def _collect_casava_qc(self):
qc_objects = []
runinfo_csv = os.path.join(os.path.abspath(self.pargs.flowcell), "{}.csv".format(self._fc_id()))
try:
with open(runinfo_csv) as fh:
runinfo_reader = csv.reader(fh)
runinfo = [x for x in runinfo_reader]
except IOError as e:
self.app.log.warn(str(e))
raise e
fcdir = os.path.join(os.path.abspath(self.pargs.analysis), 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_demultiplex_stats_htm()
fcobj.parse_samplesheet_csv()
qc_objects.append(fcobj)
for sample in runinfo[1:]:
d = dict(zip(runinfo[0], sample))
if self.app.pargs.project and self.app.pargs.project != d['SampleProject']:
continue
if self.app.pargs.sample and self.app.pargs.sample != d['SampleID']:
continue
sampledir = os.path.join(os.path.abspath(self.pargs.analysis), d['SampleProject'].replace("__", "."), d['SampleID'])
if not os.path.exists(sampledir):
self.app.log.warn("No such sample directory: {}".format(sampledir))
continue
sample_fcdir = os.path.join(sampledir, self._fc_fullname())
if not os.path.exists(sample_fcdir):
self.app.log.warn("No such sample flowcell directory: {}".format(sample_fcdir))
continue
if not modified_within_days(sample_fcdir, self.pargs.mtime):
continue
runinfo_yaml_file = os.path.join(sample_fcdir, "{}-bcbb-config.yaml".format(d['SampleID']))
if not os.path.exists(runinfo_yaml_file):
self.app.log.warn("No such yaml file for sample: {}".format(runinfo_yaml_file))
raise IOError(2, "No such yaml file for sample: {}".format(runinfo_yaml_file), runinfo_yaml_file)
with open(runinfo_yaml_file) as fh:
runinfo_yaml = yaml.load(fh)
if not runinfo_yaml['details'][0].get("multiplex", None):
self.app.log.warn("No multiplex information for sample {}".format(d['SampleID']))
continue
sample_kw = dict(path=sample_fcdir, flowcell=fc_name, date=fc_date, lane=d['Lane'], barcode_name=d['SampleID'], sample_prj=d['SampleProject'].replace("__", "."), barcode_id=runinfo_yaml['details'][0]['multiplex'][0]['barcode_id'], sequence=runinfo_yaml['details'][0]['multiplex'][0]['sequence'])
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
def _parse_samplesheet(self, runinfo, qc_objects, fc_date, fc_name, fcdir, as_yaml=False, demultiplex_stats=None, setup=None):
"""Parse samplesheet information and populate sample run metrics object"""
if as_yaml:
for info in runinfo:
if not info.get("multiplex", None):
self.app.log.warn("No multiplex information for lane {}".format(info.get("lane")))
sample = {}
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(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"))
parser = SampleRunMetricsParser(fcdir)
obj = SampleRunMetricsDocument(**sample_kw)
obj["picard_metrics"] = parser.read_picard_metrics(**sample_kw)
obj["fastq_scr"] = parser.parse_fastq_screen(**sample_kw)
obj["bc_count"] = parser.get_bc_count(run_setup=setup, **sample_kw)
obj["fastqc"] = parser.read_fastqc_metrics(**sample_kw)
obj["bcbb_checkpoints"] = parser.parse_bcbb_checkpoints(**sample_kw)
qc_objects.append(obj)
else:
for d in runinfo:
LOG.debug("Getting information for sample defined by {}".format(d.values()))
if self.app.pargs.project_name and self.app.pargs.project_name != d['SampleProject']:
continue
if self.app.pargs.sample and self.app.pargs.sample != d['SampleID']:
continue
sampledir = os.path.join(os.path.abspath(self._meta.production_root_path), d['SampleProject'].replace("__", "."), d['SampleID'])
if not os.path.exists(sampledir):
self.app.log.warn("No such sample directory: {}".format(sampledir))
continue
sample_fcdir = os.path.join(sampledir, fc_fullname(self.pargs.flowcell))
if not os.path.exists(sample_fcdir):
self.app.log.warn("No such sample flowcell directory: {}".format(sample_fcdir))
continue
if not modified_within_days(sample_fcdir, self.pargs.mtime):
continue
runinfo_yaml_file = os.path.join(sample_fcdir, "{}-bcbb-config.yaml".format(d['SampleID']))
if not os.path.exists(runinfo_yaml_file):
