Transform CellProfiler and DeepProfiler data for processing image-based profiling readouts with Pycytominer and other Cytomining tools.
Project description
CytoTable
Diagram showing data flow relative to this project.
Summary
CytoTable enables single-cell morphology data analysis by cleaning and transforming CellProfiler (.csv
or .sqlite
), cytominer-database (.sqlite
), and DeepProfiler (.npz
), and other sources such as IN Carta data output data at scale.
CytoTable creates parquet files for both independent analysis and for input into Pycytominer.
The Parquet files will have a unified and documented data model, including referenceable schema where appropriate (for validation within Pycytominer or other projects).
The name for the project is inspired from:
- Cyto: "1. (biology) cell." (Wiktionary: Cyto-)
- Table:
- "1. Furniture with a top surface to accommodate a variety of uses."
- "3.1. A matrix or grid of data arranged in rows and columns."
(Wiktionary: Table)
Installation
Install CytoTable from PyPI or from source:
# install from pypi
pip install cytotable
# install directly from source
pip install git+https://github.com/cytomining/CytoTable.git
Contributing, Development, and Testing
We test CytoTable using ubuntu-latest
and macos-latest
GitHub Actions runner images.
Please see contributing.md for more details on contributions, development, and testing.
References
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