def test_header_exception_labeled_header_not_allowed(
assay_file_exception_labeled_header_not_allowed):
with pytest.raises(ParseIsatabException) as excinfo:
AssayReader.from_stream(
"S1", "A1", assay_file_exception_labeled_header_not_allowed)
msg = 'Header "Factor Value" not allowed in assay.'
assert msg == str(excinfo.value)
def test_header_exception_term_source_ref_stop_iteration(
assay_file_exception_term_source_ref_stop_iteration):
with pytest.raises(ParseIsatabException) as excinfo:
AssayReader.from_stream(
"S1", "A1", assay_file_exception_term_source_ref_stop_iteration)
msg = 'Expected one more column on seeing "Term Source REF"'
assert msg == str(excinfo.value)
def test_header_exception_term_source_ref_next_column(
assay_file_exception_term_source_ref_next_column):
with pytest.raises(ParseIsatabException) as excinfo:
AssayReader.from_stream(
"S1", "A1", assay_file_exception_term_source_ref_next_column)
msg = 'Expected column "Term Accession Number" after seeing "Term Source REF"'
assert msg == str(excinfo.value)
def test_header_exception_labeled_header_format(
assay_file_exception_labeled_header_format):
with pytest.raises(ParseIsatabException) as excinfo:
AssayReader.from_stream("S1", "A1",
assay_file_exception_labeled_header_format)
msg = "Problem parsing labeled header CharacteristicsWithoutBrackets"
assert msg == str(excinfo.value)
def test_header_exception_duplicated_header(
assay_file_exception_duplicated_header):
with pytest.raises(ParseIsatabException) as excinfo:
AssayReader.from_stream("S1", "A1",
assay_file_exception_duplicated_header).read()
msg = "Found duplicated column types in header of study S1 assay A1: Characteristics[Organism]"
assert msg == str(excinfo.value)
def test_parsing_exception_invalid_column_type(assay_file_exception_invalid_column_type):
with pytest.raises(ParseIsatabException) as excinfo:
AssayReader.from_stream("S1", "A1", assay_file_exception_invalid_column_type).read()
msg = (
"Invalid column type occured \"Parameter Value\" not in ('Material Type', "
"'Characteristics', 'Comment', 'Factor Value', 'Label', 'Term Source REF', 'Unit')"
)
assert msg == str(excinfo.value)
def get(self, project_uuid=None) -> IsaData:
raw_data = self.get_raw(project_uuid)
investigation = InvestigationReader.from_stream(
input_file=io.StringIO(raw_data["investigation"]["tsv"]),
filename=raw_data["investigation"]["path"],
).read()
studies = {
path:
StudyReader.from_stream(study_id=path,
input_file=io.StringIO(details["tsv"]),
filename=path).read()
for path, details in raw_data["studies"].items()
}
if len(studies) > 1: # pragma: nocover
raise UnsupportedIsaTabFeatureException(
"More than one study found!")
study = list(studies.values())[0]
assays = {
path: AssayReader.from_stream(
study_id=study.file,
assay_id=path,
input_file=io.StringIO(details["tsv"]),
filename=path,
).read()
for path, details in raw_data["assays"].items()
}
return IsaData(investigation, raw_data["investigation"]["path"],
studies, assays)
def run_warnings_caught(args):
# Read investigation
investigation = InvestigationReader.from_stream(args.input_investigation_file).read()
args.input_investigation_file.close()
# Validate investigation
InvestigationValidator(investigation).validate()
# Read studies and assays
path_in = os.path.normpath(os.path.dirname(args.input_investigation_file.name))
studies = {}
assays = {}
for s, study_info in enumerate(investigation.studies):
if study_info.info.path:
with open(os.path.join(path_in, study_info.info.path), "rt") as inputf:
studies[s] = StudyReader.from_stream("S{}".format(s + 1), inputf).read()
if study_info.assays:
assays[s] = {}
for a, assay_info in enumerate(study_info.assays):
if assay_info.path:
with open(os.path.join(path_in, assay_info.path), "rt") as inputf:
assays[s][a] = AssayReader.from_stream(
"S{}".format(s + 1), "A{}".format(a + 1), inputf
).read()
# Validate studies and assays
for s, study_info in enumerate(investigation.studies):
if study_info.info.path:
StudyValidator(investigation, study_info, studies[s]).validate()
for a, assay_info in enumerate(study_info.assays):
if assay_info.path:
AssayValidator(investigation, study_info, assay_info, assays[s][a]).validate()
def load_investigation(i_path: typing.Union[str, Path]) -> IsaData:
"""Load investigation information from investigation files.
