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-0.3.29.tar.gz (75.4 kB view details)

Uploaded Source

Built Distribution

edc_lab-0.3.29-py3-none-any.whl (119.5 kB view details)

Uploaded Python 3

File details

Details for the file edc-lab-0.3.29.tar.gz.

File metadata

  • Download URL: edc-lab-0.3.29.tar.gz
  • Upload date:
  • Size: 75.4 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/4.0.1 CPython/3.9.9

File hashes

Hashes for edc-lab-0.3.29.tar.gz
Algorithm Hash digest
SHA256 4afbe5049b0d38ead1b1f3a8bf5becdf1b39d9b1e2707f8a17f3fef3d71dc87b
MD5 a9e1cd7f7f307f346cb1ad0008ba508b
BLAKE2b-256 801c4a319ecd06e0719bbec3a990d7b4f143281fbedc1810722d6f55afd3d24a

See more details on using hashes here.

File details

Details for the file edc_lab-0.3.29-py3-none-any.whl.

File metadata

  • Download URL: edc_lab-0.3.29-py3-none-any.whl
  • Upload date:
  • Size: 119.5 kB
  • Tags: Python 3
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/4.0.1 CPython/3.9.9

File hashes

Hashes for edc_lab-0.3.29-py3-none-any.whl
Algorithm Hash digest
SHA256 a5f47a62049dad795fa46d98ce427fa9b9bedb8d2027e8b1301645398c48805b
MD5 fbda8105a4fae0ab201dc6c03ac98e0c
BLAKE2b-256 5ceadd69e94e31d85d0c47561bc69d72b3da3deae3c0919e1ae830ae1bdb22d6

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