alignment.align(referenceName,
readsFile,
bidirectional=False,
mark_duplicates=False,
realign=False,
skip_sorting=True,
aligner_opts_extra="",
logfile=os.path.join(
RECALIBRATION_RESULTS,
"alignmentQC_out.txt"),
output_dir=RECALIBRATION_RESULTS,
output_basename="samplelib")
# Generate both hpTable and hpModel.
flow_space_recal.calibrate(RECALIBRATION_RESULTS,
sample_map_path,
env['recalibArgs'], chipflow)
# merge step, calibrate collects the training data saved for each barcode,
# calculate and generate hpTable and hpModel files for the whole dataset
flow_space_recal.HPaggregation(
os.path.join(env['BASECALLER_RESULTS'], "recalibration"),
env['recalibArgs'])
hptable = os.path.join(env['BASECALLER_RESULTS'],
"recalibration", "hpTable.txt")
printtime("hptable: %s" % hptable)
additional_basecallerArgs = " --calibration-file " + hptable
additional_basecallerArgs += " --phase-estimation-file " + os.path.join(
env['BASECALLER_RESULTS'], "recalibration",
alignment.align(
referenceName,
readsFile,
bidirectional=False,
mark_duplicates=False,
realign=False,
skip_sorting=True,
aligner_opts_extra="",
logfile=os.path.join(RECALIBRATION_RESULTS,"alignmentQC_out.txt"),
output_dir=RECALIBRATION_RESULTS,
output_basename="samplelib")
# Generate both hpTable and hpModel.
flow_space_recal.calibrate(
RECALIBRATION_RESULTS,
sample_map_path,
env['recalibArgs'],
chipflow)
# merge step, calibrate collects the training data saved for each barcode,
# calculate and generate hpTable and hpModel files for the whole dataset
flow_space_recal.HPaggregation(
os.path.join(env['BASECALLER_RESULTS'],"recalibration"),
env['recalibArgs'])
hptable = os.path.join(env['BASECALLER_RESULTS'], "recalibration", "hpTable.txt")
printtime("hptable: %s" % hptable)
additional_basecallerArgs = " --calibration-file " + hptable
additional_basecallerArgs += " --phase-estimation-file " + os.path.join(env['BASECALLER_RESULTS'], "recalibration", "BaseCaller.json")
additional_basecallerArgs += " --model-file " + os.path.join(env['BASECALLER_RESULTS'], "recalibration", "hpModel.txt")
os.path.join(env['BASECALLER_RESULTS'],
"recalibration", 'BaseCaller.json'), 'r')
chipflow = json.load(c)
c.close()
except:
traceback.print_exc()
raise
# Call Calibration module to process training BAM files if we have some
if len(calibration_input_bams) > 0:
calibration_args = env['recalibArgs']
if calibration_mode == "blind_recal":
calibration_args += " --blind-fit on --load-unmapped on"
flow_space_recal.calibrate(env['BASECALLER_RESULTS'],
calibration_input_bams,
calibration_args, chipflow)
additional_basecallerArgs += " --calibration-json " + \
os.path.join(env['BASECALLER_RESULTS'], "Calibration.json")
printtime("Finished Recalibration")
add_status("Recalibration", 0)
except:
traceback.print_exc()
add_status("Recalibration", 1)
printtime("ERROR: Recalibration failed")
sys.exit(1)
# ---------------------------------------------------------------------------
# Finished with Calibration workflow - on to base calling
do_sorting=False,
do_mark_duplicates=False,
do_indexing=False,
output_dir=RECALIBRATION_RESULTS,
output_basename=dataset['file_prefix'])
# Do not call Calibration if we did not generate any aligned input BAMs but gracefully continue
additional_basecallerArgs += " --phase-estimation-file " + os.path.join(env['BASECALLER_RESULTS'], "recalibration", "BaseCaller.json")
if env['doBaseRecal'] == "panel_recal":
additional_basecallerArgs += " --calibration-panel /opt/ion/config/datasets_calibration.json"
if len(calibration_input_bams)>0:
# Call Calibration module to process aligned training BAM files
flow_space_recal.calibrate(
env['BASECALLER_RESULTS'],
calibration_input_bams,
env['recalibArgs'],
chipflow)
additional_basecallerArgs += " --calibration-json " + os.path.join(env['BASECALLER_RESULTS'],"Calibration.json")
printtime("Finished Recalibration")
add_status("Recalibration", 0)
except:
traceback.print_exc()
add_status("Recalibration", 1)
printtime ("ERROR: Recalibration failed")
sys.exit(1)
else:
printtime("DEBUG: Flow Space Recalibration is disabled")