def test_download_file_swapper(self, mock_send_job):
mock_send_job.return_value = None
dlj = DownloaderJob()
dlj.accession_code = "DRR002116"
dlj.save()
og = OriginalFile()
og.source_filename = "DRR002116.sra"
og.source_url = "[email protected]:/sra/sra-instant/reads/ByRun/sra/DRR/DRR002/DRR002116/DRR002116.sra"
og.is_archive = True
og.save()
sample = Sample()
sample.accession_code = 'DRR002116'
sample.save()
assoc = OriginalFileSampleAssociation()
assoc.sample = sample
assoc.original_file = og
assoc.save()
assoc = DownloaderJobOriginalFileAssociation()
assoc.downloader_job = dlj
assoc.original_file = og
assoc.save()
result = sra._download_file(og.source_url,
dlj,
"/tmp",
force_ftp=False)
self.assertTrue(result)
def test_salmontools_with_bad_processor(self):
"""Test salmontools with a bad processor key."""
test_dir = '/home/user/data_store/salmontools/'
job_context = {
'job_id': 123,
'job': ProcessorJob.objects.create(),
'pipeline': Pipeline(name="Salmon"),
'input_file_path': test_dir + 'double_input/reads_1.fastq',
'input_file_path_2': test_dir + 'double_input/reads_2.fastq',
'salmontools_directory': test_dir + 'double_salmontools/',
'salmontools_archive': test_dir + 'salmontools-result.tar.gz',
'output_directory': test_dir + 'double_output/'
}
os.makedirs(job_context["salmontools_directory"], exist_ok=True)
homo_sapiens = Organism.get_object_for_name("HOMO_SAPIENS")
sample = Sample()
sample.organism = homo_sapiens
sample.save()
job_context["sample"] = sample
# Set the wrong yml filename on purpose to mess up Salmontools processor
original_yml_file = utils.ProcessorEnum['SALMONTOOLS'].value['yml_file']
utils.ProcessorEnum['SALMONTOOLS'].value['yml_file'] = 'foobar.yml'
salmon._run_salmontools(job_context)
self.assertEqual(job_context["success"], False)
self.assertTrue(job_context["job"].failure_reason.startswith('Failed to set processor:'))
# Change yml filename back
utils.ProcessorEnum['SALMONTOOLS'].value['yml_file'] = original_yml_file
def prepare_job():
# Create 10 job directories
for i in range(JOBS):
os.makedirs(LOCAL_ROOT_DIR + "/processor_job_" + str(i), exist_ok=True)
# These live on prod volumes at locations such as:
# /var/ebs/SRP057116/SRR1972985/SRR1972985.sra
os.makedirs(LOCAL_ROOT_DIR + "/SRP" + str(i), exist_ok=True)
os.makedirs(LOCAL_ROOT_DIR + "/SRP" + str(i) + "/SRR" + str(i),
exist_ok=True)
sample = Sample()
sample.accession_code = "SRR" + str(i)
sample.save()
cr = ComputationalResult()
cr.save()
cf = ComputedFile()
cf.result = cr
cf.size_in_bytes = 666
cf.save()
scfa = SampleComputedFileAssociation()
scfa.sample = sample
scfa.computed_file = cf
scfa.save()
# Create a job out of the range with index in it to make sure we
# don't delete index directories since that's where transcriptome
# indices get downloaded to.
os.makedirs(LOCAL_ROOT_DIR + "/processor_job_" + str(JOBS + 1) + "_index",
exist_ok=True)
os.makedirs(LOCAL_ROOT_DIR + "/SRP" + str(JOBS + 1) + "/SRR" +
str(JOBS + 1),
exist_ok=True)
sample = Sample()
sample.accession_code = "SRR" + str(JOBS + 1)
sample.save()
