def createMSRuns():
data = request.json
msRuns = data.get('samples')
responseDTO = BulkCreateResponseDTO()
for i in msRuns:
msReadySample = msReadySamplesDAO.getMSReadySampleByName(
i['msReadySampleName'])
sop = "NA"
if(msReadySample != None):
if i['runMode'] == "DIA":
entry = artefactDAO.getArtefactById(i['SOPDIA'])
if(entry != None):
sop = entry['name']
elif i['runMode'] == "DDA":
entry = artefactDAO.getArtefactById(i['SOPDDA'])
if(entry != None):
sop = entry['name']
description = ""
if i['description'] != None:
description = i['description']
existingMSRun = MSRunDAO.getMsRunByName(i['name'])
if(existingMSRun != None):
MSRunDAO.updateMSRun(
existingMSRun['id'], msReadySample['id'], msReadySample['clinicalSamples'], i['instrumentId'], sop,
description, i['instrumentMethod'], i['processingPerson'])
responseDTO.appendOverwritten(i['name'])
else:
new_msrun = {
"clinicalSamples": msReadySample['clinicalSamples'],
"msReadySampleId": msReadySample['id'],
"name": i['name'],
"projectId": i['projectId'],
"protocolId": i['runMode'],
"instrumentId": i['instrumentId'],
"sopFileName": sop,
"instrumentMethod": i['instrumentMethod'],
"updatedDate": datetime.datetime.now(),
"createdDate": datetime.datetime.now(),
"workflowTag": "Library Generation",
"description": description,
"processingPerson": i['processingPerson'],
}
new_run = MSRunDAO.createMsRun(new_msrun)
responseDTO.appendCreateSuccess(i['name'])
else:
responseDTO.appendCreateFail(i['name'])
return responseDTO.toJson(), status.HTTP_200_OK
def insertSWATHAnalysis(swa, projectId):
spl = spectralLibraryDAO.getAllLibrariesForProject(projectId)
ms_runs = MSRunDAO.getAllMSRunsByProjectId(projectId)
ms_run_ids = []
involved_clinical_samples = []
for ms_run in ms_runs:
if (re.search("^sgoetze_A1902_-*", ms_run['name'])):
ms_run_ids.append(ms_run['id'])
for j in ms_run['clinicalSamples']:
if j not in involved_clinical_samples:
involved_clinical_samples.append(j)
new_swa = {
"swathId": 1,
"clinicalSamples": involved_clinical_samples,
"msRunIds": ms_run_ids,
"name": "PHRT_001_005_CPAC_SWATH",
"spectralLibraryId": spl[0]['id'],
"projectId": projectId,
"protocolId": "1",
"protocolName": swa['protocolId'],
"sopFileName": "PHRT_Data_Analysis_SOP",
"proteinMatrixFileName": "PHRT_005_Protein_Matrix.tsv",
"updatedDate": datetime.datetime.now(),
"createdDate": datetime.datetime.now(),
"workflowTag": "SWATHAnalysis",
"description": "Generated from Excel archive"
}
print(swathAnalysisDAO.createSWATHAnalysis(new_swa))
def insertSpectralLibrary(spl, projectId):
ms_runs = MSRunDAO.getAllMSRunsByProjectId(projectId)
ms_run_ids = []
involved_clinical_samples = []
for ms_run in ms_runs:
if (re.search("^sgoetze_C1902-*", ms_run['name'])):
ms_run_ids.append(ms_run['id'])
for j in ms_run['clinicalSamples']:
if j not in involved_clinical_samples:
involved_clinical_samples.append(j)
new_spl = {
"libId": 1,
"clinicalSamples": involved_clinical_samples,
"msRunIds": ms_run_ids,
"name": "PHRT_001_005_CPAC_Lib",
"projectId": projectId,
"protocolId": "1",
"protocolName": spl['protocolId'],
"updatedDate": datetime.datetime.now(),
"createdDate": datetime.datetime.now(),
"specLibFilename": "PHRT_005_Spec_Lib.tsv",
"sopFileName": "PHRT_Data_Analysis_SOP",
"workflowTag": "Library Generation",
"description": "Generated from Excel archive",
"proteinDatabaseOrganism": spl['protein_database']['organism'],
"proteinDatabaseVersion": spl['protein_database']['version']
}
print(spectralLibraryDAO.createSpectralLibrary(new_spl))
def insertLibGenMSRuns(projectId):