self.app.log.warn("No such yaml file for sample: {}".format(runinfo_yaml_file))
raise IOError(2, "No such yaml file for sample: {}".format(runinfo_yaml_file), runinfo_yaml_file)
with open(runinfo_yaml_file) as fh:
runinfo_yaml = yaml.load(fh)
if not runinfo_yaml['details'][0].get("multiplex", None):
self.app.log.warn("No multiplex information for sample {}".format(d['SampleID']))
runinfo_yaml['details'][0]['multiplex'] = [{'barcode_id': 0, 'sequence': 'NoIndex'}]
sample_kw = dict(flowcell=fc_name, date=fc_date, lane=d['Lane'], barcode_name=d['SampleID'], sample_prj=d['SampleProject'].replace("__", "."), barcode_id=runinfo_yaml['details'][0]['multiplex'][0]['barcode_id'], sequence=runinfo_yaml['details'][0]['multiplex'][0]['sequence'])
parser = SampleRunMetricsParser(sample_fcdir)
obj = SampleRunMetricsDocument(**sample_kw)
obj["picard_metrics"] = parser.read_picard_metrics(**sample_kw)
obj["fastq_scr"] = parser.parse_fastq_screen(**sample_kw)
obj["bc_count"] = parser.get_bc_count(demultiplex_stats=demultiplex_stats, run_setup=setup, **sample_kw)
obj["fastqc"] = parser.read_fastqc_metrics(**sample_kw)
obj["bcbb_checkpoints"] = parser.parse_bcbb_checkpoints(**sample_kw)
qc_objects.append(obj)
return qc_objects
def _parse_samplesheet(self, runinfo, qc_objects, fc_date, fc_name, fcdir, as_yaml=False, demultiplex_stats=None, setup=None):
"""Parse samplesheet information and populate sample run metrics object"""
if as_yaml:
for info in runinfo:
if not info.get("multiplex", None):
self.app.log.warn("No multiplex information for lane {}".format(info.get("lane")))
sample = {}
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(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"))
parser = SampleRunMetricsParser(fcdir)
obj = SampleRunMetricsDocument(**sample_kw)
obj["picard_metrics"] = parser.read_picard_metrics(**sample_kw)
obj["fastq_scr"] = parser.parse_fastq_screen(**sample_kw)
obj["bc_count"] = parser.get_bc_count(run_setup=setup, **sample_kw)
obj["fastqc"] = parser.read_fastqc_metrics(**sample_kw)
obj["bcbb_checkpoints"] = parser.parse_bcbb_checkpoints(**sample_kw)
qc_objects.append(obj)
else:
for d in runinfo:
LOG.debug("Getting information for sample defined by {}".format(d.values()))
if self.app.pargs.project_name and self.app.pargs.project_name != d['SampleProject']:
continue
if self.app.pargs.sample and self.app.pargs.sample != d['SampleID']:
continue
sampledir = os.path.join(os.path.abspath(self._meta.production_root_path), d['SampleProject'].replace("__", "."), d['SampleID'])
if not os.path.exists(sampledir):
self.app.log.warn("No such sample directory: {}".format(sampledir))
continue
sample_fcdir = os.path.join(sampledir, fc_fullname(self.pargs.flowcell))
if not os.path.exists(sample_fcdir):
self.app.log.warn("No such sample flowcell directory: {}".format(sample_fcdir))
continue
if not modified_within_days(sample_fcdir, self.pargs.mtime):
continue
runinfo_yaml_file = os.path.join(sample_fcdir, "{}-bcbb-config.yaml".format(d['SampleID']))
if not os.path.exists(runinfo_yaml_file):
self.app.log.warn("No such yaml file for sample: {}".format(runinfo_yaml_file))
raise IOError(2, "No such yaml file for sample: {}".format(runinfo_yaml_file), runinfo_yaml_file)
with open(runinfo_yaml_file) as fh:
runinfo_yaml = yaml.load(fh)
if not runinfo_yaml['details'][0].get("multiplex", None):
self.app.log.warn("No multiplex information for sample {}".format(d['SampleID']))
runinfo_yaml['details'][0]['multiplex'] = [{'barcode_id': 0, 'sequence': 'NoIndex'}]
sample_kw = dict(flowcell=fc_name, date=fc_date, lane=d['Lane'], barcode_name=d['SampleID'], sample_prj=d['SampleProject'].replace("__", "."), barcode_id=runinfo_yaml['details'][0]['multiplex'][0]['barcode_id'], sequence=runinfo_yaml['details'][0]['multiplex'][0]['sequence'])
parser = SampleRunMetricsParser(sample_fcdir)
obj = SampleRunMetricsDocument(**sample_kw)
obj["picard_metrics"] = parser.read_picard_metrics(**sample_kw)