# Save two jobs so that we trigger two special circumstances, one
# where the job is still running and the other where the job isn't
# in Batch anymore.
pj = ProcessorJob()
pj.pipeline_applied = "SALMON"
pj.batch_job_id = "running_job"
pj.save()
pj = ProcessorJob()
pj.pipeline_applied = "SALMON"
pj.batch_job_id = "missing_job"
pj.save()
pj = ProcessorJob()
pj.pipeline_applied = "JANITOR"
pj.save()
return pj
def test_download_file(self, mock_send_job):
mock_send_job.return_value = None
dlj = DownloaderJob()
dlj.accession_code = "ERR036"
dlj.save()
og = OriginalFile()
og.source_filename = "ERR036000.fastq.gz"
og.source_url = "ftp://ftp.sra.ebi.ac.uk/vol1/fastq/ERR036/ERR036000/ERR036000_1.fastq.gz"
og.is_archive = True
og.save()
sample = Sample()
sample.accession_code = 'ERR036000'
sample.save()
assoc = OriginalFileSampleAssociation()
assoc.sample = sample
assoc.original_file = og
assoc.save()
assoc = DownloaderJobOriginalFileAssociation()
assoc.downloader_job = dlj
assoc.original_file = og
assoc.save()
success = sra.download_sra(dlj.pk)
def test_download_file_ncbi(self, mock_send_job):
mock_send_job.return_value = None
dlj = DownloaderJob()
dlj.accession_code = "DRR002116"
dlj.save()
og = OriginalFile()
og.source_filename = "DRR002116.sra"
og.source_url = "[email protected]:/sra/sra-instant/reads/ByRun/sra/DRR/DRR002/DRR002116/DRR002116.sra"
og.is_archive = True
og.save()
sample = Sample()
sample.accession_code = 'DRR002116'
sample.save()
assoc = OriginalFileSampleAssociation()
assoc.sample = sample
assoc.original_file = og
assoc.save()
assoc = DownloaderJobOriginalFileAssociation()
assoc.downloader_job = dlj
assoc.original_file = og
assoc.save()
result, downloaded_files = sra.download_sra(dlj.pk)
utils.end_downloader_job(dlj, result)
self.assertTrue(result)
self.assertEqual(downloaded_files[0].sha1, 'd5374e7fe047d4f76b165c3f5148ab2df9d42cea')
self.assertTrue(os.path.exists(downloaded_files[0].absolute_file_path))
def test_single_read(self):
"""Test outputs when the sample has one read only."""
job_context = {
'job_id': 456,
'job': ProcessorJob(),
'pipeline': Pipeline(name="Salmon"),
'input_file_path': self.test_dir + 'single_input/single_read.fastq',
'output_directory': self.test_dir + 'single_output/',
'salmontools_directory': self.test_dir + 'single_salmontools/',
'salmontools_archive': self.test_dir + 'salmontools-result.tar.gz',
'computed_files': []
}
os.makedirs(job_context["salmontools_directory"], exist_ok=True)
homo_sapiens = Organism.get_object_for_name("HOMO_SAPIENS")
sample = Sample()
sample.organism = homo_sapiens
sample.save()
job_context["sample"] = sample
salmon._run_salmontools(job_context)
# Confirm job status
self.assertTrue(job_context["success"])
# Unpack result for checking
os.system('gunzip ' + job_context['salmontools_directory'] + "*.gz")
# Check output file
output_file = job_context['salmontools_directory'] + 'unmapped_by_salmon.fa'
expected_output_file = self.test_dir + 'expected_single_output/unmapped_by_salmon.fa'
self.assertTrue(identical_checksum(output_file, expected_output_file))
def test_download_file_ncbi(self):
dlj = DownloaderJob()
dlj.accession_code = "SRR9117853"
dlj.save()
og = OriginalFile()
og.source_filename = "SRR9117853.sra"
og.source_url = "[email protected]:/sra/sra-instant/reads/ByRun/sra/SRR/SRR9117/SRR9117853/SRR9117853.sra"
og.is_archive = True
og.save()
sample = Sample()
sample.accession_code = "SRR9117853"
sample.save()
assoc = OriginalFileSampleAssociation()
assoc.sample = sample
assoc.original_file = og
assoc.save()
assoc = DownloaderJobOriginalFileAssociation()
assoc.downloader_job = dlj
assoc.original_file = og
assoc.save()
result, downloaded_files = sra.download_sra(dlj.pk)
utils.end_downloader_job(dlj, result)
self.assertTrue(result)
self.assertEqual(downloaded_files[0].sha1, "e7ad484fe6f134ba7d1b2664e58cc15ae5a958cc")
self.assertTrue(os.path.exists(downloaded_files[0].absolute_file_path))
def test_download_file(self):
dlj = DownloaderJob()
dlj.accession_code = "ERR036"
dlj.save()
og = OriginalFile()
og.source_filename = "ERR036000.fastq.gz"
