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library_name: pyaging
tags:
- pyaging
- aging-clock
- biology
- dna-methylation
---
# zhangen
Elastic-net chronological-age predictor released from the largest multi-cohort training set, using 514 selected CpGs from predominantly blood plus saliva data.
Model weights retain the original authors' terms; the pyaging software license does not relicense them.
| | |
|---|---|
| **Predicts** | chronological age |
| **Species** | Homo sapiens |
| **Tissue** | whole blood, saliva |
| **Data type** | DNA methylation |
| **Model type** | elastic net regression |
| **Year** | 2019 |
## Use with pyaging
```python
import pyaging as pya
pya.pred.predict_age(adata, ["zhangen"])
```
Browse every clock in the [pyaging Clock Catalogue](https://pyaging.readthedocs.io).
## Citation
Zhang, Q., Vallerga, C.L., Walker, R.M. et al. Improved precision of epigenetic clock estimates across tissues and its implication for biological ageing. Genome Medicine 11, 54 (2019).
https://doi.org/10.1186/s13073-019-0667-1
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