Study and assay files are expected to be next to the investigation file.
"""
i_path = Path(i_path)
with i_path.open("rt") as i_file:
investigation = InvestigationReader.from_stream(
input_file=i_file, filename=i_path.name).read()
studies = {}
assays = {}
for study in investigation.studies:
with (i_path.parent / study.info.path).open() as s_file:
studies[study.info.path.name] = StudyReader.from_stream(
study_id=study.info.path.name, input_file=s_file).read()
for assay in study.assays:
with (i_path.parent / assay.path).open() as a_file:
assays[assay.path.name] = AssayReader.from_stream(
study_id=studies[study.info.path.name].file.name,
assay_id=assay.path.name,
input_file=a_file,
).read()
return IsaData(investigation, str(i_path), studies, assays)
def test_assay_reader_minimal_assay_iostring2(minimal_investigation_file,
minimal_assay_file):
# Load investigation (tested elsewhere)
stringio = io.StringIO(minimal_investigation_file.read())
investigation = InvestigationReader.from_stream(stringio).read()
with pytest.warns(IsaWarning) as record:
InvestigationValidator(investigation).validate()
# Check warnings
assert 2 == len(record)
# Create new assay reader and read from StringIO with no filename indicated
stringio = io.StringIO(minimal_assay_file.read())
reader = AssayReader.from_stream("S1", "A1", stringio)
assert 5 == len(reader.header)
# Read and validate assay
assay = reader.read()
AssayValidator(investigation, investigation.studies[0],
investigation.studies[0].assays[0], assay).validate()
# Check results
assert str(assay.file) == os.path.normpath("<no file>")
assert 5 == len(assay.header)
assert 3 == len(assay.materials)
assert 1 == len(assay.processes)
assert 3 == len(assay.arcs)
def run(args):
with open(args.investigation_file, "rt") as inputf:
investigation = InvestigationReader.from_stream(inputf).read()
path = os.path.dirname(args.investigation_file)
print("digraph investigation {", file=args.output_file)
print(' rankdir = "LR";', file=args.output_file)
for s, study_info in enumerate(investigation.studies):
with open(os.path.join(path, study_info.info.path), "rt") as inputf:
study = StudyReader.from_stream("S{}".format(s + 1), inputf).read()
print(" /* study {} */".format(study_info.info.path),
file=args.output_file)
print(" subgraph clusterStudy{} {{".format(s), file=args.output_file)
print(' label = "Study: {}"'.format(study_info.info.path),
file=args.output_file)
print_dot(study, args.output_file)
print(" }", file=args.output_file)
for a, assay_info in enumerate(study_info.assays):
with open(os.path.join(path, assay_info.path), "rt") as inputf:
assay = AssayReader.from_stream("S{}".format(s + 1),
"A{}".format(a + 1),
inputf).read()
print(" /* assay {} */".format(assay_info.path),
file=args.output_file)
print(" subgraph clusterAssayS{}A{} {{".format(s, a),
file=args.output_file)
print(' label = "Assay: {}"'.format(assay_info.path),
file=args.output_file)
print_dot(assay, args.output_file)
print(" }", file=args.output_file)
print("}", file=args.output_file)
def _parse_write_assert_assay(investigation_file,
tmp_path,
quote=None,
normalize=False,
skip=None):
# Load investigation
investigation = InvestigationReader.from_stream(investigation_file).read()
InvestigationValidator(investigation).validate()
directory = os.path.normpath(os.path.dirname(investigation_file.name))
# Iterate assays
for s, study_info in enumerate(investigation.studies):
for a, assay_info in enumerate(study_info.assays):
if skip and str(assay_info.path) in skip:
continue
# Load assay
path_in = os.path.join(directory, assay_info.path)
with open(path_in, "rt") as inputf:
assay = AssayReader.from_stream("S{}".format(s + 1),
"A{}".format(a + 1),
inputf).read()
AssayValidator(investigation, study_info, assay_info,
assay).validate()
# Write assay to temporary file
path_out = tmp_path / assay_info.path
with open(path_out, "wt", newline="") as file:
AssayWriter.from_stream(assay, file, quote=quote).write()
if normalize:
# Read and write assay again
path_in = path_out
with open(path_out, "rt") as inputf:
assay = AssayReader.from_stream("S{}".format(s + 1),
"A{}".format(a + 1),
inputf).read()
AssayValidator(investigation, study_info, assay_info,
assay).validate()
path_out = tmp_path / (assay_info.path.name + "_b")
with open(path_out, "wt", newline="") as file:
AssayWriter.from_stream(assay, file, quote=quote).write()
# Sort and compare input and output
path_in_s = tmp_path / (assay_info.path.name + ".in.sorted")
path_out_s = tmp_path / (assay_info.path.name + ".out.sorted")
assert filecmp.cmp(sort_file(path_in, path_in_s),
sort_file(path_out, path_out_s),
shallow=False)
def parse_isatab(self):
"""
parse sample info from ISA-tab table
"""
logger.info("Parsing ISA-tab...")