frac_samples = intermediateSampleDAO.getIntermediateSamplesByProjectAndProtocolId(
"fractionation_preparation", projectId)
name_counter = 25
run_counter = 7
for f in frac_samples:
if (re.search("^IS_MMA_library_batch-1_mix-*", f['name'])):
msr_sample = msReadySamplesDAO.getMsReadySampleByIntermediateSampleId(
f['id'])
if (len(msr_sample) > 0):
msr = msr_sample[0]
new_msrun = {
"runId": run_counter,
"clinicalSamples": msr['clinicalSamples'],
"msReadySampleId": msr['id'],
"name": "PHRT_5_sgoetze_C1902_0" + str(name_counter),
"projectId": projectId,
"protocolId": "DDA_protocol",
"instrumentId": "MS:1002877",
"instrumentMethod": "Xcalibur methods TP",
"sopFileName": "PHRT_Mass_Spectrometry_SOP",
"updatedDate": datetime.datetime.now(),
"createdDate": datetime.datetime.now(),
"workflowTag": "Library Generation",
"description": "Generated from Excel archive",
"processingPerson": "System",
}
name_counter = name_counter + 1
run_counter = run_counter + 1
print(MSRunDAO.createMsRun(new_msrun))
def insertMSRuns(msruns, projectId):
for i in msruns:
x = re.search("^sgoetze_A1*", i['name'])
if x:
samples = []
sample_c = clinicalSampleDAO.getClinicalSampleByClinicalSampleCode(
str(int(i['sample_ref']['sampleIdRef'])))
if sample_c != None:
msrs = msReadySamplesDAO.getMsReadySamplesByClinicalSample(
sample_c['id'])
for msr in msrs:
if len(msr['clinicalSamples']) == 1:
new_msrun = {
"runId": i['id'],
"clinicalSamples": msr['clinicalSamples'],
"msReadySampleId": msr['id'],
"name": i['name'],
"projectId": projectId,
"protocolId": i['protocolId'],
"instrumentId": i['instrumentId'],
"sopFileName": "PHRT_Mass_Spectrometry_SOP",
"instrumentMethod": "Xcalibur methods TP",
"updatedDate": datetime.datetime.now(),
"createdDate": datetime.datetime.now(),
"workflowTag": "Sample Preparation",
"description": "Generated from Excel archive",
"processingPerson": "System",
}
print(MSRunDAO.createMsRun(new_msrun))
def deleteRun():
id = request.args.get('id')
sts = MSRunDAO.deleteMSrun(id)
if(sts == 0):
return 'MS Run with id does not exist.', status.HTTP_404_NOT_FOUND
else:
return '', status.HTTP_200_OK
def getAllSpectralLibraries():
projectId = request.args.get('projectId')
if (projectDAO.getProjectById(projectId)):
spec_libs = spectralLibraryDAO.getAllLibrariesForProject(projectId)
for s in spec_libs:
augmentedClinicalSamples = clinicalSampleDAO.augmentClinicalSampleNames(
s['clinicalSamples'])
augmentedMSRuns = MSRunDAO.augmentMSRunNames(s['msRunIds'])
s['clinicalSamples'] = augmentedClinicalSamples
s['msRunIds'] = augmentedMSRuns
return jsonify(spec_libs), status.HTTP_200_OK
else:
return 'Project with id does not exist.', status.HTTP_404_NOT_FOUND
def getMSRunById():
id = ObjectId(request.args.get('id'))
msrun = MSRunDAO.getMsRun(id)
if(msrun):
msrun = msrun.dump()
augmentedClinicalSamples = clinicalSampleDAO.augmentClinicalSampleNames(
msrun['clinicalSamples'])
msReadySampleName = msReadySamplesDAO.getMSReadySampleName(
msrun['msReadySampleId'])
msrun['clinicalSamples'] = augmentedClinicalSamples
msrun['msReadySampleName'] = msReadySampleName
return jsonify(msrun), status.HTTP_200_OK
else:
return 'MS Run with id does not exist.', status.HTTP_404_NOT_FOUND
def getMSRunsByProjectId():
projectId = request.args.get('projectId')
if (projectDAO.getProjectById(projectId)):
msruns = MSRunDAO.getAllMSRunsByProjectId(projectId)
for msrun in msruns:
augmentedClinicalSamples = clinicalSampleDAO.augmentClinicalSampleNames(
msrun['clinicalSamples'])
msReadySampleName = msReadySamplesDAO.getMSReadySampleName(
msrun['msReadySampleId'])
