def create(cls, md_template, raw_data, study, data_type,
investigation_type=None):
r"""Creates the metadata template in the database
Parameters
----------
md_template : DataFrame
The metadata template file contents indexed by samples Ids
raw_data : RawData
The raw_data to which the prep template belongs to.
study : Study
The study to which the prep template belongs to.
data_type : str or int
The data_type of the prep template
investigation_type : str, optional
The investigation type, if relevant
Returns
-------
A new instance of `cls` to access to the PrepTemplate stored in the DB
Raises
------
QiitaDBColumnError
If the investigation_type is not valid
If a required column is missing in md_template
"""
# If the investigation_type is supplied, make sure it is one of
# the recognized investigation types
if investigation_type is not None:
cls.validate_investigation_type(investigation_type)
# Get a connection handler
conn_handler = SQLConnectionHandler()
queue_name = "CREATE_PREP_TEMPLATE_%d" % raw_data.id
conn_handler.create_queue(queue_name)
# Check if the data_type is the id or the string
if isinstance(data_type, (int, long)):
data_type_id = data_type
data_type_str = convert_from_id(data_type, "data_type",
conn_handler)
else:
data_type_id = convert_to_id(data_type, "data_type", conn_handler)
data_type_str = data_type
md_template = cls._clean_validate_template(md_template, study.id,
data_type_str, conn_handler)
# Insert the metadata template
# We need the prep_id for multiple calls below, which currently is not
# supported by the queue system. Thus, executing this outside the queue
prep_id = conn_handler.execute_fetchone(
"INSERT INTO qiita.prep_template (data_type_id, raw_data_id, "
"investigation_type) VALUES (%s, %s, %s) RETURNING "
"prep_template_id", (data_type_id, raw_data.id,
investigation_type))[0]
cls._add_common_creation_steps_to_queue(md_template, prep_id,
conn_handler, queue_name)
try:
conn_handler.execute_queue(queue_name)
except Exception:
# Clean up row from qiita.prep_template
conn_handler.execute(
"DELETE FROM qiita.prep_template where "
"{0} = %s".format(cls._id_column), (prep_id,))
# Check if sample IDs present here but not in sample template
sql = ("SELECT sample_id from qiita.required_sample_info WHERE "
"study_id = %s")
# Get list of study sample IDs, prep template study IDs,
# and their intersection
prep_samples = set(md_template.index.values)
unknown_samples = prep_samples.difference(
s[0] for s in conn_handler.execute_fetchall(sql, [study.id]))
if unknown_samples:
raise QiitaDBExecutionError(
'Samples found in prep template but not sample template: '
'%s' % ', '.join(unknown_samples))
# some other error we haven't seen before so raise it
raise
pt = cls(prep_id)
pt.generate_files()
return pt
def create_templates_from_qiime_mapping_file(fp, study, data_type):
"""Creates a sample template and a prep template from qiime mapping file
Parameters
----------
fp : str or file-like object
Path to the QIIME mapping file
study : Study
The study to which the sample template belongs to
data_type : str or int
The data_type of the prep_template
Returns
-------
(SampleTemplate, PrepTemplate)
The templates created from the QIIME mapping file
"""
qiime_map = load_template_to_dataframe(fp, index='#SampleID')
# There are a few columns in the QIIME mapping file that are special and
# we know how to deal with them
rename_cols = {
'BarcodeSequence': 'barcode',
'LinkerPrimerSequence': 'primer',
'Description': 'description',
}
if 'ReverseLinkerPrimer' in qiime_map:
rename_cols['ReverseLinkerPrimer'] = 'reverselinkerprimer'
missing = set(rename_cols).difference(qiime_map.columns)
if missing:
raise QiitaWareError(
"Error generating the templates from the QIIME mapping file. "
"Missing QIIME mapping file columns: %s" % ', '.join(missing))
qiime_map.rename(columns=rename_cols, inplace=True)
# Fix the casing in the columns that we control
qiime_map.columns = [c.lower() if c.lower() in CONTROLLED_COLS else c
for c in qiime_map.columns]
# Figure out which columns belong to the prep template
def _col_iterator(restriction_set):
for restriction in viewvalues(restriction_set):
for cols in viewkeys(restriction.columns):
yield cols
pt_cols = set(col for col in _col_iterator(PREP_TEMPLATE_COLUMNS))
data_type_str = (convert_from_id(data_type, "data_type")
if isinstance(data_type, (int, long)) else data_type)
if data_type_str in TARGET_GENE_DATA_TYPES:
pt_cols.update(
col for col in _col_iterator(PREP_TEMPLATE_COLUMNS_TARGET_GENE))
pt_cols.add('reverselinkerprimer')
qiime_cols = set(qiime_map.columns)
pt_cols = qiime_cols.intersection(pt_cols)
st_cols = qiime_cols.difference(pt_cols)
st_md = qiime_map.ix[:, st_cols]
pt_md = qiime_map.ix[:, pt_cols]
return (SampleTemplate.create(st_md, study),
PrepTemplate.create(pt_md, study, data_type))
def create(cls, md_template, study, data_type, investigation_type=None):
r"""Creates the metadata template in the database
Parameters
----------
md_template : DataFrame
The metadata template file contents indexed by samples Ids
study : Study
The study to which the prep template belongs to.