logger.info("Read assay file: %s", self.args.isa_assay.name)
# read assay
assay = AssayReader.from_stream("S1", "A1", self.args.isa_assay).read()
# extract relevant fields
dummy = Bunch(type="", protocol_ref="")
sample_info = {}
arc_map = {a.tail: a.head for a in assay.arcs}
for m in assay.materials.values():
if m.type == "Sample Name":
sample_name = m.name
if sample_name not in sample_info:
sample_info[sample_name] = {}
key = m.unique_name
# breakpoint()
while key in arc_map:
key = arc_map[key]
if re.match(
"Library construction [a-z]*RNA[-_][Ss]eq",
assay.processes.get(key, dummy).protocol_ref,
):
for p in assay.processes[key].parameter_values:
if p.name == "Library layout":
sample_info[sample_name]["paired"] = (
True if p.value == "PAIRED" else False)
elif p.name == "Library strand-specificity":
sample_info[sample_name][
"stranded"] = p.value.lower()
elif re.match(
"Nucleic acid sequencing [a-z]*RNA[-_][Ss]eq",
assay.processes.get(key, dummy).protocol_ref,
):
for p in assay.processes[key].parameter_values:
if p.name == "Instrument model":
sample_info[sample_name][
"instrument"] = ",".join(p.value)
elif (p.name == "Platform" and "instrument"
not in sample_info[sample_name]):
sample_info[sample_name][
"instrument"] = ",".join(p.value)
elif p.name == "Target read length":
sample_info[sample_name][
"read_length"] = p.value
logger.info("Samples in ISA assay:\n%s", ", ".join(sample_info))
logger.debug(sample_info)
self.sample_info = sample_info
def parse_isatab(self):
"""
parse sample info from ISA-tab table
"""
logger.info("Parsing ISA-tab...")
logger.info("Read assay file: %s", self.args.isa_assay.name)
# read assay
assay = AssayReader.from_stream("S1", "A1", self.args.isa_assay).read()
# extract relevant fields
dummy = Bunch(type="", protocol_ref="")
sample_info = {}
arc_map = {a.tail: a.head for a in assay.arcs}
for m in assay.materials.values():
if m.type == "Sample Name":
sample_name = m.name
if sample_name not in sample_info:
sample_info[sample_name] = {}
key = m.unique_name
# breakpoint()
while key in arc_map:
key = arc_map[key]
if re.match(
"Library construction [a-z]*RNA[-_]?[Ss]eq",
assay.processes.get(key, dummy).protocol_ref,
):
self._parse_isatab_library_construction(
assay, key, sample_info, sample_name)
elif re.match(
"Nucleic acid sequencing [a-z]*RNA[-_]?[Ss]eq",
assay.processes.get(key, dummy).protocol_ref,
):
self._parse_isatab_sequencing(assay, key, sample_info,
sample_name)
logger.info("Samples in ISA assay:\n%s", ", ".join(sample_info))
logger.debug(sample_info)
self.sample_info = sample_info
def test_assay_reader_minimal_assay(minimal_investigation_file,
minimal_assay_file):
"""Use ``AssayReader`` to read in minimal assay file.
Using the ``AssayReader`` instead of the ``AssayRowReader`` gives us
``Assay`` objects instead of just the row-wise nodes.