msrun['clinicalSamples'] = augmentedClinicalSamples
msrun['msReadySampleName'] = msReadySampleName
return jsonify(msruns), status.HTTP_200_OK
else:
return 'Project with id does not exist.', status.HTTP_404_NOT_FOUND
def getAllSwathAnalysis():
projectId = request.args.get('projectId')
if (projectDAO.getProjectById(projectId)):
swath_analysis = swathAnalysisDAO.getSWATHByProject(projectId)
for s in swath_analysis:
augmentedClinicalSamples = clinicalSampleDAO.augmentClinicalSampleNames(
s['clinicalSamples'])
augmentedMSRuns = MSRunDAO.augmentMSRunNames(
s['msRunIds'])
s['clinicalSamples'] = augmentedClinicalSamples
s['msRunIds'] = augmentedMSRuns
return jsonify(swath_analysis), status.HTTP_200_OK
else:
return 'Project with id does not exist.', status.HTTP_404_NOT_FOUND
def getMsRunsByClinicalSampleId():
clinicalSampleId = ObjectId(request.args.get('id'))
if clinicalSampleDAO.getClinicalSampleById(clinicalSampleId):
msruns = MSRunDAO.getMsRunsByClinicalSampleId(
clinicalSampleId)
for ms_run in msruns:
augmentedClinicalSamples = clinicalSampleDAO.augmentClinicalSampleNames(
ms_run['clinicalSamples'])
msReadySampleName = msReadySamplesDAO.getMSReadySampleName(
ms_run['msReadySampleId'])
ms_run['clinicalSamples'] = augmentedClinicalSamples
ms_run['msReadySampleName'] = msReadySampleName
return jsonify(msruns), status.HTTP_200_OK
else:
return 'Clinical Sample with id does not exist.', status.HTTP_404_NOT_FOUND
def setMsPrepEntries(sampleJourney, ins):
msrs = msReadySamplesDAO.getMsReadySampleByIntermediateSampleId(ins['id'])
if len(msrs) > 0:
msr = msrs[0]
msr_name = msr['name']
sampleJourney.appendMsReadySampleName(msr_name)
sampleJourney.appendLink(ins['name'], msr_name, "")
msruns = MSRunDAO.getMsRunsByMSReadySampleId(msr['id'])
for r in msruns:
msrun_name = r['name']
msrun_sop = r['sopFileName']
sampleJourney.appendMsRunName(msrun_name)
sampleJourney.appendLink(msr_name, msrun_name, msrun_sop)
setComputationalEntries(sampleJourney, r)
return sampleJourney
def generateMassSpecCluster(g, msr):
msrun = MSRunDAO.getMsRunsByMSREadySampleId(msr['id'])[0]
if len(msrun) > 0:
msrun_name = msrun['name']
msrun_sop = msrun['sopFileName']
print(msrun_name)
with g.subgraph(name='cluster_2') as e:
e.attr(style='filled',
color='darkseagreen',
minlen='8,5',
fixedsize='True')
e.node_attr.update(style='filled', color='white', shape='box')
e.node(msrun_name)
e.attr(label='MASS SPEC')
g.edge(msr['name'],
msrun_name,
label=msrun_sop,
color='darkgrey',
fontsize='10')
generateComputationalCluster(g, msrun['id'], msrun_name)
def insertMelanomaJourney(projectId):
new_sample = {
"clinicalSampleCode": "FDSG23",
"name": "PHRT_006_FDSG23_CPAC",
"sampleCounter": 1,
"projectId": projectId,
"processingPerson": "System",
"description": "Mock sample",
"workflowTag": "Sample Preparation",
"updatedDate": datetime.datetime.now(),
"createdDate": datetime.datetime.now()
}
second_sample = {
"clinicalSampleCode": "RTYD12",
"name": "PHRT_006_RTYD12_CPAC",
"sampleCounter": 2,
"projectId": projectId,
"processingPerson": "System",
"description": "Mock sample",
"workflowTag": "Sample Preparation",
"updatedDate": datetime.datetime.now(),
"createdDate": datetime.datetime.now()
}
cs1 = clinicalSampleDAO.createClinicalSample(new_sample)
cs2 = clinicalSampleDAO.createClinicalSample(second_sample)
is_sample1 = {
"name": "IS_" + str(cs1['name']) + "_1",
"projectId": projectId,
"clinicalSamples": [cs1['id']],
"workflowTag": "Sample Preparation",
"protocolName": "fractionation_preparation",
"sopFileName": "PHRT_Sample_Preparation_SOP",
"description": "Mock sample",