obj["fastq_scr"] = parser.parse_fastq_screen(**sample_kw)
obj["bc_count"] = parser.get_bc_count(demultiplex_stats=demultiplex_stats, run_setup=setup, **sample_kw)
obj["fastqc"] = parser.read_fastqc_metrics(**sample_kw)
obj["bcbb_checkpoints"] = parser.parse_bcbb_checkpoints(**sample_kw)
qc_objects.append(obj)
return qc_objects
def _collect_casava_qc(self):
qc_objects = []
runinfo_csv = os.path.join(os.path.join(self._meta.root_path, self.pargs.flowcell), "{}.csv".format(fc_id(self.pargs.flowcell)))
if not os.path.exists(runinfo_csv):
LOG.warn("No such file {}: trying fallback SampleSheet.csv".format(runinfo_csv))
runinfo_csv = os.path.join(os.path.join(self._meta.root_path, self.pargs.flowcell), "SampleSheet.csv")
try:
with open(runinfo_csv) as fh:
runinfo_reader = csv.reader(fh)
runinfo = [x for x in runinfo_reader]
except IOError as e:
self.app.log.warn(str(e))
raise e
fcdir = os.path.join(os.path.abspath(self._meta.root_path), self.pargs.flowcell)
(fc_date, fc_name) = fc_parts(self.pargs.flowcell)
## Check modification time
demux_stats = None
if modified_within_days(fcdir, self.pargs.mtime):
fc_kw = dict(fc_date = fc_date, fc_name=fc_name)
parser = FlowcellRunMetricsParser(fcdir)
fcobj = FlowcellRunMetricsDocument(fc_date, fc_name)
fcobj["RunInfo"] = parser.parseRunInfo(**fc_kw)
fcobj["RunParameters"] = parser.parseRunParameters(**fc_kw)
fcobj["illumina"] = parser.parse_illumina_metrics(fullRTA=False, **fc_kw)
fcobj["bc_metrics"] = parser.parse_bc_metrics(**fc_kw)
fcobj["undemultiplexed_barcodes"] = parser.parse_undemultiplexed_barcode_metrics(**fc_kw)
fcobj["illumina"].update({"Demultiplex_Stats" : parser.parse_demultiplex_stats_htm(**fc_kw)})
fcobj["samplesheet_csv"] = parser.parse_samplesheet_csv(runinfo_csv=runinfo_csv, **fc_kw)
demux_stats = fcobj["illumina"]["Demultiplex_Stats"]
qc_objects.append(fcobj)
qc_objects = self._parse_samplesheet(runinfo, qc_objects, fc_date, fc_name, fcdir, demultiplex_stats=demux_stats)
return qc_objects
def _collect_casava_qc(self):
qc_objects = []
runinfo_csv = os.path.join(os.path.join(self._meta.root_path, self.pargs.flowcell), "{}.csv".format(fc_id(self.pargs.flowcell)))
if not os.path.exists(runinfo_csv):
LOG.warn("No such file {}: trying fallback SampleSheet.csv".format(runinfo_csv))
runinfo_csv = os.path.join(os.path.join(self._meta.root_path, self.pargs.flowcell), "SampleSheet.csv")
try:
with open(runinfo_csv) as fh:
runinfo_reader = csv.reader(fh)
runinfo = [x for x in runinfo_reader]
except IOError as e:
self.app.log.warn(str(e))
raise e
fcdir = os.path.join(os.path.abspath(self._meta.root_path), self.pargs.flowcell)
(fc_date, fc_name) = fc_parts(self.pargs.flowcell)
## Check modification time
if modified_within_days(fcdir, self.pargs.mtime):
fc_kw = dict(fc_date = fc_date, fc_name=fc_name)
parser = FlowcellRunMetricsParser(fcdir)
fcobj = FlowcellRunMetricsDocument(fc_date, fc_name)
fcobj["RunInfo"] = parser.parseRunInfo(**fc_kw)
fcobj["RunParameters"] = parser.parseRunParameters(**fc_kw)
fcobj["illumina"] = parser.parse_illumina_metrics(fullRTA=False, **fc_kw)
fcobj["bc_metrics"] = parser.parse_bc_metrics(**fc_kw)
fcobj["undemultiplexed_barcodes"] = parser.parse_undemultiplexed_barcode_metrics(**fc_kw)
fcobj["illumina"].update({"Demultiplex_Stats" : parser.parse_demultiplex_stats_htm(**fc_kw)})
fcobj["samplesheet_csv"] = parser.parse_samplesheet_csv(runinfo_csv=runinfo_csv, **fc_kw)
qc_objects.append(fcobj)
qc_objects = self._parse_samplesheet(runinfo, qc_objects, fc_date, fc_name, fcdir, demultiplex_stats=fcobj["illumina"]["Demultiplex_Stats"])
return qc_objects
def _collect_casava_qc(self):
qc_objects = []
read_setup = None
demux_stats = None
fcdir = os.path.join(os.path.abspath(self._meta.root_path),
self.pargs.flowcell)
# Get the fc_name, fc_date from RunInfo
parser = FlowcellRunMetricsParser(fcdir)
runinfo_xml = parser.parseRunInfo()
runparams = parser.parseRunParameters()
fc_date = runinfo_xml.get('Date', None)
