Machine learning for biomarkers computing
Project description
Biolearn
Biolearn enables easy and versatile analyses of biomarkers of aging data. It provides tools to easily load data from publicly available sources like the Gene Expression Omnibus, National Health and Nutrition Examimation Survey, and the Framingham Heart Study. Biolearn also contains reference implemenations for common aging clock such at the Horvath clock, DunedinPACE and many others that can easily be run in only a few lines of code. You can read more about it in our paper.
Important links
Source code: https://github.com/bio-learn/biolearn/
Documentation Homepage: https://bio-learn.github.io/
Requirements
Python 3.10+
Install
Install biolearn using pip.
pip install biolearnTo verify the library was installed correctly open python or a jupyter notebook and run:
from biolearn.data_library import DataLibraryIf it executes with no errors then the library is installed. To get started check out some code examples
Discord server
The biolearn team has a discord server to answer questions, discuss feature requests, or have any biolearn related discussions.
Issues
If you find any bugs with biolearn please create a Github issue including how we can replicate the issue and the expected vs actual behavior.
Contributing
Detailed instructions on developer setup and how to contribute are available in the repo
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