LIMS/lab classes for clinicedc/edc projects
Project description
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
Built Distribution
Filter files by name, interpreter, ABI, and platform.
If you're not sure about the file name format, learn more about wheel file names.
Copy a direct link to the current filters
File details
Details for the file edc_lab-1.0.5.tar.gz.
File metadata
- Download URL: edc_lab-1.0.5.tar.gz
- Upload date:
- Size: 83.0 kB
- Tags: Source
- Uploaded using Trusted Publishing? No
- Uploaded via: twine/6.1.0 CPython/3.12.11
File hashes
| Algorithm | Hash digest | |
|---|---|---|
| SHA256 |
4b74075b69bb881cac26de32f1bc2132112bd2e4f9b655c552fdb2f4d617a3e3
|
|
| MD5 |
20b94175384afe66b89c00c310843e11
|
|
| BLAKE2b-256 |
e1ba244353d17b394ba5a76f7f3357cbd1a430e192c2094d8135d82d8cd50cba
|
File details
Details for the file edc_lab-1.0.5-py3-none-any.whl.
File metadata
- Download URL: edc_lab-1.0.5-py3-none-any.whl
- Upload date:
- Size: 133.5 kB
- Tags: Python 3
- Uploaded using Trusted Publishing? No
- Uploaded via: twine/6.1.0 CPython/3.12.11
File hashes
| Algorithm | Hash digest | |
|---|---|---|
| SHA256 |
1a7e9dceaa1c9fdb20f8b1c3366794f0998fe1c89bdca6ef88d6920e8586c5c6
|
|
| MD5 |
20af19663ae91e32f60130c6a6d06d4c
|
|
| BLAKE2b-256 |
c536f228834d30c73d8aa2446fc8d716e7f2bafef82c7170735f87c4caa0b036
|