Skip to main content

Single cell Morphology Quality Control

PyPI - Version Build Status Coverage Status Ruff Poetry

🌠 Navigate the cosmos of single-cell morphology with confidence — coSMicQC keeps your data on course!

coSMicQC is a Python package to evaluate converted single-cell morphology outputs from CytoTable.

It can be challenging to get "perfect" single-cell compartment segmentation across large high-throughput screens when performing object detection in CellProfiler (or similar software). Technical artifacts can arise during segmentation, leading to issues such as under-segmentation, over-segmentation, or the erroneous segmentation of background noise, smudges, or bright artifacts.

In single-cell analysis, intriguing phenotypes often emerge by examining morphological differences. However, technical outliers in the data can obscure these biological insights, compromising the validity of the findings.

By utilizing specific morphological features extracted with CellProfiler, particularly AreaShape features, you can identify technically incorrect segmentations. These can then be labeled or removed before further preprocessing steps, such as those performed with pycytominer.

Installation

Install coSMicQC from PyPI or from source:

# install from pypi
pip install coSMicQC

# install directly from source
pip install git+https://github.com/WayScience/coSMicQC.git

Contributing, Development, and Testing

Please see CONTRIBUTING.md for more details on contributions, development, and testing.

References

Download files

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

Source Distribution

cosmicqc-0.0.10.tar.gz (18.8 kB view details)

Uploaded Source

Built Distribution

If you're not sure about the file name format, learn more about wheel file names.

cosmicqc-0.0.10-py3-none-any.whl (19.4 kB view details)

Uploaded Python 3

File details

Details for the file cosmicqc-0.0.10.tar.gz.

File metadata

  • Download URL: cosmicqc-0.0.10.tar.gz
  • Upload date:
  • Size: 18.8 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? Yes
  • Uploaded via: twine/5.1.0 CPython/3.12.4

File hashes

Hashes for cosmicqc-0.0.10.tar.gz
Algorithm Hash digest
SHA256 c2a45b020119c9cc3349886c75913de413d7cc880ca0012de69e35af872b68bd
MD5 69d703c1c61f982f77d0893c21c11e4a
BLAKE2b-256 3f932b90bb7facdd5e300e1f6cd3b0470090c2d5abdf7004fe193474982bacdb

See more details on using hashes here.

File details

Details for the file cosmicqc-0.0.10-py3-none-any.whl.

File metadata

  • Download URL: cosmicqc-0.0.10-py3-none-any.whl
  • Upload date:
  • Size: 19.4 kB
  • Tags: Python 3
  • Uploaded using Trusted Publishing? Yes
  • Uploaded via: twine/5.1.0 CPython/3.12.4

File hashes

Hashes for cosmicqc-0.0.10-py3-none-any.whl
Algorithm Hash digest
SHA256 ab94b96be3fcb597bc40620735074ed55edcf885d90bd46013efb34ffffd56db
MD5 799efea6f9a57e458358ee4118316c1c
BLAKE2b-256 4a883eba282ec7380d3a2cbc0f200aedeb42565d3ad1da71c9b71b62e6df0fb0

See more details on using hashes here.

Supported by

AWS Cloud computing and Security Sponsor Datadog Monitoring Depot Continuous Integration Fastly CDN Google Download Analytics Sentry Error logging StatusPage Status page