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library_name: pyaging
tags:
- pyaging
- aging-clock
- biology
- dna-methylation
---
# epitoc3
Code-defined 170-CpG extension of the dynamic mitotic model. Official EpiMitClocks data show that all 170 sites are a subset of the 371 stemTOC vivo-mitCpGs derived from fetal/neonatal references, six normal proliferating cell lines, and three adult whole-blood cohorts. The assigned 2020 dynamic-model paper does not name or define epiTOC3.
Model weights retain the original authors' terms; the pyaging software license does not relicense them.
| | |
|---|---|
| **Predicts** | mitotic age |
| **Species** | Homo sapiens |
| **Tissue** | cultured primary human cells, whole blood, multi-tissue, cord 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, ["epitoc3"])
```
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
|