Skip to main content

LIMS/lab classes for clinicedc/edc projects

Project description

pypi actions codecov downloads

edc-lab

Add to settings:

INSTALLED_APPS = [
    ...
    'edc_lab.apps.AppConfig',
    ...
]

Configuration

Create aliquot types:

# aliquot types
wb = AliquotType(name='whole_blood', alpha_code='WB', numeric_code='02')
bc = AliquotType(name='buffy_coat', alpha_code='BC', numeric_code='16')
pl = AliquotType(name='plasma', alpha_code='PL', numeric_code='32')

Add possible derivatives to an aliquot type:

# in this case, plasma and buffy coat are possible derivatives
wb.add_derivatives(pl, bc)

Set up a processing profile:

viral_load = ProcessingProfile(
    name='viral_load', aliquot_type=wb)
process_bc = Process(aliquot_type=bc, aliquot_count=4)
process_pl = Process(aliquot_type=pl, aliquot_count=2)
viral_load.add_processes(process_bc, process_pl)

Create a``panel`` that uses the processing profile:

panel = RequisitionPanel(
    name='Viral Load',
    processing_profile=viral_load)

Add the panel (and others) to a lab profile:

lab_profile = LabProfile(
    name='lab_profile',
    requisition_model='edc_lab.subjectrequisition')
lab_profile.add_panel(panel)

Register the lab_profile with the site global:

site_labs.register(lab_profile)

Usage

Create a requisition model instance:

requisition = SubjectRequisition.objects.create(
    subject_visit=self.subject_visit,
    panel_name=self.panel.name,
    is_drawn=YES)

Pass the requisition to Specimen

specimen = Specimen(requisition=requisition)

Process:

specimen.process()

Aliquots have been created according to the configured processing profile:

>>> specimen.primary_aliquot.identifier
'99900GV63F00000201'

>>> for aliquot in specimen.aliquots.order_by('count'):
       print(aliquot.aliquot_identifier)
'99900GV63F00000201'
'99900GV63F02013202'
'99900GV63F02013203'
'99900GV63F02011604'
'99900GV63F02011605'
'99900GV63F02011606'
'99900GV63F02011607'

Project details


Release history Release notifications | RSS feed

Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

edc-lab-0.3.56.tar.gz (82.1 kB view details)

Uploaded Source

Built Distribution

edc_lab-0.3.56-py3-none-any.whl (132.4 kB view details)

Uploaded Python 3

File details

Details for the file edc-lab-0.3.56.tar.gz.

File metadata

  • Download URL: edc-lab-0.3.56.tar.gz
  • Upload date:
  • Size: 82.1 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/4.0.2 CPython/3.11.6

File hashes

Hashes for edc-lab-0.3.56.tar.gz
Algorithm Hash digest
SHA256 a1ed7f8eb6eea88ce93e11edf36b70b716d3594a4aff496e4b717f2995267b43
MD5 f2338e807472f97f406ffc57f5aa5368
BLAKE2b-256 aa6a02448c972660af71bcba5d9ede5a6d81a9ebc534c6cef0d49b4bc59ab183

See more details on using hashes here.

File details

Details for the file edc_lab-0.3.56-py3-none-any.whl.

File metadata

  • Download URL: edc_lab-0.3.56-py3-none-any.whl
  • Upload date:
  • Size: 132.4 kB
  • Tags: Python 3
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/4.0.2 CPython/3.11.6

File hashes

Hashes for edc_lab-0.3.56-py3-none-any.whl
Algorithm Hash digest
SHA256 1be5cc152222ec546a9f909e99ca1c246826571070f0875852423e521c2cda6f
MD5 b882e43ecf042baf529da076cac0c35f
BLAKE2b-256 e2569c7ae630c6b4495c0c6b284b64dc8f5d9ef86e7d66ad21d2b42a851a804d

See more details on using hashes here.

Supported by

AWS AWS Cloud computing and Security Sponsor Datadog Datadog Monitoring Fastly Fastly CDN Google Google Download Analytics Microsoft Microsoft PSF Sponsor Pingdom Pingdom Monitoring Sentry Sentry Error logging StatusPage StatusPage Status page