og.source_url = "ftp.sra.ebi.ac.uk/vol1/fastq/ERR036/ERR036000/ERR036000_1.fastq.gz"
og.is_archive = True
og.save()
sample = Sample()
sample.accession_code = "ERR036000"
sample.save()
assoc = OriginalFileSampleAssociation()
assoc.sample = sample
assoc.original_file = og
assoc.save()
assoc = DownloaderJobOriginalFileAssociation()
assoc.downloader_job = dlj
assoc.original_file = og
assoc.save()
result, downloaded_files = sra.download_sra(dlj.pk)
self.assertTrue(result)
self.assertEqual(downloaded_files[0].sha1,
"1dfe5460a4101fe87feeffec0cb2e053f6695961")
self.assertTrue(os.path.exists(downloaded_files[0].absolute_file_path))
def test_management_command(self):
sample = Sample()
sample.accession_code = "DRR001173"
sample.technology = "RNA-SEQ"
sample.source_database = "SRA"
sample.title = "Not important"
sample.save()
command = Command()
command.handle(file=TEST_METADATA,
source_name="refinebio_tests",
methods_url="ccdatalab.org")
self.assertEqual(SampleAttribute.objects.all().count(), 1)
metadata = sample.to_metadata_dict()
self.assertIsNotNone(metadata.get("other_metadata", None))
self.assertEqual(len(metadata["other_metadata"]), 1)
# Make sure everything matches what was in TEST_METADATA
self.assertEqual(metadata["other_metadata"][0]["name"]["term"],
"PATO:0000047")
self.assertEqual(metadata["other_metadata"][0]["name"]["name"],
"biological sex")
self.assertEqual(metadata["other_metadata"][0]["value"]["term"],
"PATO:0000383")
self.assertEqual(metadata["other_metadata"][0]["value"]["name"],
"female")
self.assertAlmostEqual(metadata["other_metadata"][0]["probability"],
0.7856624891880539)
def make_test_data(organism):
experiment = Experiment()
experiment.accession_code = "GSE51088"
experiment.technology = "RNA-SEQ"
experiment.save()
xoa = ExperimentOrganismAssociation()
xoa.experiment = experiment
xoa.organism = organism
xoa.save()
result = ComputationalResult()
result.save()
sample = Sample()
sample.accession_code = "GSM1237818"
sample.title = "GSM1237818"
sample.organism = organism
sample.technology = "RNA-SEQ"
sample.is_processed = True
sample.save()
sra = SampleResultAssociation()
sra.sample = sample
sra.result = result
sra.save()
esa = ExperimentSampleAssociation()
esa.experiment = experiment
esa.sample = sample
esa.save()
computed_file = ComputedFile()
computed_file.s3_key = "smasher-test-quant.sf"
computed_file.s3_bucket = "data-refinery-test-assets"
computed_file.filename = "quant.sf"
computed_file.absolute_file_path = "/home/user/data_store/QUANT/smasher-test-quant.sf"
computed_file.result = result
computed_file.is_smashable = True
computed_file.size_in_bytes = 123123
computed_file.sha1 = (
"08c7ea90b66b52f7cd9d9a569717a1f5f3874967" # this matches with the downloaded file
)
computed_file.save()
computed_file = ComputedFile()
computed_file.filename = "logquant.tsv"
computed_file.is_smashable = True
computed_file.size_in_bytes = 123123
computed_file.result = result
computed_file.save()
assoc = SampleComputedFileAssociation()
assoc.sample = sample
assoc.computed_file = computed_file
assoc.save()
def prepare_dotsra_job(filename="ERR1562482.sra"):
pj = ProcessorJob()
pj.pipeline_applied = "SALMON"
pj.id = random.randint(111, 999999)
pj.save()
c_elegans = Organism.get_object_for_name("CAENORHABDITIS_ELEGANS")
samp = Sample()
samp.accession_code = "SALMON" # So the test files go to the right place
samp.organism = c_elegans
samp.source_database = 'SRA'
samp.technology = 'RNA-SEQ'
samp.save()
prepare_organism_indices()
og_file = OriginalFile()
og_file.source_filename = filename
og_file.filename = filename
og_file.absolute_file_path = "/home/user/data_store/raw/TEST/SALMON/" + filename
og_file.is_downloaded = True
og_file.save()
og_file_samp_assoc = OriginalFileSampleAssociation()
og_file_samp_assoc.original_file = og_file
og_file_samp_assoc.sample = samp
og_file_samp_assoc.save()
assoc1 = ProcessorJobOriginalFileAssociation()
assoc1.original_file = og_file
assoc1.processor_job = pj
assoc1.save()
return pj, [og_file]
def test_sra_experiment_missing_alternate_accession(self):
"""Tests that an SRA experiment has its missing alternate_accession_code added."""
