def test_sra_metadata_is_harmonized(self):
metadata = SraSurveyor.gather_all_metadata("SRR3098582")
sample = Sample()
SraSurveyor._apply_harmonized_metadata_to_sample(sample, metadata)
self.assertEqual(sample.treatment, "biliatresone")
self.assertEqual(sample.subject, "liver")
self.assertEqual(sample.specimen_part, "liver")
def test_survey_unmated_reads(self, mock_send_job):
"""Test an experiment with unmated reads.
Also make sure the file report endpoint's properties are recorded.
"""
survey_job = SurveyJob(source_type="SRA")
survey_job.save()
key_value_pair = SurveyJobKeyValue(
survey_job=survey_job, key="experiment_accession_code", value="SRP048683"
)
key_value_pair.save()
sra_surveyor = SraSurveyor(survey_job)
experiment, samples = sra_surveyor.discover_experiment_and_samples()
self.assertEqual(experiment.accession_code, "SRP048683")
self.assertEqual(len(samples), 12)
expected_file_names = set()
# Just check one file for one sample's expected file size/md5
for sample in samples:
if sample.accession_code == "SRR1603661":
for original_file in sample.original_files.all():
expected_file_names.add(original_file.source_filename)
if original_file.source_filename == "SRR1603661_1.fastq.gz":
self.assertEqual(
original_file.expected_md5, "502a9a482bfa5aa75865ccc0105ad13c"
)
self.assertEqual(original_file.expected_size_in_bytes, 6751980628)
self.assertEqual({"SRR1603661_1.fastq.gz", "SRR1603661_2.fastq.gz"}, expected_file_names)
def test_get_next_accession(self):
self.assertEqual(SraSurveyor.get_next_accession("DRR123456"),
"DRR123457")
self.assertEqual(SraSurveyor.get_next_accession("DRR1234567"),
"DRR1234568")
self.assertEqual(SraSurveyor.get_next_accession("DRR12345678"),
"DRR12345679")
self.assertEqual(SraSurveyor.get_next_accession("DRR123456789"),
"DRR123456790")
def test_survey(self):
"""A Simple test of the SRA surveyor.
"""
sra_surveyor = SraSurveyor(self.survey_job)
sra_surveyor.discover_experiment_and_samples()
samples = Sample.objects.all()
# We are expecting this to discover 1 sample.
self.assertEqual(samples.count(), 1)
# Confirm the sample's protocol_info
experiment = Experiment.objects.all().first()
self.assertEqual(samples.first().protocol_info[0]["Description"],
experiment.protocol_description)
def test_batch_created(self, mock_get):
mock_get.side_effect = mocked_requests_get
# Use same run accession for the start and end of the range to
# achieve a length of 1
survey_job = SurveyJob(source_type="SRA")
survey_job.save()
key_value_pair = SurveyJobKeyValue(survey_job=survey_job,
key="start_accession",
value=RUN_ACCESSION)
key_value_pair.save()
key_value_pair = SurveyJobKeyValue(survey_job=survey_job,
key="end_accession",
value=RUN_ACCESSION)
key_value_pair.save()
surveyor = SraSurveyor(survey_job)
self.assertTrue(surveyor.discover_batches())