fc_name = runinfo_xml.get('Flowcell', None)
fc_pos = runparams.get('FCPosition', '')
runinfo_csv = os.path.join(
os.path.join(self._meta.root_path, self.pargs.flowcell),
"{}.csv".format(fc_name))
if not os.path.exists(runinfo_csv):
LOG.warn("No such file {}: trying fallback SampleSheet.csv".format(
runinfo_csv))
runinfo_csv = os.path.join(
os.path.join(self._meta.root_path, self.pargs.flowcell),
"SampleSheet.csv")
runinfo = parser.parse_samplesheet_csv(runinfo_csv=runinfo_csv)
if modified_within_days(fcdir, self.pargs.mtime):
# Most of the code expects to have the flowcell position pre-pended to the flowcell id
fc_kw = dict(fc_date=fc_date,
fc_name="{}{}".format(fc_pos, fc_name))
fcobj = FlowcellRunMetricsDocument(**fc_kw)
fcobj["RunInfo"] = runinfo_xml
fcobj["RunParameters"] = runparams
fcobj["DemultiplexConfig"] = parser.parseDemultiplexConfig(**fc_kw)
fcobj["illumina"] = parser.parse_illumina_metrics(fullRTA=False,
**fc_kw)
fcobj["bc_metrics"] = parser.parse_bc_metrics(**fc_kw)
fcobj[
"undemultiplexed_barcodes"] = parser.parse_undemultiplexed_barcode_metrics(
**fc_kw)
fcobj["illumina"].update({
"Demultiplex_Stats":
parser.parse_demultiplex_stats_htm(**fc_kw)
})
fcobj["samplesheet_csv"] = runinfo
read_setup = fcobj["RunInfo"].get('Reads', [])
fcobj["run_setup"] = self._run_setup(read_setup)
demux_stats = fcobj["illumina"]["Demultiplex_Stats"]
qc_objects.append(fcobj)
qc_objects = self._parse_samplesheet(runinfo,
qc_objects,
fc_date,
"{}{}".format(fc_pos, fc_name),
fcdir,
demultiplex_stats=demux_stats,
setup=read_setup)
return qc_objects
def _collect_pre_casava_qc(self):
qc_objects = []
as_yaml = False
runinfo_csv = os.path.join(
os.path.join(self._meta.root_path, self.pargs.flowcell),
"{}.csv".format(fc_id(self.pargs.flowcell)))
if not os.path.exists(runinfo_csv):
LOG.warn("No such file {}: trying fallback SampleSheet.csv".format(
runinfo_csv))
runinfo_csv = os.path.join(
os.path.join(self._meta.root_path, self.pargs.flowcell),
"SampleSheet.csv")
runinfo_yaml = os.path.join(os.path.abspath(self.pargs.flowcell),
"run_info.yaml")
try:
if os.path.exists(runinfo_csv):
with open(runinfo_csv) as fh:
runinfo_reader = csv.reader(fh)
runinfo = [x for x in runinfo_reader]
else:
as_yaml = True
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) = fc_parts(self.pargs.flowcell)
## Check modification time
if modified_within_days(fcdir, self.pargs.mtime):
fc_kw = dict(fc_date=fc_date, fc_name=fc_name)
parser = FlowcellRunMetricsParser(fcdir)
fcobj = FlowcellRunMetricsDocument(**fc_kw)
fcobj["RunInfo"] = parser.parseRunInfo(**fc_kw)
fcobj["RunParameters"] = parser.parseRunParameters(**fc_kw)
fcobj["illumina"] = parser.parse_illumina_metrics(fullRTA=False,
**fc_kw)
fcobj["bc_metrics"] = parser.parse_bc_metrics(**fc_kw)
fcobj["filter_metrics"] = parser.parse_filter_metrics(**fc_kw)
fcobj["samplesheet_csv"] = parser.parse_samplesheet_csv(
runinfo_csv=runinfo_csv, **fc_kw)
fcobj["run_info_yaml"] = parser.parse_run_info_yaml(**fc_kw)
qc_objects.append(fcobj)
else:
return qc_objects
qc_objects = self._parse_samplesheet(runinfo,
qc_objects,
fc_date,
fc_name,
fcdir,
as_yaml=as_yaml)
return qc_objects
def _collect_pre_casava_qc(self):
qc_objects = []
as_yaml = False
read_setup = None
fcdir = os.path.abspath(self.pargs.flowcell)
## Check modification time
if not modified_within_days(fcdir, self.pargs.mtime):
return qc_objects
# Get the fc_name, fc_date from RunInfo
parser = FlowcellRunMetricsParser(fcdir)
runinfo_xml = parser.parseRunInfo()
runparams = parser.parseRunParameters()
fc_date = runinfo_xml.get('Date',None)
fc_name = runinfo_xml.get('Flowcell',None)
fc_pos = runparams.get('FCPosition','')
runinfo_csv = os.path.join(os.path.join(self._meta.root_path, self.pargs.flowcell), "{}.csv".format(fc_name))
if not os.path.exists(runinfo_csv):
LOG.warn("No such file {}: trying fallback SampleSheet.csv".format(runinfo_csv))
