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library_name: pyaging
tags:
- pyaging
- aging-clock
- biology
- dna-methylation
---
# epitoc2
Dynamic methylation-transmission model returning total cumulative stem-cell divisions per stem cell; an intrinsic rate additionally requires chronological age but is not this implementation's returned value.
Model weights retain the original authors' terms; the pyaging software license does not relicense them.
| | |
|---|---|
| **Predicts** | mitotic age |
| **Species** | Homo sapiens |
| **Tissue** | whole blood |
| **Data type** | DNA methylation |
| **Model type** | dynamic methylation transmission model |
| **Year** | 2020 |
## Use with pyaging
```python
import pyaging as pya
pya.pred.predict_age(adata, ["epitoc2"])
```
Browse every clock in the [pyaging Clock Catalogue](https://pyaging.readthedocs.io).
## Citation
Teschendorff, Andrew E. "A comparison of epigenetic mitotic-like clocks for cancer risk prediction." Genome Medicine 12 (2020): 56.
https://doi.org/10.1186/s13073-020-00752-3
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