# 1. Create an experiment without an alternate_accession_code
experiment = Experiment()
experiment.accession_code = "SRP094947"
experiment.source_database = "SRA"
experiment.title = "Not important"
experiment.save()
# 2. We need to add a sample because the way that the SRA surveyor finds metadata is
# through run accessions
sample = Sample()
sample.accession_code = "SRR5099111"
sample.technology = "RNA-SEQ"
sample.source_database = "SRA"
sample.title = "Not important"
sample.save()
ExperimentSampleAssociation.objects.get_or_create(
experiment=experiment, sample=sample)
# 3. Setup is done, actually run the command.
command = Command()
command.handle()
# 4. Refresh the experiment
experiment.refresh_from_db()
# Test that the correct alternate_accession_code was added
self.assertEquals(experiment.alternate_accession_code, "GSE92260")
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_convert_processed_illumina(self):
job = ProcessorJob()
job.pipeline_applied = "NO_OP"
job.save()
# ex:
# Reporter Identifier VALUE Detection Pval
# ILMN_1343291 14.943602 0
# ILMN_1343295 13.528082 0
og_file = OriginalFile()
og_file.source_filename = "https://www.ebi.ac.uk/arrayexpress/experiments/E-GEOD-22433/"
og_file.filename = "GSM557500_sample_table.txt"
og_file.absolute_file_path = (
"/home/user/data_store/raw/TEST/NO_OP/GSM557500_sample_table.txt")
og_file.is_downloaded = True
og_file.save()
homo_sapiens = Organism(name="HOMO_SAPIENS",
taxonomy_id=9606,
is_scientific_name=True)
homo_sapiens.save()
sample = Sample()
sample.accession_code = "GSM557500"
sample.title = "GSM557500"
sample.platform_accession_code = "A-MEXP-1171"
sample.manufacturer = "ILLUMINA"
sample.organism = homo_sapiens
sample.save()
assoc = OriginalFileSampleAssociation()
assoc.original_file = og_file
assoc.sample = sample
assoc.save()
assoc1 = ProcessorJobOriginalFileAssociation()
assoc1.original_file = og_file
assoc1.processor_job = job
assoc1.save()
# To:
# ENSG00000156508 14.943602
# ENSG00000111640 13.528082
final_context = no_op.no_op_processor(job.pk)
self.assertTrue(final_context["success"])
self.assertTrue(os.path.exists(final_context["output_file_path"]))
self.assertEqual(os.path.getsize(final_context["output_file_path"]),
920374)
self.assertTrue(
no_op.check_output_quality(final_context["output_file_path"]))
def prepare_job():
pj = ProcessorJob()
pj.pipeline_applied = "AFFY_TO_PCL"
pj.save()
original_file = OriginalFile()
original_file.source_filename = "ftp://ftp.ebi.ac.uk/pub/databases/microarray/data/experiment/GEOD/E-GEOD-59071/E-GEOD-59071.raw.3.zip"
original_file.filename = "GSM1426071_CD_colon_active_1.CEL"
original_file.absolute_file_path = "/home/user/data_store/raw/TEST/CEL/GSM1426071_CD_colon_active_1.CEL"
original_file.save()
assoc1 = ProcessorJobOriginalFileAssociation()
assoc1.original_file = original_file
assoc1.processor_job = pj
assoc1.save()
c_elegans = Organism.get_object_for_name("CAENORHABDITIS_ELEGANS")
sample = Sample()
sample.title = "Heyo"
sample.organism = c_elegans
sample.is_processed = False
sample.save()
ogsa = OriginalFileSampleAssociation()
ogsa.sample = sample
ogsa.original_file = original_file
ogsa.save()
return pj
def test_get_sample_keywords(self):
experiment = Experiment()
experiment.save()
sample = Sample()
sample.title = "123"
sample.accession_code = "123"
sample.age = 23
sample.save()
experiment_sample_association = ExperimentSampleAssociation()
experiment_sample_association.sample = sample
experiment_sample_association.experiment = experiment
experiment_sample_association.save()
length = OntologyTerm()
length.ontology_term = "EFO:0002939"
length.human_readable_name = "medulloblastoma"
length.save()
sk = SampleKeyword()
sk.name = length
sk.source, _ = Contribution.objects.get_or_create(
source_name="Refinebio Tests", methods_url="ccdatalab.org")
sk.sample = sample
sk.save()
self.assertEqual(set(experiment.get_sample_keywords()),
set(["medulloblastoma"]))
def test_convert_illumina_no_header(self):
job = ProcessorJob()
job.pipeline_applied = "NO_OP"
job.save()