runinfo_csv = os.path.join(os.path.join(self._meta.root_path, self.pargs.flowcell), "SampleSheet.csv")
runinfo = parser.parse_samplesheet_csv(runinfo_csv=runinfo_csv)
if len(runinfo) == 0:
runinfo_yaml = os.path.join(os.path.abspath(self.pargs.flowcell), "run_info.yaml")
as_yaml = True
try:
with open(runinfo_yaml) as fh:
runinfo = yaml.load(fh)
except IOError as e:
self.app.log.warn(str(e))
raise e
# Most of the code expects to have the flowcell position pre-pended to the flowcell id
fc_kw = dict(fc_date = fc_date, fc_name="{}{}".format(fc_pos,fc_name))
fcobj = FlowcellRunMetricsDocument(**fc_kw)
fcobj["RunInfo"] = runinfo_xml
fcobj["RunParameters"] = runparams
fcobj["illumina"] = parser.parse_illumina_metrics(fullRTA=False, **fc_kw)
fcobj["bc_metrics"] = parser.parse_bc_metrics(**fc_kw)
fcobj["filter_metrics"] = parser.parse_filter_metrics(**fc_kw)
fcobj["samplesheet_csv"] = runinfo
fcobj["run_info_yaml"] = parser.parse_run_info_yaml(**fc_kw)
read_setup = fcobj["RunInfo"].get('Reads',[])
fcobj["run_setup"] = self._run_setup(read_setup)
qc_objects.append(fcobj)
qc_objects = self._parse_samplesheet(runinfo, qc_objects, fc_date, "{}{}".format(fc_pos,fc_name), fcdir, as_yaml=as_yaml, setup=read_setup)
return qc_objects
def _collect_pre_casava_qc(self):
qc_objects = []
as_yaml = False
read_setup = None
fcdir = os.path.abspath(self.pargs.flowcell)
## Check modification time
if not modified_within_days(fcdir, self.pargs.mtime):
return qc_objects
# Get the fc_name, fc_date from RunInfo
parser = FlowcellRunMetricsParser(fcdir)
runinfo_xml = parser.parseRunInfo()
runparams = parser.parseRunParameters()
fc_date = runinfo_xml.get('Date',None)
fc_name = runinfo_xml.get('Flowcell',None)
fc_pos = runparams.get('FCPosition','')
runinfo_csv = os.path.join(os.path.join(self._meta.root_path, self.pargs.flowcell), "{}.csv".format(fc_name))
if not os.path.exists(runinfo_csv):
LOG.warn("No such file {}: trying fallback SampleSheet.csv".format(runinfo_csv))
runinfo_csv = os.path.join(os.path.join(self._meta.root_path, self.pargs.flowcell), "SampleSheet.csv")
runinfo = parser.parse_samplesheet_csv(runinfo_csv=runinfo_csv)
if len(runinfo) == 0:
runinfo_yaml = os.path.join(os.path.abspath(self.pargs.flowcell), "run_info.yaml")
as_yaml = True
try:
with open(runinfo_yaml) as fh:
runinfo = yaml.load(fh)
except IOError as e:
self.app.log.warn(str(e))
raise e
# Most of the code expects to have the flowcell position pre-pended to the flowcell id
fc_kw = dict(fc_date = fc_date, fc_name="{}{}".format(fc_pos,fc_name))
fcobj = FlowcellRunMetricsDocument(**fc_kw)
fcobj["RunInfo"] = runinfo_xml
fcobj["RunParameters"] = runparams
fcobj["illumina"] = parser.parse_illumina_metrics(fullRTA=False, **fc_kw)
fcobj["bc_metrics"] = parser.parse_bc_metrics(**fc_kw)
fcobj["filter_metrics"] = parser.parse_filter_metrics(**fc_kw)
fcobj["samplesheet_csv"] = runinfo
fcobj["run_info_yaml"] = parser.parse_run_info_yaml(**fc_kw)
read_setup = fcobj["RunInfo"].get('Reads',[])
fcobj["run_setup"] = self._run_setup(read_setup)
qc_objects.append(fcobj)
qc_objects = self._parse_samplesheet(runinfo, qc_objects, fc_date, "{}{}".format(fc_pos,fc_name), fcdir, as_yaml=as_yaml, setup=read_setup)
return qc_objects
def _collect_pre_casava_qc(self):
qc_objects = []
as_yaml = False
runinfo_csv = os.path.join(
os.path.join(self._meta.root_path, self.pargs.flowcell), "{}.csv".format(fc_id(self.pargs.flowcell))
)
if not os.path.exists(runinfo_csv):
LOG.warn("No such file {}: trying fallback SampleSheet.csv".format(runinfo_csv))
runinfo_csv = os.path.join(os.path.join(self._meta.root_path, self.pargs.flowcell), "SampleSheet.csv")
runinfo_yaml = os.path.join(os.path.abspath(self.pargs.flowcell), "run_info.yaml")
try:
if os.path.exists(runinfo_csv):
with open(runinfo_csv) as fh:
runinfo_reader = csv.reader(fh)
runinfo = [x for x in runinfo_reader]
else:
as_yaml = True
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) = fc_parts(self.pargs.flowcell)