"""
# Load investigation (tested elsewhere)
investigation = InvestigationReader.from_stream(
minimal_investigation_file).read()
with pytest.warns(IsaWarning) as record:
InvestigationValidator(investigation).validate()
# Check warnings
assert 1 == len(record)
# Create new row reader and check read headers
reader = AssayReader.from_stream("S1", "A1", minimal_assay_file)
assert 5 == len(reader.header)
# Read and validate assay
assay = reader.read()
AssayValidator(investigation, investigation.studies[0],
investigation.studies[0].assays[0], assay).validate()
# Check results
assert os.path.normpath(str(assay.file)).endswith(
os.path.normpath("data/i_minimal/a_minimal.txt"))
assert 5 == len(assay.header)
assert 3 == len(assay.materials)
assert 1 == len(assay.processes)
assert 3 == len(assay.arcs)
expected = models.Material(
"Sample Name",
"S1-sample-0815-N1",
"0815-N1",
None,
(),
(),
(),
None,
[table_headers.SAMPLE_NAME],
)
assert expected == assay.materials["S1-sample-0815-N1"]
expected = models.Material(
"Raw Data File",
"S1-A1-0815-N1-DNA1-WES1_L???_???_R1.fastq.gz-COL4",
"0815-N1-DNA1-WES1_L???_???_R1.fastq.gz",
None,
(),
(),
(),
None,
[table_headers.RAW_DATA_FILE],
)
assert expected == assay.materials[
"S1-A1-0815-N1-DNA1-WES1_L???_???_R1.fastq.gz-COL4"]
expected = models.Material(
"Raw Data File",
"S1-A1-0815-N1-DNA1-WES1_L???_???_R2.fastq.gz-COL5",
"0815-N1-DNA1-WES1_L???_???_R2.fastq.gz",
None,
(),
(),
(),
None,
[table_headers.RAW_DATA_FILE],
)
assert expected == assay.materials[
"S1-A1-0815-N1-DNA1-WES1_L???_???_R2.fastq.gz-COL5"]
expected = models.Process(
"nucleic acid sequencing",
"S1-A1-0815-N1-DNA1-WES1-3",
"0815-N1-DNA1-WES1",
"Assay Name",
None,
None,
(),
(),
None,
None,
None,
[table_headers.PROTOCOL_REF, table_headers.ASSAY_NAME],
)
assert expected == assay.processes["S1-A1-0815-N1-DNA1-WES1-3"]
expected = (
models.Arc("S1-sample-0815-N1", "S1-A1-0815-N1-DNA1-WES1-3"),
models.Arc("S1-A1-0815-N1-DNA1-WES1-3",
"S1-A1-0815-N1-DNA1-WES1_L???_???_R1.fastq.gz-COL4"),
models.Arc(
"S1-A1-0815-N1-DNA1-WES1_L???_???_R1.fastq.gz-COL4",
"S1-A1-0815-N1-DNA1-WES1_L???_???_R2.fastq.gz-COL5",
),
)
assert expected == assay.arcs
def test_assay_reader_gelelect(gelelect_investigation_file,
gelelect_assay_file):
"""Use ``AssayReader`` to read in small assay file."""
with pytest.warns(IsaWarning) as record:
# Load investigation
investigation = InvestigationReader.from_stream(
gelelect_investigation_file).read()
InvestigationValidator(investigation).validate()
# Create new row reader and check read headers
reader = AssayReader.from_stream("S1", "A1", gelelect_assay_file)
assert 22 == len(reader.header)
# Read assay
assay = reader.read()
AssayValidator(investigation, investigation.studies[0],
investigation.studies[0].assays[0], assay).validate()
# Check warnings
assert 4 == len(record)
# Check results
assert os.path.normpath(str(assay.file)).endswith(
os.path.normpath(
"data/test_gelelect/a_study01_protein_expression_profiling_gel_electrophoresis.txt"
))
assert 22 == len(assay.header)
assert 9 == len(assay.materials)
assert 10 == len(assay.processes)
assert 18 == len(assay.arcs)
expected = models.Material(
"Image File",
"S1-A1-Image01.jpeg-COL19",
"Image01.jpeg",
None,
(),
(),
(),
None,
[table_headers.IMAGE_FILE],
)
assert expected == assay.materials["S1-A1-Image01.jpeg-COL19"]
expected = models.Process(
"data collection",
"S1-A1-Scan02-18",
"Scan02",
"Scan Name",
None,
None,
(),
(),
None,
None,
None,
[table_headers.PROTOCOL_REF, table_headers.SCAN_NAME],
)
assert expected == assay.processes["S1-A1-Scan02-18"]
header_electrophoresis = [
table_headers.PROTOCOL_REF,
table_headers.GEL_ELECTROPHORESIS_ASSAY_NAME,
table_headers.FIRST_DIMENSION,
table_headers.TERM_SOURCE_REF,
table_headers.TERM_ACCESSION_NUMBER,
table_headers.SECOND_DIMENSION,
table_headers.TERM_SOURCE_REF,
table_headers.TERM_ACCESSION_NUMBER,
]
expected = models.Process(
"electrophoresis",
"S1-A1-Assay01-10",
"Assay01",
"Gel Electrophoresis Assay Name",
None,
None,
(),
(),
None,
models.OntologyTermRef("", "", ""),
models.OntologyTermRef("", "", ""),
header_electrophoresis,
)
assert expected == assay.processes["S1-A1-Assay01-10"]
expected = models.Process(
"electrophoresis",
"S1-A1-electrophoresis-9-2",
"",
"Gel Electrophoresis Assay Name",
None,
None,
(),
(),
None,
models.OntologyTermRef("AssayX", None, None),
models.OntologyTermRef("AssayY", None, None),
header_electrophoresis,
)
assert expected == assay.processes["S1-A1-electrophoresis-9-2"]
def test_assay_reader_small2_assay(small2_investigation_file,
small2_assay_file):
"""Use ``AssayReader`` to read in small assay file."""
