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-0.3.42.tar.gz (78.0 kB view details)

Uploaded Source

Built Distribution

edc_lab-0.3.42-py3-none-any.whl (122.5 kB view details)

Uploaded Python 3

File details

Details for the file edc-lab-0.3.42.tar.gz.

File metadata

  • Download URL: edc-lab-0.3.42.tar.gz
  • Upload date:
  • Size: 78.0 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/4.0.2 CPython/3.10.6

File hashes

Hashes for edc-lab-0.3.42.tar.gz
Algorithm Hash digest
SHA256 b0e0acd76920dc6609859880835d194245bde7dba43f1d0b67cf001aff636ae2
MD5 e082785d1d1aefa82f33d8ba27962a5f
BLAKE2b-256 87a5c0f2b52024155fb898b832435dad383709973010d571eb20a0904d361746

See more details on using hashes here.

File details

Details for the file edc_lab-0.3.42-py3-none-any.whl.

File metadata

  • Download URL: edc_lab-0.3.42-py3-none-any.whl
  • Upload date:
  • Size: 122.5 kB
  • Tags: Python 3
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/4.0.2 CPython/3.10.6

File hashes

Hashes for edc_lab-0.3.42-py3-none-any.whl
Algorithm Hash digest
SHA256 d0604ae0a61805158323fd4c309c2954e8c8fdb0fe478087d8588aa9374843ed
MD5 6311659427038b32f16fe5197106d437
BLAKE2b-256 91eb279ac67e9058a287ffb3227cd50de866fe5d1a7805362238a89a94f84c3a

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