https://github.com/theislab/campa
Conditional Autoencoders for Multiplexed Pixel Analysis
https://github.com/theislab/campa
Last synced: 10 months ago
JSON representation
Conditional Autoencoders for Multiplexed Pixel Analysis
- Host: GitHub
- URL: https://github.com/theislab/campa
- Owner: theislab
- License: bsd-3-clause
- Created: 2021-10-20T15:26:52.000Z (almost 5 years ago)
- Default Branch: main
- Last Pushed: 2022-11-25T14:07:57.000Z (over 3 years ago)
- Last Synced: 2025-09-14T04:58:07.819Z (10 months ago)
- Language: Jupyter Notebook
- Homepage: https://campa.readthedocs.io
- Size: 89.9 MB
- Stars: 16
- Watchers: 3
- Forks: 5
- Open Issues: 6
-
Metadata Files:
- Readme: README.rst
- Contributing: CONTRIBUTING.rst
- License: LICENSE
Awesome Lists containing this project
README
CAMPA - Conditional Autoencoder for Multiplexed Pixel Analysis
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
CAMPA is a framework for quantiative analysis of subcellular multi-channel imaging data.
It consists of a workflow that generates consistent subcellular landmarks (CSLs)
using conditional Variational Autoencoders (cVAE).
The output of the CAMPA workflow is an `anndata`_ object that contains interpretable
per-cell features summarizing the molecular composition
and spatial arrangement of CSLs inside each cell.
.. raw:: html
Visit our `documentation`_ for installation and usage examples.
Manuscript
----------
Please see our preprint
*"Learning consistent subcellular landmarks to quantify changes in multiplexed protein maps"*
(`Spitzer, Berry et al. (2022)`_) to learn more.
Installation
------------
CAMPA was developed for Python 3.9 and can be installed by running::
pip install campa
Contributing
------------
We are happy about any contributions! Before you start, check out our `contributing guide `_.
.. _anndata: https://anndata.readthedocs.io/en/stable/
.. _documentation: https://campa.readthedocs.io/en/stable/
.. _`data and experiment paths`: https://campa.readthedocs.io/en/stable/overview.html#campa-config
.. _`Spitzer, Berry et al. (2022)`: https://www.biorxiv.org/content/10.1101/2022.05.07.490900v1