# With only a single run accession there should only be a
# single batch.
self.assertEqual(len(surveyor.batches), 1)
batch = surveyor.batches[0]
self.assertEqual(batch.survey_job.id, survey_job.id)
self.assertEqual(batch.source_type, "SRA")
self.assertEqual(batch.pipeline_required, "SALMON")
self.assertEqual(batch.platform_accession_code, "IlluminaHiSeq2000")
self.assertEqual(batch.experiment_accession_code, "DRX001563")
self.assertEqual(batch.experiment_title,
("Illumina HiSeq 2000 sequencing; "
"Exp_Gg_HH16_1_embryo_mRNAseq"))
self.assertEqual(batch.status, "NEW")
self.assertEqual(batch.release_date, "2013-07-19")
self.assertEqual(batch.last_uploaded_date, "2017-08-11")
self.assertEqual(batch.organism_id, 9031)
self.assertEqual(batch.organism_name, "GALLUS GALLUS")
file = batch.files[0]
self.assertEqual(file.size_in_bytes, -1)
self.assertEqual(
file.download_url,
"ftp://ftp.sra.ebi.ac.uk/vol1/fastq/DRR002/DRR002116/DRR002116.fastq.gz"
) # noqa
self.assertEqual(file.raw_format, "fastq.gz")
self.assertEqual(file.processed_format, "tar.gz")
self.assertEqual(file.name, "DRR002116.fastq.gz")
self.assertEqual(file.internal_location, "IlluminaHiSeq2000/SALMON")
def test_arrayexpress_alternate_accession(self):
""" Make sure that ENA experiments correctly detect their ArrayExpress alternate accession
"""
survey_job = SurveyJob(source_type="SRA")
survey_job.save()
key_value_pair = SurveyJobKeyValue(
survey_job=survey_job, key="experiment_accession_code", value="ERP108370"
)
key_value_pair.save()
sra_surveyor = SraSurveyor(survey_job)
experiment, _ = sra_surveyor.discover_experiment_and_samples()
self.assertEqual(experiment.accession_code, "ERP108370")
self.assertEqual(experiment.alternate_accession_code, "E-MTAB-6681")
def test_sra_metadata_is_harmonized(self):
metadata = SraSurveyor.gather_all_metadata("SRR3098582")
sample = Sample()
SraSurveyor._apply_harmonized_metadata_to_sample(sample, metadata)
self.assertEqual(sample.treatment, "biliatresone")
self.assertEqual(sample.subject, "liver")
self.assertEqual(sample.specimen_part, "liver")
experiment = Experiment()
SraSurveyor._apply_metadata_to_experiment(experiment, metadata)
self.assertEqual(
experiment.title,
"Transcriptional profiling through RNA-seq of zebrafish larval"
" liver after exposure to biliatresone, a biliary toxin.",
)
self.assertEqual(experiment.source_first_published, datetime.date(2017, 9, 25))
self.assertEqual(experiment.source_last_modified, datetime.date(2017, 9, 25))
def _get_surveyor_for_source(survey_job: SurveyJob):
"""Factory method for ExternalSourceSurveyors."""
if survey_job.source_type == "ARRAY_EXPRESS":
return ArrayExpressSurveyor(survey_job)
if survey_job.source_type == "SRA":
return SraSurveyor(survey_job)
if survey_job.source_type == "TRANSCRIPTOME_INDEX":
return TranscriptomeIndexSurveyor(survey_job)
else:
raise SourceNotSupportedError("Source " + survey_job.source_type +
" is not supported.")
def test_discover_batches(self, mock_generate_batch):
survey_job = SurveyJob(source_type="SRA")
survey_job.save()
key_value_pair = SurveyJobKeyValue(survey_job=survey_job,
key="start_accession",
value="DRR012345")
key_value_pair.save()
key_value_pair = SurveyJobKeyValue(survey_job=survey_job,
key="end_accession",
value="DRR012348")
key_value_pair.save()
sra_surveyor = SraSurveyor(survey_job)
sra_surveyor.discover_batches()
mock_generate_batch.assert_has_calls([
call("DRR012345"),
call("DRR012346"),
call("DRR012347"),
call("DRR012348")
])
def test_srp_survey(self, mock_send_job):
"""A slightly harder test of the SRA surveyor.
