The Cell Maps VNN Tool enables creation, training, and usage of an interpretable neural network-based models that predict cell response to a drug.
Project description
cellmaps_vnn
Cell Maps Visual Neural Network Toolkit
Free software: MIT license
Documentation: https://cellmaps-vnn.readthedocs.io.
Dependencies
Compatibility
Python 3.8+
Installation
git clone https://github.com/idekerlab/cellmaps_vnn
cd cellmaps_vnn
pip install -r requirements_dev.txt
make dist
pip install dist/cellmaps_vnn*whl
Run make command with no arguments to see other build/deploy options including creation of Docker image
make
Output:
clean remove all build, test, coverage and Python artifacts
clean-build remove build artifacts
clean-pyc remove Python file artifacts
clean-test remove test and coverage artifacts
lint check style with flake8
test run tests quickly with the default Python
test-all run tests on every Python version with tox
coverage check code coverage quickly with the default Python
docs generate Sphinx HTML documentation, including API docs
servedocs compile the docs watching for changes
testrelease package and upload a TEST release
release package and upload a release
dist builds source and wheel package
install install the package to the active Python's site-packages
dockerbuild build docker image and store in local repository
dockerpush push image to dockerhub
Before running tests and builds, please install pip install -r requirements_dev.txt
For developers
To deploy development versions of this package
Below are steps to make changes to this code base, deploy, and then run against those changes.
Make changes
Modify code in this repo as desired
Build and deploy
# From base directory of this repo cellmaps_vnn
pip uninstall cellmaps_vnn -y ; make clean dist; pip install dist/cellmaps_vnn*whl
Needed files
TODO: Add description of needed files
Usage
For information invoke cellmaps_vnncmd.py -h
Example usage
TODO: Add information about example usage
cellmaps_vnncmd.py # TODO Add other needed arguments here
Via Docker
Example usage
TODO: Add information about example usage
Coming soon ...
Credits
This package was created with Cookiecutter and the audreyr/cookiecutter-pypackage project template.
History
0.2.2 (2025-07-25)
Bug fixes: fixed hyperparameter optimization and generation of config file with optimal parameters
0.2.1 (2025-07-01)
Bug fixes: fixed _annotate_interactomes_of_systems method’s return value and fix hierarchy annotations
0.2.0 (2025-06-26)
Add annotation in hierarchy nodes of which gene have data for VNN (train)
Add fake generator of gene importance scores in interactomes of hierarchy system (the real generator will be implemented in the future)
0.1.0 (2024-12-26)
First release on PyPI.
Project details
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