def _collect_pre_casava_qc(self):
qc_objects = []
runinfo_yaml = os.path.join(os.path.abspath(self.pargs.flowcell), "run_info.yaml")
try:
with open(runinfo_yaml) as fh:
runinfo = yaml.load(fh)
except IOError as e:
self.app.log.warn(str(e))
raise e
fcdir = os.path.abspath(self.pargs.flowcell)
(fc_date, fc_name) = self._fc_parts()
## Check modification time
if modified_within_days(fcdir, self.pargs.mtime):
fc_kw = dict(path=fcdir, fc_date = fc_date, fc_name=fc_name)
fcobj = FlowcellRunMetrics(**fc_kw)
fcobj.parse_illumina_metrics(fullRTA=False)
fcobj.parse_bc_metrics()
fcobj.parse_filter_metrics()
if not fcobj.parse_samplesheet_csv():
fcobj.parse_run_info_yaml()
qc_objects.append(fcobj)
else:
return qc_objects
for info in runinfo:
if not info.get("multiplex", None):
self.app.log.warn("No multiplex information for lane {}".format(info.get("lane")))
sample.update({k: info.get(k, None) for k in ('analysis', 'description', 'flowcell_id', 'lane')})
sample_kw = dict(path=fcdir, flowcell=fc_name, date=fc_date, lane=sample.get('lane', None), barcode_name=sample.get('name', None), sample_prj=sample.get('sample_prj', None),
barcode_id=sample.get('barcode_id', None), sequence=sample.get('sequence', "NoIndex"))
for sample in info["multiplex"]:
sample.update({k: info.get(k, None) for k in ('analysis', 'description', 'flowcell_id', 'lane')})
sample_kw = dict(path=fcdir, flowcell=fc_name, date=fc_date, lane=sample['lane'], barcode_name=sample['name'], sample_prj=sample.get('sample_prj', None),
barcode_id=sample['barcode_id'], sequence=sample.get('sequence', "NoIndex"))
obj = SampleRunMetrics(**sample_kw)
obj.read_picard_metrics()
obj.parse_fastq_screen()
obj.parse_bc_metrics()
obj.read_fastqc_metrics()
qc_objects.append(obj)
return qc_objects
