Machine learning for biomarkers computing
Project description
Biolearn
Biolearn leverages the scikit-learn Python toolbox for biomarkers analysis
Important links
Official source code repo: https://github.com/bio-learn/biolearn/
HTML documentation (stable release): https://bio-learn.github.io/
Install
Latest release
1. Setup a virtual environment
We recommend that you install biolearn in a virtual Python environment. In linux as example you can create one with venv:
python3 -m venv bioenv
source bioenv/bin/activateAfter you can install the package in the activated virtual environment:
pip install -U biolearnDevelopment version
Please find all development setup instructions in the contribution guide.
Check installation
Try importing biolearn in a python / iPython session:
import biolearnIf no error is raised, you have installed biolearn correctly.
Discord server
The biolearn team has a discord server to answer questions, discuss feature requests, or have any biolearn related discussions.
For more information and ways to engage with the biolearn team see How to get help.
Dependencies
The required dependencies to use the software are listed in the file pyproject.toml.
If you are using biolearn plotting functionalities or running the examples, matplotlib >= 3.3.0 is required.
Some plotting functions in biolearn support both matplotlib and plotly as plotting engines.
If you want to run the tests, you need pytest >= 6.0.0 and pytest-cov for coverage reporting.
Development
Detailed instructions on how to contribute are available at http://bio-learn.github.io/stable/development.html
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