"""
survey_job = SurveyJob(source_type="SRA")
survey_job.save()
key_value_pair = SurveyJobKeyValue(
survey_job=survey_job, key="experiment_accession_code", value="SRP068364"
)
key_value_pair.save()
sra_surveyor = SraSurveyor(survey_job)
experiment, samples = sra_surveyor.discover_experiment_and_samples()
self.assertEqual(experiment.accession_code, "SRP068364")
self.assertEqual(experiment.alternate_accession_code, "GSE76780")
self.assertEqual(len(samples), 4)
survey_job = SurveyJob(source_type="SRA")
survey_job.save()
key_value_pair = SurveyJobKeyValue(
survey_job=survey_job, key="experiment_accession_code", value="SRP111553"
)
key_value_pair.save()
sra_surveyor = SraSurveyor(survey_job)
experiment, samples = sra_surveyor.discover_experiment_and_samples()
self.assertEqual(experiment.accession_code, "SRP111553")
self.assertEqual(experiment.alternate_accession_code, "GSE101204")
self.assertEqual(len(samples), 16) # 8 samples with 2 runs each
survey_job = SurveyJob(source_type="SRA")
survey_job.save()
key_value_pair = SurveyJobKeyValue(
survey_job=survey_job, key="experiment_accession_code", value="DRP003977"
)
key_value_pair.save()
sra_surveyor = SraSurveyor(survey_job)
experiment, samples = sra_surveyor.discover_experiment_and_samples()
self.assertEqual(experiment.accession_code, "DRP003977")
self.assertEqual(experiment.alternate_accession_code, None)
self.assertEqual(len(samples), 9)
def test_sra_harmony(self):
"""
Tests a specific harmonization from SRA
"""
metadata = SraSurveyor.gather_all_metadata("SRR1533126")
harmonized_sample = self._harmonizer.harmonize_sample(metadata)
title = "Phosphaturic mesenchymal tumour (PMT) case 2 of NTUH"
self.assertEqual(title, harmonized_sample["title"])
self.assertTrue("sex" in harmonized_sample.keys())
self.assertEqual("female", harmonized_sample["sex"])
self.assertTrue("age" in harmonized_sample.keys())
self.assertEqual(57.0, harmonized_sample["age"])
self.assertTrue("specimen_part" in harmonized_sample.keys())
self.assertTrue("disease" in harmonized_sample.keys())
def test_sra_lots(self):
"""
Smoke tests a few SRA types
"""
# These can be built via
# https://www.ncbi.nlm.nih.gov/sra
# Searching for
# (human) NOT cluster_dbgap[PROP]
# And then Sent To -> File -> Accession List
lots = [
"ERR188021",
"ERR188022",
"ERR205021",
"ERR205022",
"ERR205023",
"SRR000001", # Soft fail, bad platform
"ERR1737666",
"ERR030891",
"ERR030892",
"SRR1542948",
"SRR1553477",
"SRR1542330",
"SRR1538698",
"SRR1538760",
"SRR1538866",
"SRR1539218",
"SRR1797277",
"SRR1533126",
]
for accession in lots:
try:
metadata = SraSurveyor.gather_all_metadata(accession)
harmonized = harmonize_all_samples([metadata])
self.assertIsNotNone(harmonized)
except UnsupportedDataTypeError:
continue
def test_queue_downloader_jobs_for_original_files(self, mock_send_task):
"""Make sure that queue_downloader_jobs queues all expected Downloader
jobs for a given experiment.
"""
# First, create an experiment with two samples associated with it
# and create two original files for each of those samples.
experiment_object = Experiment()
experiment_object.accession_code = "Experiment1"
experiment_object.save()
sample_object_1 = Sample()
sample_object_1.accession_code = "Sample1"
sample_object_1.platform_accession_code = "Illumina Genome Analyzer"
sample_object_1.platform_accession_name = "Illumina Genome Analyzer"
sample_object_1.technology = "RNA-SEQ"
sample_object_1.manufacturer = "ILLUMINA"
sample_object_1.source_database = "SRA"
sample_object_1.save()
sample_object_2 = Sample()
sample_object_2.accession_code = "Sample2"
sample_object_2.platform_accession_code = "Illumina Genome Analyzer"
sample_object_2.platform_accession_name = "Illumina Genome Analyzer"
sample_object_2.technology = "RNA-SEQ"
sample_object_2.manufacturer = "ILLUMINA"
sample_object_2.source_database = "SRA"
sample_object_2.save()
association = ExperimentSampleAssociation()
association.experiment = experiment_object
association.sample = sample_object_1
association.save()
association = ExperimentSampleAssociation()
association.experiment = experiment_object
association.sample = sample_object_2
association.save()
sample_1_original_files = []
sample_2_original_files = []
original_file = OriginalFile()
original_file.source_url = "first_url"
original_file.source_filename = "first_filename"
original_file.is_downloaded = False
original_file.has_raw = True
original_file.save()
sample_1_original_files.append(original_file)
original_file_sample_association = OriginalFileSampleAssociation()
original_file_sample_association.original_file = original_file
original_file_sample_association.sample = sample_object_1
original_file_sample_association.save()
original_file = OriginalFile()
original_file.source_url = "second_url"
original_file.source_filename = "second_filename"
original_file.is_downloaded = False
original_file.has_raw = True
original_file.save()
sample_2_original_files.append(original_file)
original_file_sample_association = OriginalFileSampleAssociation()
original_file_sample_association.original_file = original_file
original_file_sample_association.sample = sample_object_1
original_file_sample_association.save()
original_file = OriginalFile()
