file(s) to be consistent.\n"
"Missing BED files: SAGE-1-2.bed, SAGE-1-3.bed\n",
"",
),
(
pd.DataFrame({"SEQ_ASSAY_ID": ["SAGE-1-2", "SAGE-1-3"]}),
[
"expected_missing_files": ["sage-1-2.bed", "sage-1-3.bed"],
},
{
"name": "no_bed_files",
"test_clinical_df": pd.DataFrame(
{"SEQ_ASSAY_ID": ["SAGE-1-2", "SAGE-1-3", "SAge-1_2"]}
),
"test_ancillary_files": [
[{"name": "SAGE-1.txt", "path": ""}],
],
"At least one SEQ_ASSAY_ID in your clinical file does not have an associated BED file. "
"Please update your file(s) to be consistent.\n"
"Missing BED files: SAGE-1-2.bed, SAGE-1-3.bed\n",
"",
),
],
ids=["all_match", "partial_match", "no_match", "no_bed_files"],
"expected_missing_files": ["sage-1-2.bed", "sage-1-3.bed"],
},
]

@pytest.mark.parametrize(
"test_cases", get_cross_validate_bed_files_test_cases(), ids=lambda x: x["name"]
)
def test_that_cross_validate_bed_files_exist_returns_correct_msgs(
clin_class, test_clinical_df, test_ancillary_files, expected_error, expected_warning
clin_class, test_cases
):
clin_class.ancillary_files = test_ancillary_files
errors, warnings = clin_class._cross_validate_bed_files_exist(test_clinical_df)
assert errors == expected_error
assert warnings == expected_warning
clin_class.ancillary_files = test_cases["test_ancillary_files"]
missing_files = clin_class._cross_validate_bed_files_exist(test_cases["test_clinical_df"])
assert Counter(test_cases["expected_missing_files"]) == Counter(missing_files)


def test_that_cross_validate_bed_files_exist_calls_expected_methods(clin_class):
Expand All @@ -1138,29 +1147,62 @@ def test_that_cross_validate_bed_files_exist_calls_expected_methods(clin_class):
clin_class._cross_validate_bed_files_exist(test_clinical_df)
patch_parse_file_info.assert_called_once_with(
nested_list=clin_class.ancillary_files,
search_str="SAGE-SAGE-1.bed",
search_str="sage-sage-1.bed",
ignore_case=True,
allow_underscore=True,
)


@pytest.mark.parametrize(
"missing_files,expected_error,expected_warning",
[
(
[],
"",
"",
),
(
["test1.bed", "test2.bed"],
"At least one SEQ_ASSAY_ID in your clinical file does not have an associated BED file. "
"Please update your file(s) to be consistent.\n"
"Missing BED files: test1.bed, test2.bed\n",
"",
),
],
ids=["no_missing_files", "missing_files"],
)
def test_that_cross_validate_bed_files_exist_message_returns_correct_msgs(
clin_class, missing_files, expected_error, expected_warning
):
errors, warnings = clin_class._cross_validate_bed_files_exist_message(missing_files)
assert errors == expected_error
assert warnings == expected_warning


def test_that__cross_validate_calls_expected_methods(clin_class):
with mock.patch.object(
Clinical, "_cross_validate_assay_info_has_seq", return_value=("", "")
) as patch__cross_validate_assay, mock.patch.object(
Clinical, "_cross_validate_bed_files_exist", return_value=("", "")
) as patch__cross_validate_bed:
) as patch__cross_validate_bed, mock.patch.object(
Clinical, "_cross_validate_bed_files_exist_message", return_value=("", "")
) as patch__cross_validate_bed_msg:
clin_class._cross_validate(clinicaldf=pd.DataFrame({"something": [1]}))
patch__cross_validate_assay.assert_called_once()
patch__cross_validate_bed.assert_called_once()
patch__cross_validate_bed_msg.assert_called_once()


def test_that__cross_validate_returns_correct_format_for_errors_warnings(clin_class):
with mock.patch.object(
Clinical, "_cross_validate_assay_info_has_seq", return_value=("test1", "")
) as patch__cross_validate_assay, mock.patch.object(
Clinical, "_cross_validate_bed_files_exist", return_value=("test3\n", "")
) as patch__cross_validate_bed:
Clinical, "_cross_validate_bed_files_exist", return_value=["something_missing"]
) as patch__cross_validate_bed, mock.patch.object(
Clinical,
"_cross_validate_bed_files_exist_message",
return_value=("test3\n", ""),
) as patch__cross_validate_bed_msg:
errors, warnings = clin_class._cross_validate(
clinicaldf=pd.DataFrame({"something": [1]})
)
Expand Down

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