# Load investigation (tested elsewhere)
investigation = InvestigationReader.from_stream(
small2_investigation_file).read()
InvestigationValidator(investigation).validate()
# Create new row reader and check read headers
reader = AssayReader.from_stream("S1", "A1", small2_assay_file)
assert 14 == len(reader.header)
# Read assay
assay = reader.read()
AssayValidator(investigation, investigation.studies[0],
investigation.studies[0].assays[0], assay).validate()
# Check results
assert os.path.normpath(str(assay.file)).endswith(
os.path.normpath("data/i_small2/a_small2.txt"))
assert 14 == len(assay.header)
assert 25 == len(assay.materials)
assert 41 == len(assay.processes)
assert 74 == len(assay.arcs)
# Comments
expected = models.Comment(name="Replicate", value="B")
assert assay.materials["S1-A1-0815-T1-Pro1-B-115-COL5"].comments[
0] == expected
# Expected arcs
expected = (
models.Arc("S1-sample-0815-N1", "S1-A1-extraction-2-1"),
models.Arc("S1-sample-0815-T1", "S1-A1-extraction-2-2"),
models.Arc("S1-A1-extraction-2-1", "S1-A1-0815-N1-Pro1-COL3"),
models.Arc("S1-A1-extraction-2-2", "S1-A1-0815-T1-Pro1-COL3"),
models.Arc("S1-A1-0815-N1-Pro1-COL3", "S1-A1-labeling-4-1"),
models.Arc("S1-A1-0815-T1-Pro1-COL3", "S1-A1-labeling-4-2"),
models.Arc("S1-A1-0815-N1-Pro1-COL3", "S1-A1-labeling-4-3"),
models.Arc("S1-A1-0815-T1-Pro1-COL3", "S1-A1-labeling-4-4"),
models.Arc("S1-A1-0815-N1-Pro1-COL3", "S1-A1-labeling-4-5"),
models.Arc("S1-A1-0815-T1-Pro1-COL3", "S1-A1-labeling-4-6"),
models.Arc("S1-A1-0815-N1-Pro1-COL3", "S1-A1-labeling-4-7"),
models.Arc("S1-A1-0815-T1-Pro1-COL3", "S1-A1-labeling-4-8"),
models.Arc("S1-A1-0815-N1-Pro1-COL3", "S1-A1-labeling-4-9"),
models.Arc("S1-A1-0815-T1-Pro1-COL3", "S1-A1-labeling-4-10"),
models.Arc("S1-A1-0815-N1-Pro1-COL3", "S1-A1-labeling-4-11"),
models.Arc("S1-A1-0815-T1-Pro1-COL3", "S1-A1-labeling-4-12"),
models.Arc("S1-A1-labeling-4-1", "S1-A1-0815-N1-Pro1-A-114-COL5"),
models.Arc("S1-A1-labeling-4-2", "S1-A1-0815-T1-Pro1-A-115-COL5"),
models.Arc("S1-A1-labeling-4-3", "S1-A1-0815-N1-Pro1-B-114-COL5"),
models.Arc("S1-A1-labeling-4-4", "S1-A1-0815-T1-Pro1-B-115-COL5"),
models.Arc("S1-A1-labeling-4-5", "S1-A1-0815-N1-Pro1-C-114-COL5"),
models.Arc("S1-A1-labeling-4-6", "S1-A1-0815-T1-Pro1-C-115-COL5"),
models.Arc("S1-A1-labeling-4-7", "S1-A1-0815-N1-Pro1-D-114-COL5"),
models.Arc("S1-A1-labeling-4-8", "S1-A1-0815-T1-Pro1-D-115-COL5"),
models.Arc("S1-A1-labeling-4-9", "S1-A1-0815-N1-Pro1-E-114-COL5"),
models.Arc("S1-A1-labeling-4-10", "S1-A1-0815-T1-Pro1-E-115-COL5"),
models.Arc("S1-A1-labeling-4-11", "S1-A1-0815-N1-Pro1-F-114-COL5"),
models.Arc("S1-A1-labeling-4-12", "S1-A1-0815-T1-Pro1-F-115-COL5"),
models.Arc("S1-A1-0815-N1-Pro1-A-114-COL5",
"S1-A1-chromatography-8-1"),
models.Arc("S1-A1-0815-T1-Pro1-A-115-COL5",
"S1-A1-chromatography-8-2"),