original_file.source_url = "third_url"
original_file.source_filename = "third_filename"
original_file.is_downloaded = False
original_file.has_raw = True
original_file.save()
sample_2_original_files.append(original_file)
original_file_sample_association = OriginalFileSampleAssociation()
original_file_sample_association.original_file = original_file
original_file_sample_association.sample = sample_object_2
original_file_sample_association.save()
original_file = OriginalFile()
original_file.source_url = "fourth_url"
original_file.source_filename = "fourth_filename"
original_file.is_downloaded = False
original_file.has_raw = True
original_file.save()
sample_2_original_files.append(original_file)
original_file_sample_association = OriginalFileSampleAssociation()
original_file_sample_association.original_file = original_file
original_file_sample_association.sample = sample_object_2
original_file_sample_association.save()
survey_job = SurveyJob(source_type="SRA")
survey_job.save()
surveyor = SraSurveyor(survey_job)
surveyor.queue_downloader_job_for_original_files(
sample_1_original_files, experiment_object.accession_code
)
surveyor.queue_downloader_job_for_original_files(
sample_2_original_files, experiment_object.accession_code
)
self.assertEqual(DownloaderJob.objects.all().count(), 2)
def test_no_repeat_jobs(self):
"""Make sure that queue_downloader_jobs queues all expected Downloader
jobs for a given experiment.
"""
# First, create an experiment with two samples associated with it
# and create two original files for each of those samples.
experiment_object = Experiment()
experiment_object.accession_code = "Experiment1"
experiment_object.save()
sample_object = Sample()
sample_object.accession_code = "Sample1"
sample_object.platform_accession_code = "Illumina Genome Analyzer"
sample_object.platform_accession_name = "Illumina Genome Analyzer"
sample_object.technology = "RNA-SEQ"
sample_object.manufacturer = "ILLUMINA"
sample_object.source_database = "SRA"
sample_object.save()
original_file_1 = OriginalFile()
original_file_1.source_url = "first_url"
original_file_1.source_filename = "first_filename"
original_file_1.is_downloaded = False
original_file_1.has_raw = True
original_file_1.save()
original_file_sample_association = OriginalFileSampleAssociation()
original_file_sample_association.original_file = original_file_1
original_file_sample_association.sample = sample_object
original_file_sample_association.save()
original_file_2 = OriginalFile()
original_file_2.source_url = "second_url"
original_file_2.source_filename = "second_filename"
original_file_2.is_downloaded = False
original_file_2.has_raw = True
original_file_2.save()
original_file_sample_association = OriginalFileSampleAssociation()
original_file_sample_association.original_file = original_file_2
original_file_sample_association.sample = sample_object
original_file_sample_association.save()
dlj = DownloaderJob()
dlj.save()
DownloaderJobOriginalFileAssociation(
downloader_job=dlj, original_file=original_file_1
).save()
DownloaderJobOriginalFileAssociation(
downloader_job=dlj, original_file=original_file_2
).save()
survey_job = SurveyJob(source_type="SRA")
survey_job.save()
surveyor = SraSurveyor(survey_job)
surveyor.queue_downloader_job_for_original_files(
[original_file_1, original_file_2], experiment_object.accession_code
)
# We made one DownloaderJob in this test, so
# queue_downloader_job_for_original_files didn't have anything
# to do, so there should still be only one:
self.assertEqual(1, DownloaderJob.objects.all().count())
def handle(self, *args, **options):
"""Refreshes the metadata for all experiments, or experiments from a specific database
"""
possible_source_databases = ["ARRAY_EXPRESS", "GEO", "SRA"]
if options.get("source_database", None) is None:
experiments = Experiment.objects.all()
elif options["source_database"] in possible_source_databases:
source_database = options["source_database"]
experiments = Experiment.objects.filter(
source_database=source_database)
else:
logger.error('Invalid source database "{}"'.format(
options["source_database"]) +
"\nPossible source databases: {}".format(", ".join(
possible_source_databases)))
sys.exit(1)
paginator = PerformantPaginator(experiments, PAGE_SIZE)
page = paginator.page()
while True:
for experiment in page.object_list:
logger.debug("Refreshing metadata for an experiment.",
experiment=experiment.accession_code)
try:
if experiment.source_database == "SRA":
metadata = SraSurveyor.gather_all_metadata(
experiment.samples.first().accession_code)
SraSurveyor._apply_metadata_to_experiment(
experiment, metadata)
elif experiment.source_database == "GEO":
gse = GEOparse.get_GEO(
experiment.accession_code,
destdir="/tmp/management",
silent=True,
)
GeoSurveyor._apply_metadata_to_experiment(
experiment, gse)
elif experiment.source_database == "ARRAY_EXPRESS":
request_url = EXPERIMENTS_URL + experiment.accession_code
experiment_request = utils.requests_retry_session(
).get(request_url, timeout=60)
try:
parsed_json = experiment_request.json(
)["experiments"]["experiment"][0]
except KeyError:
logger.error(
"Remote experiment has no Experiment data!",
experiment_accession_code=experiment.
