omniage 0.99.3

The package provides a comprehensive Python framework for aging research. It offers high-level interfaces for calculating a vast suite of aging-related clocks and biomarkers.

OmniAge

A comprehensive Python framework for aging research and biological clock calculation

Authors:

• Zhaozhen Du (Shanghai Institute of Nutrition and Health, CAS) - [e-mail]
• Andrew E. Teschendorff (Shanghai Institute of Nutrition and Health, CAS) - [e-mail]

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📖 Overview

OmniAge offers high-level interfaces for calculating a vast suite of aging-related clocks and biomarkers. It is designed to integrate seamlessly with standard bioinformatics workflows (e.g., scanpy, pandas).

The package covers three main categories:

1. Epigenetic (DNAm) Clocks: Including Chronological, Biological (e.g., GrimAge, DunedinPACE), Cellular (Mitotic), and Gestational age clocks.
2. Transcriptomic (RNA) Clocks: Including sc-ImmuAging, Brain_CT_clock, and Pasta.
3. Surrogate Biomarkers: Proxies for proteins (CRP, IL6) and lifestyle traits (Smoking, BMI).

✨ For a complete list of supported clocks and detailed usage examples, please refer to our Tutorial Notebook.

🛠 Installation

Install via pip with the subdirectory flag:

git clone https://github.com/Duzhaozhen/OmniAgePy.git
pip install .

[!TIP] If you encounter errors building pyarrow or h5py (common on Linux servers), we recommend pre-installing these dependencies via Conda:

conda install -c conda-forge pyarrow h5py

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