# ex:
# ILMN_1885639 10.0000 0.7931
# ILMN_2209417 10.0000 0.2029
# ILMN_1765401 152.0873 0.0000
og_file = OriginalFile()
og_file.source_filename = (
"https://github.com/AlexsLemonade/refinebio/files/2255178/GSM1089291-tbl-1.txt"
)
og_file.filename = "GSM1089291-tbl-1.txt"
og_file.absolute_file_path = "/home/user/data_store/raw/TEST/NO_OP/GSM1089291-tbl-1.txt"
og_file.is_downloaded = True
og_file.save()
homo_sapiens = Organism(name="HOMO_SAPIENS",
taxonomy_id=9606,
is_scientific_name=True)
homo_sapiens.save()
sample = Sample()
sample.accession_code = "GSM557500"
sample.title = "GSM557500"
sample.platform_accession_code = "A-MEXP-1171"
sample.manufacturer = "ILLUMINA"
sample.organism = homo_sapiens
sample.save()
assoc = OriginalFileSampleAssociation()
assoc.original_file = og_file
assoc.sample = sample
assoc.save()
assoc1 = ProcessorJobOriginalFileAssociation()
assoc1.original_file = og_file
assoc1.processor_job = job
assoc1.save()
# To:
# ENSG00000105675 10
# ENSG00000085721 152.0873
# ENSG00000278494 152.0873
final_context = no_op.no_op_processor(job.pk)
self.assertTrue(final_context["success"])
self.assertTrue(os.path.exists(final_context["output_file_path"]))
self.assertEqual(os.path.getsize(final_context["output_file_path"]),
786207)
def test_convert_illumina_bad_cols(self):
"""
In future, this test may be deprecated. For now it just alerts that it needs attention.
"""
job = ProcessorJob()
job.pipeline_applied = "NO_OP"
job.save()
# ex:
# ILMN_1885639 10.0000 0.7931 11.0000 0.123
# ILMN_2209417 10.0000 0.2029 11.1234 0.543
# LMN_1765401 152.0873 0.0000 99.999 0.19
og_file = OriginalFile()
og_file.source_filename = (
"https://github.com/AlexsLemonade/refinebio/files/2255178/GSM1089291-tbl-1-modified.txt"
)
og_file.filename = "GSM1089291-tbl-1-modified.txt"
og_file.absolute_file_path = (
"/home/user/data_store/raw/TEST/NO_OP/GSM1089291-tbl-1-modified.txt"
)
og_file.is_downloaded = True
og_file.save()
homo_sapiens = Organism(name="HOMO_SAPIENS",
taxonomy_id=9606,
is_scientific_name=True)
homo_sapiens.save()
sample = Sample()
sample.accession_code = "GSM557500"
sample.title = "GSM557500"
sample.platform_accession_code = "A-MEXP-1171"
sample.manufacturer = "ILLUMINA"
sample.organism = homo_sapiens
sample.save()
assoc = OriginalFileSampleAssociation()
assoc.original_file = og_file
assoc.sample = sample
assoc.save()
assoc1 = ProcessorJobOriginalFileAssociation()
assoc1.original_file = og_file
assoc1.processor_job = job
assoc1.save()
final_context = no_op.no_op_processor(job.pk)
self.assertFalse(final_context["success"])
self.assertTrue("Tell Rich!" in final_context["job"].failure_reason)
def test_download_file_unmated_reads(self):
dlj = DownloaderJob()
dlj.accession_code = "SRR1603661"
dlj.save()
og_1 = OriginalFile()
og_1.source_filename = "SRR1603661_1.fastq.gz"
og_1.source_url = "ftp.sra.ebi.ac.uk/vol1/fastq/SRR160/001/SRR1603661/SRR1603661_1.fastq.gz"
og_1.expected_md5 = "502a9a482bfa5aa75865ccc0105ad13c"
og_1.expected_size_in_bytes = 6751980628
og_1.is_archive = True
og_1.save()
og_2 = OriginalFile()
og_2.source_filename = "SRR1603661_2.fastq.gz"
og_2.source_url = "ftp.sra.ebi.ac.uk/vol1/fastq/SRR160/001/SRR1603661/SRR1603661_2.fastq.gz"
og_1.expected_md5 = "fffd24457418d255991f54ec82a39d57"
og_1.expected_size_in_bytes = 6949912932
og_2.is_archive = True
og_2.save()
sample = Sample()
sample.accession_code = "SRR1603661"
sample.save()
assoc = OriginalFileSampleAssociation()
assoc.sample = sample
assoc.original_file = og_1
assoc.save()
assoc = DownloaderJobOriginalFileAssociation()
assoc.downloader_job = dlj
assoc.original_file = og_1
assoc.save()
assoc = OriginalFileSampleAssociation()
assoc.sample = sample
assoc.original_file = og_2
assoc.save()
assoc = DownloaderJobOriginalFileAssociation()
assoc.downloader_job = dlj
assoc.original_file = og_2
assoc.save()
result, downloaded_files = sra.download_sra(dlj.pk)
utils.end_downloader_job(dlj, result)
self.assertTrue(result)
self.assertEqual(downloaded_files[0].sha1,
"52bf22472069d04fa7767429f6ab78ebd10c0152")
self.assertTrue(os.path.exists(downloaded_files[0].absolute_file_path))