accession_code,
survey_job=self.survey_job.id,
)
continue
ArrayExpressSurveyor._apply_metadata_to_experiment(
experiment, parsed_json)
experiment.save()
# If there are any errors, just continue. It's likely that it's
# just a problem with this experiment.
except Exception:
logger.exception(
"exception caught while updating metadata for {}".
format(experiment.accession_code))
if not page.has_next():
break
else:
page = paginator.page(page.next_page_number())
# 2000 samples queued up every five minutes should be fast
# enough and also not thrash the DB.
time.sleep(60 * 5)
def handle(self, *args, **options):
"""Refreshes the metadata for all samples, or samples from a specific database
"""
possible_source_databases = ["ARRAY_EXPRESS", "GEO", "SRA"]
if options.get("source_database", None) is None:
samples = Sample.objects.all()
elif options["source_database"] in possible_source_databases:
source_database = options["source_database"]
samples = Sample.objects.filter(source_database=source_database)
else:
logger.error('Invalid source database "{}"'.format(
options["source_database"]) +
"\nPossible source databases: {}".format(", ".join(
possible_source_databases)))
sys.exit(1)
paginator = PerformantPaginator(samples, PAGE_SIZE)
page = paginator.page()
while True:
for sample in samples:
logger.debug("Refreshing metadata for a sample.",
sample=sample.accession_code)
if sample.source_database == "SRA":
metadata = SraSurveyor.gather_all_metadata(
sample.accession_code)
SraSurveyor._apply_harmonized_metadata_to_sample(
sample, metadata)
elif sample.source_database == "GEO":
gse = GEOparse.get_GEO(
sample.experiments.first().accession_code,
destdir="/tmp/management",
how="brief",
silent=True,
)
preprocessed_samples = harmony.preprocess_geo(
gse.gsms.items())
harmonized_samples = harmony.harmonize(
preprocessed_samples)
GeoSurveyor._apply_harmonized_metadata_to_sample(
sample, harmonized_samples[sample.title])
elif sample.source_database == "ARRAY_EXPRESS":
SDRF_URL_TEMPLATE = (
"https://www.ebi.ac.uk/arrayexpress/files/{code}/{code}.sdrf.txt"
)
sdrf_url = SDRF_URL_TEMPLATE.format(
code=sample.experiments.first().accession_code)
sdrf_samples = harmony.parse_sdrf(sdrf_url)
harmonized_samples = harmony.harmonize(sdrf_samples)
ArrayExpressSurveyor._apply_harmonized_metadata_to_sample(
sample, harmonized_samples[sample.title])
sample.save()
if not page.has_next():
break
else:
page = paginator.page(page.next_page_number())