## Check modification time
if modified_within_days(fcdir, self.pargs.mtime):
fc_kw = dict(fc_date=fc_date, fc_name=fc_name)
parser = FlowcellRunMetricsParser(fcdir)
fcobj = FlowcellRunMetricsDocument(**fc_kw)
fcobj["RunInfo"] = parser.parseRunInfo(**fc_kw)
fcobj["RunParameters"] = parser.parseRunParameters(**fc_kw)
fcobj["illumina"] = parser.parse_illumina_metrics(fullRTA=False, **fc_kw)
fcobj["bc_metrics"] = parser.parse_bc_metrics(**fc_kw)
fcobj["filter_metrics"] = parser.parse_filter_metrics(**fc_kw)
fcobj["samplesheet_csv"] = parser.parse_samplesheet_csv(runinfo_csv=runinfo_csv, **fc_kw)
fcobj["run_info_yaml"] = parser.parse_run_info_yaml(**fc_kw)
qc_objects.append(fcobj)
else:
return qc_objects
qc_objects = self._parse_samplesheet(runinfo, qc_objects, fc_date, fc_name, fcdir, as_yaml=as_yaml)
return qc_objects
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
def _collect_casava_qc(self):
qc_objects = []
read_setup = None
demux_stats = None
fcdir = os.path.join(os.path.abspath(self._meta.root_path), self.pargs.flowcell)
# Get the fc_name, fc_date from RunInfo
parser = FlowcellRunMetricsParser(fcdir)
runinfo_xml = parser.parseRunInfo()
runparams = parser.parseRunParameters()
fc_date = runinfo_xml.get('Date',None)
fc_name = runinfo_xml.get('Flowcell',None)
fc_pos = runparams.get('FCPosition','')
runinfo_csv = os.path.join(os.path.join(self._meta.root_path, self.pargs.flowcell), "{}.csv".format(fc_name))
if not os.path.exists(runinfo_csv):
LOG.warn("No such file {}: trying fallback SampleSheet.csv".format(runinfo_csv))
runinfo_csv = os.path.join(os.path.join(self._meta.root_path, self.pargs.flowcell), "SampleSheet.csv")
runinfo = parser.parse_samplesheet_csv(runinfo_csv=runinfo_csv)
if modified_within_days(fcdir, self.pargs.mtime):
# Most of the code expects to have the flowcell position pre-pended to the flowcell id
fc_kw = dict(fc_date = fc_date, fc_name="{}{}".format(fc_pos,fc_name))
fcobj = FlowcellRunMetricsDocument(**fc_kw)
fcobj["RunInfo"] = runinfo_xml
fcobj["RunParameters"] = runparams
fcobj["DemultiplexConfig"] = parser.parseDemultiplexConfig(**fc_kw)
fcobj["illumina"] = parser.parse_illumina_metrics(fullRTA=False, **fc_kw)
fcobj["bc_metrics"] = parser.parse_bc_metrics(**fc_kw)
fcobj["undemultiplexed_barcodes"] = parser.parse_undemultiplexed_barcode_metrics(**fc_kw)
fcobj["illumina"].update({"Demultiplex_Stats" : parser.parse_demultiplex_stats_htm(**fc_kw)})
fcobj["samplesheet_csv"] = runinfo
read_setup = fcobj["RunInfo"].get('Reads',[])
fcobj["run_setup"] = self._run_setup(read_setup)
demux_stats = fcobj["illumina"]["Demultiplex_Stats"]
qc_objects.append(fcobj)
qc_objects = self._parse_samplesheet(runinfo, qc_objects, fc_date, "{}{}".format(fc_pos,fc_name), fcdir, demultiplex_stats=demux_stats, setup=read_setup)
return qc_objects
def upload_analysis(self):
kw = vars(self.pargs)
if not kw.get("flowcell"):
kw["flowcell"] = "TOTAL"
# Get a connection to the analysis database
acon = AnalysisConnection(**kw)
# Traverse the folder hierarchy and determine paths to process
to_process = {}
for pdir in os.listdir(self._meta.root_path):
pdir = os.path.join(self._meta.root_path,pdir)
if not os.path.isdir(pdir):
continue
plist = []
for sdir in [d for d in os.listdir(pdir) if re.match(r'^P[0-9]{3,}_[0-9]+',d)]:
fdir = os.path.join(pdir,sdir,kw.get("flowcell"))
if not os.path.exists(fdir) or not modified_within_days(fdir, self.pargs.mtime):
continue
plist.append(fdir)
if plist:
to_process[os.path.basename(pdir)] = plist
# Collect the data from each folder
for project_name, sdirs in to_process.items():
self.log.info("Processing {}".format(project_name))
samples = {}
for sdir in sdirs:
config = glob.glob(os.path.join(sdir,"*-bcbb-config.yaml"))
if not config:
self.log.error("Could not find sample configuration file in {}. Skipping sample.".format(sdir))
continue
if len(config) > 1:
self.log.warn("Multiple sample configuration files found in {}. Will only use {}.".format(sdir,os.path.basename(config[0])))