models.Arc("S1-A1-0815-N1-Pro1-B-114-COL5",
"S1-A1-chromatography-8-3"),
models.Arc("S1-A1-0815-T1-Pro1-B-115-COL5",
"S1-A1-chromatography-8-4"),
models.Arc("S1-A1-0815-N1-Pro1-C-114-COL5",
"S1-A1-chromatography-8-5"),
models.Arc("S1-A1-0815-T1-Pro1-C-115-COL5",
"S1-A1-chromatography-8-6"),
models.Arc("S1-A1-0815-N1-Pro1-D-114-COL5",
"S1-A1-chromatography-8-7"),
models.Arc("S1-A1-0815-T1-Pro1-D-115-COL5",
"S1-A1-chromatography-8-8"),
models.Arc("S1-A1-0815-N1-Pro1-E-114-COL5",
"S1-A1-chromatography-8-9"),
models.Arc("S1-A1-0815-T1-Pro1-E-115-COL5",
"S1-A1-chromatography-8-10"),
models.Arc("S1-A1-0815-N1-Pro1-F-114-COL5",
"S1-A1-chromatography-8-11"),
models.Arc("S1-A1-0815-T1-Pro1-F-115-COL5",
"S1-A1-chromatography-8-12"),
models.Arc("S1-A1-chromatography-8-1", "S1-A1-poolA-10"),
models.Arc("S1-A1-chromatography-8-2", "S1-A1-poolA-10"),
models.Arc("S1-A1-chromatography-8-3", "S1-A1-mass spectrometry-9-3"),
models.Arc("S1-A1-chromatography-8-4", "S1-A1-mass spectrometry-9-4"),
models.Arc("S1-A1-chromatography-8-5", "S1-A1-poolC-10"),
models.Arc("S1-A1-chromatography-8-6", "S1-A1-poolC-10"),
models.Arc("S1-A1-chromatography-8-7", "S1-A1-mass spectrometry-9-7"),
models.Arc("S1-A1-chromatography-8-8", "S1-A1-mass spectrometry-9-8"),
models.Arc("S1-A1-chromatography-8-9", "S1-A1-poolE-10"),
models.Arc("S1-A1-chromatography-8-10", "S1-A1-poolE-10"),
models.Arc("S1-A1-chromatography-8-11", "S1-A1-poolF-10"),
models.Arc("S1-A1-chromatography-8-12", "S1-A1-poolF-10"),
models.Arc("S1-A1-poolA-10", "S1-A1-poolA.raw-COL11"),
models.Arc("S1-A1-mass spectrometry-9-3", "S1-A1-poolB.raw-COL11"),
models.Arc("S1-A1-mass spectrometry-9-4", "S1-A1-poolB.raw-COL11"),
models.Arc("S1-A1-poolC-10",
"S1-A1-Empty Raw Spectral Data File-11-5"),
models.Arc("S1-A1-mass spectrometry-9-7",
"S1-A1-Empty Raw Spectral Data File-11-7"),
models.Arc("S1-A1-mass spectrometry-9-8",
"S1-A1-Empty Raw Spectral Data File-11-8"),
models.Arc("S1-A1-poolE-10", "S1-A1-poolE.raw-COL11"),
models.Arc("S1-A1-poolF-10",
"S1-A1-Empty Raw Spectral Data File-11-11"),
models.Arc("S1-A1-poolA.raw-COL11", "S1-A1-data transformation-12-1"),
models.Arc("S1-A1-poolB.raw-COL11", "S1-A1-data transformation-12-3"),
models.Arc("S1-A1-Empty Raw Spectral Data File-11-5",
"S1-A1-data transformation-12-5"),
models.Arc("S1-A1-Empty Raw Spectral Data File-11-7",
"S1-A1-data transformation-12-7"),
models.Arc("S1-A1-Empty Raw Spectral Data File-11-8",
"S1-A1-data transformation-12-8"),
models.Arc("S1-A1-poolE.raw-COL11", "S1-A1-data transformation-12-9"),
models.Arc("S1-A1-Empty Raw Spectral Data File-11-11",
"S1-A1-data analysis-13"),
models.Arc("S1-A1-data transformation-12-1",
"S1-A1-results.csv-COL14"),
models.Arc("S1-A1-data transformation-12-3",
"S1-A1-results.csv-COL14"),
models.Arc("S1-A1-data transformation-12-5",