# 2000 samples queued up every five minutes should be fast
# enough and also not thrash the DB.
time.sleep(60 * 5)
def test_metadata_is_gathered_correctly(self):
metadata = SraSurveyor.gather_all_metadata("DRR002116")
self.assertEqual(metadata["broker_name"], "DDBJ")
self.assertEqual(metadata["center_name"], "RIKEN_CDB")
self.assertEqual(metadata["ena-base-count"], "158881910957")
self.assertEqual(metadata["ena-spot-count"], "1371813555")
self.assertEqual(metadata["experiment_accession"], "DRX001563")
self.assertEqual(
metadata["experiment_design_description"],
("Experiment for mRNAseq of chicken at stage " "HH16 (biological replicate 1)"),
)
self.assertEqual(
metadata["experiment_title"],
("Illumina HiSeq 2000 sequencing; " "Exp_Gg_HH16_1_embryo_mRNAseq"),
)
self.assertEqual(
metadata["lab_name"],
(
"Group for Morphological Evolution, Center for Developmental "
"Biology, Kobe Institute, RIKEN"
),
)
self.assertEqual(metadata["library_layout"], "SINGLE")
self.assertEqual(metadata["library_name"], "Gg_HH16_1_embryo_mRNAseq")
self.assertEqual(metadata["library_selection"], "RANDOM")
self.assertEqual(metadata["library_source"], "TRANSCRIPTOMIC")
self.assertEqual(metadata["library_strategy"], "RNA-Seq")
self.assertEqual(metadata["organism_id"], "9031")
self.assertEqual(metadata["organism_name"], "GALLUS GALLUS")
self.assertEqual(metadata["platform_instrument_model"], "Illumina HiSeq 2000")
self.assertEqual(metadata["read_spec_0_base_coord"], "1")
self.assertEqual(metadata["read_spec_0_class"], "Application Read")
self.assertEqual(metadata["read_spec_0_index"], "0")
self.assertEqual(metadata["read_spec_0_type"], "Forward")
self.assertEqual(metadata["run_accession"], "DRR002116")
self.assertEqual(metadata["run_center"], "RIKEN_CDB")
self.assertEqual(metadata["run_date"], "2011-09-01T00:00:00+09:00")
self.assertEqual(metadata["run_ena_base_count"], "3256836000")
self.assertEqual(metadata["run_ena_first_public"], "2013-07-19")
self.assertEqual(metadata["run_ena_last_update"], "2017-08-11")
self.assertEqual(metadata["run_ena_spot_count"], "32568360")
self.assertEqual(metadata["sample_accession"], "DRS001521")
self.assertEqual(metadata["sample_center_name"], "BioSample")
self.assertEqual(metadata["sample_ena_base_count"], "3256836000")
self.assertEqual(metadata["sample_ena_first_public"], "2013-07-20")
self.assertEqual(metadata["sample_ena_last_update"], "2015-08-24")
self.assertEqual(metadata["sample_ena_spot_count"], "32568360")
self.assertEqual(
metadata["sample_sample_comment"],
("mRNAseq of chicken at stage HH16 (biological " "replicate 1)"),
)
self.assertEqual(metadata["sample_sample_name"], "DRS001521")
self.assertEqual(metadata["sample_title"], "Gg_HH16_1_embryo_mRNAseq")
self.assertEqual(metadata["spot_length"], "100")
self.assertEqual(metadata["study_ena_first_public"], "2013-07-19")
self.assertEqual(metadata["study_ena_last_update"], "2015-06-22")
self.assertEqual(metadata["study_accession"], "DRP000595")
self.assertEqual(metadata["submission_accession"], "DRA000567")
self.assertEqual(
metadata["submission_comment"],
(
"Time course gene expression profiles of turtle "
"(Pelodiscus sinensis) and chicken (Gallus gallus) "
"embryos were examined. Whole transcriptome of turtle "
"was also determined by uding stranded sequencing "
"methods."
),
)
self.assertEqual(metadata["submission_title"], "Submitted by RIKEN_CDB on 19-JUL-2013")
ncbi_url = SraSurveyor._build_ncbi_file_url(metadata["run_accession"])
self.assertTrue(
ncbi_url
in [
"[email protected]:/sra/sra-instant/reads/ByRun/sra/DRR/DRR002/DRR002116/DRR002116.sra",
"[email protected]:/sra/sra-instant/reads/ByRun/sra/DRR/DRR002/DRR002116/DRR002116.sra",
"[email protected]:data/sracloud/traces/dra0/DRR/000002/DRR002116",
]
)