# Parse the config file and get the flowcell, lane and index sequence that may be needed to parse
info = {}
sinfos = []
with open(config[0]) as fh:
info = yaml.load(fh)
fcdate = info.get("fc_date")
fcname = info.get("fc_name")
for laneinfo in info.get("details",[]):
for sampleinfo in laneinfo.get("multiplex",[laneinfo]):
linfo = laneinfo
linfo.update(sampleinfo)
name = linfo.get("name",linfo.get("description","unknown"))
m = re.match(r'(P[0-9_]{4,}[0-9])',name)
if m:
name = m.group(1)
sample_kw = {'flowcell': linfo.get("flowcell_id") if not fcname else fcname,
'date': fcdate,
'lane': linfo.get("lane"),
'barcode_name': name,
'sample_prj': linfo.get("sample_prj",project_name),
'barcode_id': linfo.get("barcode_id","1"),
'sequence': linfo.get("sequence","NoIndex")}
sinfos.append(sample_kw)
# Create a parser object and collect the metrics
parser = SampleRunMetricsParser(sdir)
sinfo = sinfos[0]
name = sinfo.get("barcode_name","unknown")
samples[name] = {}
samples[name]["bcbb_checkpoints"] = parser.parse_bcbb_checkpoints(**sinfo)
samples[name]["software_versions"] = parser.parse_software_versions(**sinfo)
samples[name]["project_summary"] = parser.parse_project_summary(**sinfo)
samples[name]["snpeff_genes"] = parser.parse_snpeff_genes(**sinfo)
for sinfo in sinfos:
picard = parser.read_picard_metrics(**sinfo)
if picard:
samples[name]["picard_metrics"] = picard
fq_scr = parser.parse_fastq_screen(**sinfo)
if fq_scr:
samples[name]["fastq_scr"] = fq_scr
fastqc = parser.read_fastqc_metrics(**sinfo)
if fastqc.get("stats"):
samples[name]["fastqc"] = fastqc
gteval = parser.parse_eval_metrics(**sinfo)
if gteval:
samples[name]["gatk_variant_eval"] = gteval
# Store the collected metrics in an analysis document
obj = AnalysisDocument(**{'project_name': project_name,
'name': project_name,
'samples': samples})
dry("Saving object {}".format(repr(obj)), acon.save(obj))
def _parse_samplesheet(self, runinfo, qc_objects, fc_date, fc_name, fcdir, as_yaml=False, demultiplex_stats=None):
"""Parse samplesheet information and populate sample run metrics object"""
if as_yaml:
for info in runinfo:
if not info.get("multiplex", None):
self.app.log.warn("No multiplex information for lane {}".format(info.get("lane")))
sample = {}
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(
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"),
)
parser = SampleRunMetricsParser(fcdir)
obj = SampleRunMetricsDocument(**sample_kw)
obj["picard_metrics"] = parser.read_picard_metrics(**sample_kw)
obj["fastq_scr"] = parser.parse_fastq_screen(**sample_kw)
obj["bc_count"] = parser.get_bc_count(**sample_kw)
obj["fastqc"] = parser.read_fastqc_metrics(**sample_kw)
qc_objects.append(obj)
else:
for sample in runinfo[1:]:
LOG.debug("Getting information for sample defined by {}".format(sample))
d = dict(zip(runinfo[0], sample))
if self.app.pargs.project_name and self.app.pargs.project_name != d["SampleProject"]:
continue
if self.app.pargs.sample and self.app.pargs.sample != d["SampleID"]:
continue
sampledir = os.path.join(
os.path.abspath(self._meta.production_root_path),
d["SampleProject"].replace("__", "."),
d["SampleID"],
)
if not os.path.exists(sampledir):
self.app.log.warn("No such sample directory: {}".format(sampledir))
continue
sample_fcdir = os.path.join(sampledir, fc_fullname(self.pargs.flowcell))
if not os.path.exists(sample_fcdir):
self.app.log.warn("No such sample flowcell directory: {}".format(sample_fcdir))
continue
if not modified_within_days(sample_fcdir, self.pargs.mtime):
continue
runinfo_yaml_file = os.path.join(sample_fcdir, "{}-bcbb-config.yaml".format(d["SampleID"]))
if not os.path.exists(runinfo_yaml_file):
self.app.log.warn("No such yaml file for sample: {}".format(runinfo_yaml_file))
raise IOError(2, "No such yaml file for sample: {}".format(runinfo_yaml_file), runinfo_yaml_file)
with open(runinfo_yaml_file) as fh:
runinfo_yaml = yaml.load(fh)