"S1-A1-results.csv-COL14"),
models.Arc("S1-A1-data transformation-12-7",
"S1-A1-results.csv-COL14"),
models.Arc("S1-A1-data transformation-12-8",
"S1-A1-results.csv-COL14"),
models.Arc("S1-A1-data transformation-12-9",
"S1-A1-Empty Derived Data File-14-9"),
models.Arc("S1-A1-data analysis-13", "S1-A1-results.csv-COL14"),
)
assert sorted(expected) == sorted(assay.arcs)
def test_assay_reader_small_assay(small_investigation_file, small_assay_file):
"""Use ``AssayReader`` to read in small assay file."""
# Load investigation (tested elsewhere)
investigation = InvestigationReader.from_stream(
small_investigation_file).read()
with pytest.warns(IsaWarning) as record:
InvestigationValidator(investigation).validate()
# Check warnings
assert 1 == len(record)
# Create new row reader and check read headers
reader = AssayReader.from_stream("S1", "A1", small_assay_file)
assert 9 == len(reader.header)
# Read assay
with pytest.warns(IsaWarning) as record:
assay = reader.read()
AssayValidator(investigation, investigation.studies[0],
investigation.studies[0].assays[0], assay).validate()
# Check warnings
assert 1 == len(record)
# Check results
assert os.path.normpath(str(assay.file)).endswith(
os.path.normpath("data/i_small/a_small.txt"))
assert 9 == len(assay.header)
assert 9 == len(assay.materials)
assert 5 == len(assay.processes)
assert 13 == len(assay.arcs)
expected = models.Material(
"Sample Name",
"S1-sample-0815-N1",
"0815-N1",
None,
(),
(),
(),
None,
[table_headers.SAMPLE_NAME],
)
assert expected == assay.materials["S1-sample-0815-N1"]
expected = models.Material(
"Sample Name",
"S1-sample-0815-T1",
"0815-T1",
None,
(),
(),
(),
None,
[table_headers.SAMPLE_NAME],
)
assert expected == assay.materials["S1-sample-0815-T1"]
expected = models.Material(
"Raw Data File",
"S1-A1-0815-N1-DNA1-WES1_L???_???_R1.fastq.gz-COL6",
"0815-N1-DNA1-WES1_L???_???_R1.fastq.gz",
None,
(),
(),
(),
None,
[table_headers.RAW_DATA_FILE],
)
assert expected == assay.materials[
"S1-A1-0815-N1-DNA1-WES1_L???_???_R1.fastq.gz-COL6"]
expected = models.Material(
"Raw Data File",
"S1-A1-0815-N1-DNA1-WES1_L???_???_R2.fastq.gz-COL7",
"0815-N1-DNA1-WES1_L???_???_R2.fastq.gz",
None,
(),
(),
(),
None,
[table_headers.RAW_DATA_FILE],
)
assert expected == assay.materials[
"S1-A1-0815-N1-DNA1-WES1_L???_???_R2.fastq.gz-COL7"]
expected = models.Material(
"Raw Data File",
"S1-A1-0815-T1-DNA1-WES1_L???_???_R1.fastq.gz-COL6",
"0815-T1-DNA1-WES1_L???_???_R1.fastq.gz",
None,
(),
(),
(),
None,
[table_headers.RAW_DATA_FILE],
)
assert expected == assay.materials[
"S1-A1-0815-T1-DNA1-WES1_L???_???_R1.fastq.gz-COL6"]
expected = models.Material(
"Raw Data File",
"S1-A1-0815-T1-DNA1-WES1_L???_???_R2.fastq.gz-COL7",
"0815-T1-DNA1-WES1_L???_???_R2.fastq.gz",
None,
(),
(),
(),
None,
[table_headers.RAW_DATA_FILE],
)
