---
license: mit
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.

| | |
|---|---|
| **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