if not runinfo_yaml["details"][0].get("multiplex", None):
self.app.log.warn("No multiplex information for sample {}".format(d["SampleID"]))
continue
sample_kw = dict(
flowcell=fc_name,
date=fc_date,
lane=d["Lane"],
barcode_name=d["SampleID"],
sample_prj=d["SampleProject"].replace("__", "."),
barcode_id=runinfo_yaml["details"][0]["multiplex"][0]["barcode_id"],
sequence=runinfo_yaml["details"][0]["multiplex"][0]["sequence"],
)
parser = SampleRunMetricsParser(sample_fcdir)
obj = SampleRunMetricsDocument(**sample_kw)
obj["picard_metrics"] = parser.read_picard_metrics(**sample_kw)
obj["fastq_scr"] = parser.parse_fastq_screen(**sample_kw)
obj["bc_count"] = parser.get_bc_count(demultiplex_stats=demultiplex_stats, **sample_kw)
obj["fastqc"] = parser.read_fastqc_metrics(**sample_kw)
qc_objects.append(obj)
return qc_objects
def upload_analysis(self):
kw = vars(self.pargs)
if not kw.get("flowcell"):
kw["flowcell"] = "TOTAL"
# Get a connection to the analysis database
acon = AnalysisConnection(**kw)
# Traverse the folder hierarchy and determine paths to process
to_process = {}
for pdir in os.listdir(self._meta.root_path):
pdir = os.path.join(self._meta.root_path, pdir)
if not os.path.isdir(pdir):
continue
plist = []
for sdir in [
d for d in os.listdir(pdir)
if re.match(r'^P[0-9]{3,}_[0-9]+', d)
]:
fdir = os.path.join(pdir, sdir, kw.get("flowcell"))
if not os.path.exists(fdir) or not modified_within_days(
fdir, self.pargs.mtime):
continue
plist.append(fdir)
if plist:
to_process[os.path.basename(pdir)] = plist
# Collect the data from each folder
for project_name, sdirs in to_process.items():
self.log.info("Processing {}".format(project_name))
samples = {}
for sdir in sdirs:
config = glob.glob(os.path.join(sdir, "*-bcbb-config.yaml"))
if not config:
self.log.error(
"Could not find sample configuration file in {}. Skipping sample."
.format(sdir))
continue
if len(config) > 1:
self.log.warn(
"Multiple sample configuration files found in {}. Will only use {}."
.format(sdir, os.path.basename(config[0])))
# Parse the config file and get the flowcell, lane and index sequence that may be needed to parse
info = {}
sinfos = []
with open(config[0]) as fh:
info = yaml.load(fh)
fcdate = info.get("fc_date")
fcname = info.get("fc_name")
for laneinfo in info.get("details", []):
for sampleinfo in laneinfo.get("multiplex", [laneinfo]):
linfo = laneinfo
linfo.update(sampleinfo)
name = linfo.get("name",
linfo.get("description", "unknown"))
m = re.match(r'(P[0-9_]{4,}[0-9])', name)
if m:
name = m.group(1)
sample_kw = {
'flowcell':
linfo.get("flowcell_id") if not fcname else fcname,
'date':
fcdate,
'lane':
linfo.get("lane"),
'barcode_name':
name,
'sample_prj':
linfo.get("sample_prj", project_name),
'barcode_id':
linfo.get("barcode_id", "1"),
'sequence':
linfo.get("sequence", "NoIndex")
}
sinfos.append(sample_kw)
# Create a parser object and collect the metrics
parser = SampleRunMetricsParser(sdir)
sinfo = sinfos[0]
name = sinfo.get("barcode_name", "unknown")
samples[name] = {}
samples[name][
"bcbb_checkpoints"] = parser.parse_bcbb_checkpoints(
**sinfo)
samples[name][
"software_versions"] = parser.parse_software_versions(
**sinfo)
samples[name][
"project_summary"] = parser.parse_project_summary(**sinfo)
samples[name]["snpeff_genes"] = parser.parse_snpeff_genes(
**sinfo)
for sinfo in sinfos:
picard = parser.read_picard_metrics(**sinfo)
if picard:
samples[name]["picard_metrics"] = picard
fq_scr = parser.parse_fastq_screen(**sinfo)
if fq_scr:
samples[name]["fastq_scr"] = fq_scr
fastqc = parser.read_fastqc_metrics(**sinfo)
if fastqc.get("stats"):
samples[name]["fastqc"] = fastqc
gteval = parser.parse_eval_metrics(**sinfo)
if gteval:
samples[name]["gatk_variant_eval"] = gteval
# Store the collected metrics in an analysis document
obj = AnalysisDocument(
**{
'project_name': project_name,
'name': project_name,
'samples': samples
})
dry("Saving object {}".format(repr(obj)), acon.save(obj))