def setUp(self):
# Create a directory with the test split libraries output
self.test_slo = mkdtemp(prefix='test_slo_')
path_builder = partial(join, self.test_slo)
fna_fp = path_builder('seqs.fna')
fastq_fp = path_builder('seqs.fastq')
log_fp = path_builder('split_library_log.txt')
demux_fp = path_builder('seqs.demux')
with open(fna_fp, 'w') as f:
f.write(FASTA_SEQS)
with open(fastq_fp, 'w') as f:
f.write(FASTQ_SEQS)
with open(log_fp, 'w') as f:
f.write("Test log\n")
generate_demux_file(self.test_slo)
self._filepaths_to_remove = [fna_fp, fastq_fp, demux_fp, log_fp]
self._dirpaths_to_remove = [self.test_slo]
# Generate a directory with test split libraries output missing files
self.missing_slo = mkdtemp(prefix='test_missing_')
path_builder = partial(join, self.test_slo)
fna_fp = path_builder('seqs.fna')
fastq_fp = path_builder('seqs.fastq')
with open(fna_fp, 'w') as f:
f.write(FASTA_SEQS)
with open(fastq_fp, 'w') as f:
f.write(FASTQ_SEQS)
self._filepaths_to_remove.append(fna_fp)
self._filepaths_to_remove.append(fastq_fp)
self._dirpaths_to_remove.append(self.missing_slo)
# Create a study with no preprocessed data
info = {
"timeseries_type_id": 1,
"metadata_complete": True,
"mixs_compliant": True,
"number_samples_collected": 25,
"number_samples_promised": 28,
"study_alias": "FCM",
"study_description": "Microbiome of people who eat nothing but "
"fried chicken",
"study_abstract": "Exploring how a high fat diet changes the "
"gut microbiome",
"emp_person_id": StudyPerson(2),
"principal_investigator_id": StudyPerson(3),
"lab_person_id": StudyPerson(1)
}
self.no_ppd_study = Study.create(
User('*****@*****.**'), "Test study", [1], info)
# Get the directory where the preprocessed data is usually copied.
_, self.db_ppd_dir = get_mountpoint('preprocessed_data')[0]
def test_generate_demux_file(self):
prep_out_dir = mkdtemp()
with open(join(prep_out_dir, 'seqs.fastq'), "w") as f:
f.write(DEMUX_SEQS)
obs_fp = generate_demux_file(prep_out_dir)
exp_fp = join(prep_out_dir, 'seqs.demux')
self.assertEqual(obs_fp, exp_fp)
self.assertTrue(exists(exp_fp))
def test_generate_demux_file(self):
prep_out_dir = mkdtemp()
with open(join(prep_out_dir, 'seqs.fastq'), "w") as f:
f.write(DEMUX_SEQS)
obs_fp = generate_demux_file(prep_out_dir)
exp_fp = join(prep_out_dir, 'seqs.demux')
self.assertEqual(obs_fp, exp_fp)
self.assertTrue(exists(exp_fp))
def setUp(self):
# Create a directory with the test split libraries output
self.test_slo = mkdtemp(prefix='test_slo_')
path_builder = partial(join, self.test_slo)
fna_fp = path_builder('seqs.fna')
fastq_fp = path_builder('seqs.fastq')
log_fp = path_builder('split_library_log.txt')
demux_fp = path_builder('seqs.demux')
with open(fna_fp, 'w') as f:
f.write(FASTA_SEQS)
with open(fastq_fp, 'w') as f:
f.write(FASTQ_SEQS)
with open(log_fp, 'w') as f:
f.write("Test log\n")
generate_demux_file(self.test_slo)
self._filepaths_to_remove = [fna_fp, fastq_fp, demux_fp, log_fp]
self._dirpaths_to_remove = [self.test_slo]
# Generate a directory with test split libraries output missing files
self.missing_slo = mkdtemp(prefix='test_missing_')
path_builder = partial(join, self.test_slo)
fna_fp = path_builder('seqs.fna')
fastq_fp = path_builder('seqs.fastq')
with open(fna_fp, 'w') as f:
f.write(FASTA_SEQS)
with open(fastq_fp, 'w') as f:
f.write(FASTQ_SEQS)
self._filepaths_to_remove.append(fna_fp)
self._filepaths_to_remove.append(fastq_fp)
self._dirpaths_to_remove.append(self.missing_slo)
# Create a study with no preprocessed data
info = {
"timeseries_type_id": 1,
"metadata_complete": True,
"mixs_compliant": True,
"number_samples_collected": 25,
"number_samples_promised": 28,
"portal_type_id": 3,
"study_alias": "FCM",
"study_description": "Microbiome of people who eat nothing but "
"fried chicken",
"study_abstract": "Exploring how a high fat diet changes the "
"gut microbiome",
"emp_person_id": StudyPerson(2),
"principal_investigator_id": StudyPerson(3),
"lab_person_id": StudyPerson(1)
}
self.no_ppd_study = Study.create(User('*****@*****.**'), "Test study",
[1], info)
# Get the directory where the preprocessed data is usually copied.
_, self.db_ppd_dir = get_mountpoint('preprocessed_data')[0]