"processingPerson": "System",
"updatedDate": datetime.datetime.now(),
"createdDate": datetime.datetime.now()
}
is_sample2 = {
"name": "IS_" + str(cs1['name']) + "_2",
"projectId": projectId,
"clinicalSamples": [cs1['id']],
"workflowTag": "Sample Preparation",
"protocolName": "fractionation_preparation",
"sopFileName": "PHRT_Sample_Preparation_SOP",
"description": "Mock sample",
"processingPerson": "System",
"updatedDate": datetime.datetime.now(),
"createdDate": datetime.datetime.now()
}
is1 = intermediateSampleDAO.createIntermediateSample(is_sample1)
is2 = intermediateSampleDAO.createIntermediateSample(is_sample2)
new_msr1 = {
"name": "MSR_" + is1['name'],
"projectId": projectId,
"clinicalSamples": is1['clinicalSamples'],
"intermediateSampleId": is1['id'],
"workflowTag": "Sample Preparation",
"description": "Mock samples",
"processingPerson": "System",
"updatedDate": datetime.datetime.now(),
"createdDate": datetime.datetime.now()
}
new_msr2 = {
"name": "MSR_" + is2['name'],
"projectId": projectId,
"clinicalSamples": is2['clinicalSamples'],
"intermediateSampleId": is2['id'],
"workflowTag": "Sample Preparation",
"description": "Mock samples",
"processingPerson": "System",
"updatedDate": datetime.datetime.now(),
"createdDate": datetime.datetime.now()
}
msr1 = msReadySamplesDAO.createMSReadySample(new_msr1)
msr2 = msReadySamplesDAO.createMSReadySample(new_msr2)
new_msrun1 = {
"runId": 1,
"clinicalSamples": msr1['clinicalSamples'],
"msReadySampleId": msr1['id'],
"name": "PHRT_6_salbert_A1902_012",
"projectId": projectId,
"protocolId": "DIA",
"instrumentId": "MS:1002523",
"instrumentMethod": "Xcalibur methods TP",
"sopFileName": "PHRT_Mass_Spectrometry_SOP",
"updatedDate": datetime.datetime.now(),
"createdDate": datetime.datetime.now(),
"workflowTag": "Sample Preparation",
"description": "Mock run",
"processingPerson": "System"
}
new_msrun2 = {
"runId": 2,
"clinicalSamples": msr2['clinicalSamples'],
"msReadySampleId": msr2['id'],
"name": "PHRT_6_salbert_A1902_045",
"projectId": projectId,
"protocolId": "DIA",
"instrumentId": "MS:1002523",
"sopFileName": "PHRT_Mass_Spectrometry_SOP",
"updatedDate": datetime.datetime.now(),
"instrumentMethod": "Xcalibur methods TP",
"createdDate": datetime.datetime.now(),
"workflowTag": "Sample Preparation",
"description": "Mock run",
"processingPerson": "System"
}
run1 = MSRunDAO.createMsRun(new_msrun1)
run2 = MSRunDAO.createMsRun(new_msrun2)
new_spl = {
"libId": 1,
"clinicalSamples": is1['clinicalSamples'],
"msRunIds": [run1['id'], run2['id']],
"name": "PHRT_001_006_CPAC_Lib",
"projectId": projectId,
"protocolId": "1",
"protocolName": "PHRT_Data_Analysis_SOP",
"updatedDate": datetime.datetime.now(),
"createdDate": datetime.datetime.now(),
"specLibFilename": "PHRT_005_Spec_Lib.tsv",
"sopFileName": "PHRT_Data_Analysis_SOP",
"workflowTag": "Library Generation",
"description": "Mock lib",
"proteinDatabaseOrganism": "UP000005640",
"proteinDatabaseVersion": "200812"
}
spl = spectralLibraryDAO.createSpectralLibrary(new_spl)
new_swa = {
"swathId": 1,
"clinicalSamples": is1['clinicalSamples'],
"msRunIds": [run1['id']],
"name": "PHRT_001_006_CPAC_SWATH",
"spectralLibraryId": spl['id'],
"projectId": projectId,
"protocolId": "1",
"protocolName": "PHRT_Data_Analysis_SOP",
"sopFileName": "PHRT_Data_Analysis_SOP",
"proteinMatrixFileName": "PHRT_006_Protein_Matrix.tsv",
"updatedDate": datetime.datetime.now(),
"createdDate": datetime.datetime.now(),
"workflowTag": "SWATHAnalysis",
"description": "Mock swath"
}
print(swathAnalysisDAO.createSWATHAnalysis(new_swa))