def test_download_file_swapper(self):
dlj = DownloaderJob()
dlj.accession_code = "SRR9117853"
dlj.save()
og = OriginalFile()
og.source_filename = "SRR9117853.sra"
og.source_url = "[email protected]:/sra/sra-instant/reads/ByRun/sra/SRR/SRR9117/SRR9117853/SRR9117853.sra"
og.is_archive = True
og.save()
sample = Sample()
sample.accession_code = "SRR9117853"
sample.save()
assoc = OriginalFileSampleAssociation()
assoc.sample = sample
assoc.original_file = og
assoc.save()
assoc = DownloaderJobOriginalFileAssociation()
assoc.downloader_job = dlj
assoc.original_file = og
assoc.save()
result = sra._download_file(og.source_url, dlj, "/tmp/doomed", force_ftp=False)
self.assertTrue(result)
def test_fail(self):
""" Test our ability to fail """
result = ComputationalResult()
result.save()
sample = Sample()
sample.accession_code = 'XXX'
sample.title = 'XXX'
sample.organism = Organism.get_object_for_name("HOMO_SAPIENS")
sample.save()
sra = SampleResultAssociation()
sra.sample = sample
sra.result = result
sra.save()
computed_file = ComputedFile()
computed_file.filename = "NOT_REAL.PCL"
computed_file.absolute_file_path = "/home/user/data_store/PCL/" + computed_file.filename
computed_file.result = result
computed_file.size_in_bytes = 123
computed_file.is_smashable = True
computed_file.save()
assoc = SampleComputedFileAssociation()
assoc.sample = sample
assoc.computed_file = computed_file
assoc.save()
ds = Dataset()
ds.data = {'GSE51081': ['XXX']}
ds.aggregate_by = 'EXPERIMENT'
ds.scale_by = 'MINMAX'
ds.email_address = "*****@*****.**"
ds.quantile_normalize = False
ds.save()
dsid = ds.id
job = ProcessorJob()
job.pipeline_applied = "SMASHER"
job.save()
pjda = ProcessorJobDatasetAssociation()
pjda.processor_job = job
pjda.dataset = ds
pjda.save()
final_context = smasher.smash(job.pk, upload=False)
ds = Dataset.objects.get(id=dsid)
print(ds.failure_reason)
print(final_context['dataset'].failure_reason)
self.assertNotEqual(final_context['unsmashable_files'], [])
def prepare_job(job_info: dict) -> ProcessorJob:
job = ProcessorJob()
job.pipeline_applied = "NO_OP"
job.save()
og_file = OriginalFile()
og_file.source_filename = job_info["source_filename"]
og_file.filename = job_info["filename"]
og_file.absolute_file_path = job_info["absolute_file_path"]
og_file.is_downloaded = True
og_file.save()
sample = Sample()
sample.accession_code = job_info["accession_code"]
sample.title = job_info["accession_code"]
sample.platform_accession_code = job_info["platform_accession_code"]
manufacturer = job_info.get("manufacturer", None)
if manufacturer is not None:
sample.manufacturer = manufacturer
# The illumina samples need the human organism
if manufacturer == "ILLUMINA":
homo_sapiens = Organism(name="HOMO_SAPIENS",
taxonomy_id=9606,
is_scientific_name=True)
homo_sapiens.save()
sample.organism = homo_sapiens
sample.save()
assoc = OriginalFileSampleAssociation()
assoc.original_file = og_file
assoc.sample = sample
assoc.save()
assoc1 = ProcessorJobOriginalFileAssociation()
assoc1.original_file = og_file
assoc1.processor_job = job
assoc1.save()
return job
def test_get_sample_metadata_fields(self):
experiment = Experiment()
experiment.save()
sample = Sample()
sample.title = "123"
sample.accession_code = "123"
sample.specimen_part = "Lung"
sample.sex = "Male"
sample.save()
experiment_sample_association = ExperimentSampleAssociation()
experiment_sample_association.sample = sample
experiment_sample_association.experiment = experiment
experiment_sample_association.save()
self.assertEqual(set(experiment.get_sample_metadata_fields()), set(['specimen_part', 'sex']))
def prepare_illumina_job(job_info: Dict) -> ProcessorJob:
pj = ProcessorJob()
pj.pipeline_applied = "ILLUMINA_TO_PCL"
pj.save()
og_file = OriginalFile()
og_file.source_filename = job_info["source_filename"]
og_file.filename = job_info["filename"]
og_file.absolute_file_path = job_info["absolute_file_path"]
og_file.is_downloaded = True
og_file.save()
assoc1 = ProcessorJobOriginalFileAssociation()
assoc1.original_file = og_file
assoc1.processor_job = pj
assoc1.save()
for s in job_info["samples"]:
# For convenience, if you give a list of strings we'll just use the
# strings as both titles and accessions.
annotation = None
if type(s) == str:
accession_code = s
title = s
elif type(s) == tuple and list(map(type, s)) == [str, str]:
accession_code, title = s
elif type(s) == tuple and list(map(type, s)) == [str, str, dict]:
accession_code, title, annotation = s
else:
raise ValueError(f"Invalid sample type for sample {s}")
sample = Sample()
sample.accession_code = accession_code
sample.title = title
sample.organism = job_info["organism"]
sample.save()
sa = SampleAnnotation()
sa.sample = sample
sa.data = annotation if annotation is not None else {
"description": [title]
}
sa.is_ccdl = False
sa.save()
sample_assoc = OriginalFileSampleAssociation()
sample_assoc.original_file = og_file
sample_assoc.sample = sample
sample_assoc.save()
return pj
def test_good_detection(self):
"""GSE54661 appears to be mislabled (illuminaHumanv4) on GEO. Shows our detector works. """
from data_refinery_workers.processors import illumina
pj = ProcessorJob()
pj.pipeline_applied = "ILLUMINA_TO_PCL"
pj.save()
og_file = OriginalFile()
og_file.source_filename = "ftp://ftp.ncbi.nlm.nih.gov/geo/series/GSE54nnn/GSE54661/suppl/GSE54661%5Fnon%5Fnormalized%2Etxt%2Egz"
og_file.filename = "GSE54661_non_normalized.txt"
og_file.absolute_file_path = (
"/home/user/data_store/raw/TEST/ILLUMINA/GSE54661_non_normalized.txt"
)
og_file.is_downloaded = True
og_file.save()
assoc1 = ProcessorJobOriginalFileAssociation()
assoc1.original_file = og_file
assoc1.processor_job = pj
assoc1.save()
organism = Organism(name="HOMO_SAPIENS",
taxonomy_id=9606,
is_scientific_name=True)
organism.save()
sample = Sample()
sample.accession_code = "ABCD-1234"
sample.title = "hypoxia_Signal"
sample.organism = organism
sample.save()
sample_assoc = OriginalFileSampleAssociation()
sample_assoc.original_file = og_file
sample_assoc.sample = sample
sample_assoc.save()
final_context = illumina.illumina_to_pcl(pj.pk)
self.assertEqual(final_context["platform"], "illuminaHumanv3")
for key in final_context["samples"][0].sampleannotation_set.all(
)[0].data.keys():
self.assertTrue(key in [
"detected_platform", "detection_percentage",
"mapped_percentage"
])
# Cleanup after the job since it won't since we aren't running in cloud.
shutil.rmtree(final_context["work_dir"], ignore_errors=True)
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 test_get_sample_metadata_fields_age(self):
experiment = Experiment()
experiment.save()
sample = Sample()
sample.title = "123"
sample.accession_code = "123"
sample.age = 23
sample.save()
experiment_sample_association = ExperimentSampleAssociation()
experiment_sample_association.sample = sample
experiment_sample_association.experiment = experiment
experiment_sample_association.save()
self.assertEqual(set(experiment.get_sample_metadata_fields()), set(['age']))
def test_no_rnaseq(self):
"""Makes sure that no RNA-Seq data gets downloaded even if there's a job for it.