data_type : str or int
The data_type of the prep template
investigation_type : str, optional
The investigation type, if relevant
Returns
-------
A new instance of `cls` to access to the PrepTemplate stored in the DB
Raises
------
QiitaDBColumnError
If the investigation_type is not valid
If a required column is missing in md_template
"""
with TRN:
# If the investigation_type is supplied, make sure it is one of
# the recognized investigation types
if investigation_type is not None:
cls.validate_investigation_type(investigation_type)
# Check if the data_type is the id or the string
if isinstance(data_type, (int, long)):
data_type_id = data_type
data_type_str = convert_from_id(data_type, "data_type")
else:
data_type_id = convert_to_id(data_type, "data_type")
data_type_str = data_type
pt_cols = PREP_TEMPLATE_COLUMNS
if data_type_str in TARGET_GENE_DATA_TYPES:
pt_cols = deepcopy(PREP_TEMPLATE_COLUMNS)
pt_cols.update(PREP_TEMPLATE_COLUMNS_TARGET_GENE)
md_template = cls._clean_validate_template(md_template, study.id,
pt_cols)
# Insert the metadata template
sql = """INSERT INTO qiita.prep_template
(data_type_id, investigation_type)
VALUES (%s, %s)
RETURNING prep_template_id"""
TRN.add(sql, [data_type_id, investigation_type])
prep_id = TRN.execute_fetchlast()
try:
cls._common_creation_steps(md_template, prep_id)
except Exception:
# Check if sample IDs present here but not in sample template
sql = """SELECT sample_id from qiita.study_sample
WHERE study_id = %s"""
# Get list of study sample IDs, prep template study IDs,
# and their intersection
TRN.add(sql, [study.id])
prep_samples = set(md_template.index.values)
unknown_samples = prep_samples.difference(
TRN.execute_fetchflatten())
if unknown_samples:
raise QiitaDBExecutionError(
'Samples found in prep template but not sample '
'template: %s' % ', '.join(unknown_samples))
# some other error we haven't seen before so raise it
raise
# Link the prep template with the study
sql = """INSERT INTO qiita.study_prep_template
(study_id, prep_template_id)
VALUES (%s, %s)"""
TRN.add(sql, [study.id, prep_id])
TRN.execute()
pt = cls(prep_id)
pt.generate_files()
return pt
def testConvertFromID(self):
self.assertEqual(convert_from_id(807481739, 'ontology'), 'ENA')
def create_templates_from_qiime_mapping_file(fp, study, data_type):
"""Creates a sample template and a prep template from qiime mapping file
Parameters
----------
fp : str or file-like object
Path to the QIIME mapping file
study : Study
The study to which the sample template belongs to
data_type : str or int
The data_type of the prep_template
Returns
-------
(SampleTemplate, PrepTemplate)
The templates created from the QIIME mapping file
"""
qiime_map = load_template_to_dataframe(fp, index='#SampleID')
# There are a few columns in the QIIME mapping file that are special and
# we know how to deal with them
rename_cols = {
'BarcodeSequence': 'barcode',
'LinkerPrimerSequence': 'primer',
'Description': 'description',
}
if 'ReverseLinkerPrimer' in qiime_map:
rename_cols['ReverseLinkerPrimer'] = 'reverselinkerprimer'
missing = set(rename_cols).difference(qiime_map.columns)
if missing:
raise QiitaWareError(
"Error generating the templates from the QIIME mapping file. "
"Missing QIIME mapping file columns: %s" % ', '.join(missing))
qiime_map.rename(columns=rename_cols, inplace=True)
# Fix the casing in the columns that we control
qiime_map.columns = [
c.lower() if c.lower() in CONTROLLED_COLS else c
for c in qiime_map.columns
]
# Figure out which columns belong to the prep template
def _col_iterator(restriction_set):
for restriction in restriction_set.values():
for cols in restriction.columns.keys():
yield cols
pt_cols = set(col for col in _col_iterator(PREP_TEMPLATE_COLUMNS))
data_type_str = (convert_from_id(data_type, "data_type") if isinstance(
data_type, int) else data_type)
if data_type_str in TARGET_GENE_DATA_TYPES:
pt_cols.update(
col for col in _col_iterator(PREP_TEMPLATE_COLUMNS_TARGET_GENE))
pt_cols.add('reverselinkerprimer')
qiime_cols = set(qiime_map.columns)
pt_cols = qiime_cols.intersection(pt_cols)
st_cols = qiime_cols.difference(pt_cols)
st_md = qiime_map.loc[:, st_cols]
pt_md = qiime_map.loc[:, pt_cols]
return (SampleTemplate.create(st_md, study),
PrepTemplate.create(pt_md, study, data_type))