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-0.3.35.tar.gz (76.2 kB view details)

Uploaded Source

Built Distribution

edc_lab-0.3.35-py3-none-any.whl (120.8 kB view details)

Uploaded Python 3

File details

Details for the file edc-lab-0.3.35.tar.gz.

File metadata

  • Download URL: edc-lab-0.3.35.tar.gz
  • Upload date:
  • Size: 76.2 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/4.0.1 CPython/3.9.9

File hashes

Hashes for edc-lab-0.3.35.tar.gz
Algorithm Hash digest
SHA256 63028b4beadc59e2029e2881c8d6ff65c37635c15b5946211a1a7ddb46e97afb
MD5 6451bd607c1cf03f518493c5e53cd67f
BLAKE2b-256 678dc443aeecd7af533d9526ca97d8cc6f89f9f761bb4491d56181bd37e51858

See more details on using hashes here.

File details

Details for the file edc_lab-0.3.35-py3-none-any.whl.

File metadata

  • Download URL: edc_lab-0.3.35-py3-none-any.whl
  • Upload date:
  • Size: 120.8 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-0.3.35-py3-none-any.whl
Algorithm Hash digest
SHA256 84d08aa9cb323543b506d61768700ce180b698c4afd793fc551bef358d266bc9
MD5 96c8185c129b449f52d92483ae10b001
BLAKE2b-256 2692728f04f6cff5add4db1daff0858f91ce0419b544558ede7f3b527dd91c23

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