def samplesheet_pool_samples(lims, process_id, output_file):
"""Create manual pipetting samplesheet for pooling samples."""
process = Process(lims, id=process_id)
# print header
output_file.write('Sample\tContainer\tWell\tPool\n')
# Get all input artifact and store per container
input_containers = {}
for input_artifact in process.all_inputs(resolve=True):
container = input_artifact.location[0].name
well = ''.join(input_artifact.location[1].split(':'))
if container not in input_containers:
input_containers[container] = {}
input_containers[container][well] = input_artifact
# print pool scheme per input artifact
# sort on container and well
for input_container in sorted(input_containers.keys()):
input_artifacts = input_containers[input_container]
for well in clarity_epp.export.utils.sort_96_well_plate(
input_artifacts.keys()):
output_file.write('{sample}\t{container}\t{well}\t{pool}\n'.format(
sample=input_artifacts[well].name,
container=input_artifacts[well].location[0].name,
well=well,
pool=process.outputs_per_input(input_artifacts[well].id,
Analyte=True)[0].name))
def samplesheet_normalization(lims, process_id, output_file):
"""Create manual pipetting samplesheet for normalizing (MIP) samples."""
output_file.write(
'Sample\tConcentration (ng/ul)\tVolume sample (ul)\tVolume water (ul)\tOutput (ng)\tIndampen\n'
)
process = Process(lims, id=process_id)
# Find all QC process types
qc_process_types = clarity_epp.export.utils.get_process_types(
lims, ['Dx Qubit QC', 'Dx Tecan Spark 10M QC'])
for input_artifact in process.all_inputs(resolve=True):
artifact = process.outputs_per_input(
input_artifact.id,
Analyte=True)[0] # assume one artifact per input
sample = input_artifact.samples[
0] # asume one sample per input artifact
# Find last qc process for artifact
qc_process = sorted(
lims.get_processes(type=qc_process_types,
inputartifactlimsid=input_artifact.id),
key=lambda process: int(process.id.split('-')[-1]))[-1]
# Find concentration measurement
for qc_artifact in qc_process.outputs_per_input(input_artifact.id):
if qc_artifact.name.split(' ')[0] == artifact.name:
concentration = float(
qc_artifact.udf['Dx Concentratie fluorescentie (ng/ul)'])
final_volume = float(artifact.udf['Dx Eindvolume (ul)'])
input_ng = float(artifact.udf['Dx Input (ng)'])
if 'Dx pipetteervolume (ul)' in artifact.udf:
input_ng = concentration * float(
artifact.udf['Dx pipetteervolume (ul)'])
sample_volume = input_ng / concentration
water_volume = final_volume - sample_volume
evaporate = 'N'
if sample_volume < 0.5:
sample_volume = 0.5
water_volume = final_volume - sample_volume
elif sample_volume > final_volume:
evaporate = 'J'
water_volume = 0
output_file.write(
'{sample}\t{concentration:.1f}\t{sample_volume:.1f}\t{water_volume:.1f}\t{output:.1f}\t{evaporate}\n'
.format(sample=sample.name,
concentration=concentration,
sample_volume=sample_volume,
water_volume=water_volume,
output=input_ng,
evaporate=evaporate))
def samplesheet_dilute(lims, process_id, output_file):
"""Create Caliper samplesheet for diluting samples."""
output_file.write(
'Monsternummer\tPlate_Id_input\tWell\tPlate_Id_output\tPipetteervolume DNA (ul)\tPipetteervolume H2O (ul)\n'
)
process = Process(lims, id=process_id)
output = {} # save output data to dict, to be able to sort on well.
nM_pool = process.udf['Dx Pool verdunning (nM)']
output_ul = process.udf['Eindvolume (ul)']
for input_artifact in process.all_inputs():
output_artifact = process.outputs_per_input(input_artifact.id,
Analyte=True)[0]
# Get QC stats
size = float(input_artifact.udf['Dx Fragmentlengte (bp)'])
concentration = float(
input_artifact.udf['Dx Concentratie fluorescentie (ng/ul)'])
# Calculate dilution
nM_dna = (concentration * 1000 * (1 / 660.0) * (1 / size)) * 1000
ul_sample = (nM_pool / nM_dna) * output_ul
ul_water = output_ul - ul_sample
# Store output lines by well
well = ''.join(input_artifact.location[1].split(':'))
output[
well] = '{name}\t{plate_id_input}\t{well}\t{plate_id_output}\t{volume_dna:.1f}\t{volume_water:.1f}\n'.format(
name=input_artifact.name,
plate_id_input=input_artifact.location[0].name,
well=well,
plate_id_output=output_artifact.location[0].name,
volume_dna=ul_sample,
volume_water=ul_water)
wells = []
for col in range(1, 13):
wells.extend([
'{}{}'.format(row, str(col)) for row in string.ascii_uppercase[:8]
])
for well in wells:
if well in output:
output_file.write(output[well])
else:
output_file.write(
'Leeg\tNone\t{well}\t{plate_id_output}\t0\t0\n'.format(
well=well,
plate_id_output=output_artifact.location[0].name,
))