"""
dlj = DownloaderJob()
dlj.accession_code = 'GSE103217'
dlj.save()
original_file = OriginalFile()
original_file.filename = "GSE103217_family.xml.tgz"
original_file.source_url = "ftp://ftp.ncbi.nlm.nih.gov/geo/series/GSE103nnn/GSE103217/miniml/GSE103217_family.xml.tgz"
original_file.source_filename = "GSE103217_family.xml.tgz"
original_file.save()
assoc = DownloaderJobOriginalFileAssociation()
assoc.original_file = original_file
assoc.downloader_job = dlj
assoc.save()
sample = Sample()
sample.accession_code = 'GSE103217'
sample.technology = "RNA-SEQ"
sample.manufacturer = "ILLUMINA"
sample.platform_accession_code = "Illumina HiSeq 2500"
sample.save()
og_assoc = OriginalFileSampleAssociation()
og_assoc.sample = sample
og_assoc.original_file = original_file
og_assoc.save()
download_result = geo.download_geo(dlj.id)
self.assertFalse(download_result)
dlj.refresh_from_db()
self.assertFalse(dlj.success)
# It's not necessarily that we didn't extract any files, but
# none that were usable so it looks like none.
self.assertEqual(dlj.failure_reason,
"Failed to extract any downloaded files.")
def test_sra_experiment_missing_metadata(self):
"""Tests that an SRA experiment has its missing metadata added."""
# 1. Create an experiment with a bad title
BAD_TITLE = "GEO accession GSE1337 is currently private\
and is scheduled to be released on Jan 01, 1970."
experiment = Experiment()
experiment.accession_code = "DRP003977"
experiment.source_database = "SRA"
experiment.title = BAD_TITLE
experiment.save()
# 2. We need to add a sample because the way that the SRA surveyor finds metadata is
# through run accessions
sample = Sample()
sample.accession_code = "DRR002116"
sample.technology = "RNA-SEQ"
sample.source_database = "SRA"
sample.title = "Not important"
sample.save()
ExperimentSampleAssociation.objects.get_or_create(
experiment=experiment, sample=sample)
# 3. Setup is done, actually run the command.
command = Command()
command.handle()
# Test that the title was fixed
self.assertNotEqual(
Experiment.objects.get_or_create(
accession_code=experiment.accession_code)[0].title,
BAD_TITLE,
)
# Run the command again to make sure that it does not fail if there are no changes
command = Command()
command.handle()
def prepare_job(length):
pj = ProcessorJob()
pj.pipeline_applied = "TRANSCRIPTOME_INDEX_" + length.upper()
pj.save()
homo_sapiens = Organism.get_object_for_name("HOMO_SAPIENS",
taxonomy_id=1001)
samp = Sample()
samp.organism = homo_sapiens
samp.accession_code = "derp" + length
samp.save()
og_file = OriginalFile()
og_file.source_filename = "aegilops_tauschii_" + length + ".fa.gz"
og_file.filename = "aegilops_tauschii_" + length + ".fa.gz"
og_file.absolute_file_path = "/home/user/data_store/raw/TEST/TRANSCRIPTOME_INDEX/AEGILOPS_TAUSCHII/aegilops_tauschii_short.fa.gz"
og_file.is_downloaded = True
og_file.save()
og_file2 = OriginalFile()
og_file2.source_filename = "aegilops_tauschii_" + length + ".gtf.gz"
og_file2.filename = "aegilops_tauschii_" + length + ".gtf.gz"
og_file2.absolute_file_path = "/home/user/data_store/raw/TEST/TRANSCRIPTOME_INDEX/AEGILOPS_TAUSCHII/aegilops_tauschii_short.gtf.gz"
og_file2.is_downloaded = True
og_file2.save()
og_file_samp_assoc = OriginalFileSampleAssociation()
og_file_samp_assoc.original_file = og_file
og_file_samp_assoc.sample = samp
og_file_samp_assoc.save()
og_file_samp_assoc2 = OriginalFileSampleAssociation()
og_file_samp_assoc2.original_file = og_file2
og_file_samp_assoc2.sample = samp
og_file_samp_assoc2.save()
assoc1 = ProcessorJobOriginalFileAssociation()
assoc1.original_file = og_file
assoc1.processor_job = pj
assoc1.save()
assoc2 = ProcessorJobOriginalFileAssociation()
assoc2.original_file = og_file2
assoc2.processor_job = pj
assoc2.save()
return pj