assert expected == assay.materials[
"S1-A1-0815-T1-DNA1-WES1_L???_???_R2.fastq.gz-COL7"]
expected = models.Material(
"Derived Data File",
"S1-A1-0815-somatic.vcf.gz-COL9",
"0815-somatic.vcf.gz",
None,
(),
(),
(),
None,
[table_headers.DERIVED_DATA_FILE],
)
assert expected == assay.materials["S1-A1-0815-somatic.vcf.gz-COL9"]
expected = models.Process(
"library preparation",
"S1-A1-library preparation-2-1",
None,
None,
None,
None,
(),
(),
None,
None,
None,
[table_headers.PROTOCOL_REF],
)
assert expected == assay.processes["S1-A1-library preparation-2-1"]
expected = models.Process(
"library preparation",
"S1-A1-library preparation-2-2",
None,
None,
None,
None,
(),
(),
None,
None,
None,
[table_headers.PROTOCOL_REF],
)
assert expected == assay.processes["S1-A1-library preparation-2-2"]
expected = models.Process(
"nucleic acid sequencing",
"S1-A1-0815-N1-DNA1-WES1-5",
"0815-N1-DNA1-WES1",
"Assay Name",
None,
None,
(),
(),
None,
None,
None,
[table_headers.PROTOCOL_REF, table_headers.ASSAY_NAME],
)
assert expected == assay.processes["S1-A1-0815-N1-DNA1-WES1-5"]
expected = models.Process(
"nucleic acid sequencing",
"S1-A1-0815-T1-DNA1-WES1-5",
"0815-T1-DNA1-WES1",
"Assay Name",
None,
None,
(),
(),
None,
None,
None,
[table_headers.PROTOCOL_REF, table_headers.ASSAY_NAME],
)
assert expected == assay.processes["S1-A1-0815-T1-DNA1-WES1-5"]
expected = (
models.Arc("S1-sample-0815-N1", "S1-A1-library preparation-2-1"),
models.Arc("S1-A1-library preparation-2-1", "S1-A1-0815-N1-DNA1-COL3"),
models.Arc("S1-A1-0815-N1-DNA1-COL3", "S1-A1-0815-N1-DNA1-WES1-5"),
models.Arc("S1-A1-0815-N1-DNA1-WES1-5",
"S1-A1-0815-N1-DNA1-WES1_L???_???_R1.fastq.gz-COL6"),
models.Arc(
"S1-A1-0815-N1-DNA1-WES1_L???_???_R1.fastq.gz-COL6",
"S1-A1-0815-N1-DNA1-WES1_L???_???_R2.fastq.gz-COL7",
),
models.Arc("S1-A1-0815-N1-DNA1-WES1_L???_???_R2.fastq.gz-COL7",
"S1-A1-somatic variant calling-1-8"),
models.Arc("S1-A1-somatic variant calling-1-8",
"S1-A1-0815-somatic.vcf.gz-COL9"),
models.Arc("S1-sample-0815-T1", "S1-A1-library preparation-2-2"),
models.Arc("S1-A1-library preparation-2-2", "S1-A1-0815-T1-DNA1-COL3"),
models.Arc("S1-A1-0815-T1-DNA1-COL3", "S1-A1-0815-T1-DNA1-WES1-5"),
models.Arc("S1-A1-0815-T1-DNA1-WES1-5",
"S1-A1-0815-T1-DNA1-WES1_L???_???_R1.fastq.gz-COL6"),
models.Arc(
"S1-A1-0815-T1-DNA1-WES1_L???_???_R1.fastq.gz-COL6",
"S1-A1-0815-T1-DNA1-WES1_L???_???_R2.fastq.gz-COL7",
),
models.Arc("S1-A1-0815-T1-DNA1-WES1_L???_???_R2.fastq.gz-COL7",
"S1-A1-somatic variant calling-1-8"),
)
assert expected == assay.arcs
def test_header_exception_unknown_header(assay_file_exception_unknown_header):
with pytest.raises(ParseIsatabException) as excinfo:
AssayReader.from_stream("S1", "A1",
assay_file_exception_unknown_header)
msg = 'Header "Test Name" unknown, processing unclear'
assert msg == str(excinfo.value)