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Python library and Orange3 widget for high-throughput screening data preprocessing, toxicity scoring, and FAIRification

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ideaconsult/orange3-toxfairy

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orange-tox5

Installation Steps

  1. Install the latest version of Miniforge.
  2. Clone the repo.
  3. Open a new Miniforge prompt and change directory to where you cloned the repo.
  4. Create a new Conda environment (see Notes below about mamba).
mamba env create -f environment.yml
  1. Activate the environment.
mamba activate orange-tox5
  1. Run Orange.
orange-canvas

Notes

  • IMPORTANT: On the first run Orange will need to download some additional R libraries. You may see several progress bars (on Windows) or messages in the console (on Linux). The message package 'toxpiR' successfully unpacked in the console will indicate when the downloads are finished. On subsequent runs Orange should start much faster.
  • Miniforge is the only Conda system that we test and support. Other Conda systems like the standard Anaconda and Miniconda should work, but we cannot provide support for them.
  • Miniforge provides mamba in addition to conda. mamba is a reimplementation of the conda package manager in C++. It is much faster in dependency resolution, which is why we stronly recommend using it instead of conda.
  • Installing with Conda is the only supported method. It should be possible to use an existing Orange3 installation and also use pip to install the Python dependencies, as well as install R independently, but we cannot at the moment provide support for such solution.

Acknowledgements

🇪🇺 This project has received funding from the European Union’s Horizon 2020 research and innovation program under grant agreement No. 953183.

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Python library and Orange3 widget for high-throughput screening data preprocessing, toxicity scoring, and FAIRification

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