---
library_name: pyaging
tags:
- pyaging
- aging-clock
- biology
- dna-methylation
---

# stocp

Stochastic chronological-age clock built from simulated methylation trajectories at PhenoAge CpGs; despite its CpG source, its fitted outcome and returned construct are chronological age, not PhenoAge.

Model weights retain the original authors' terms; the pyaging software license does not relicense them.

| | |
|---|---|
| **Predicts** | chronological age |
| **Species** | Homo sapiens |
| **Tissue** | sorted monocytes |
| **Data type** | DNA methylation |
| **Model type** | elastic net regression |
| **Year** | 2024 |

## Use with pyaging

```python
import pyaging as pya

pya.pred.predict_age(adata, ["stocp"])
```

Browse every clock in the [pyaging Clock Catalogue](https://pyaging.readthedocs.io).

## Citation

Tong, Huige, et al. "Quantifying the stochastic component of epigenetic aging." Nature Aging 4 (2024): 886–901.

https://doi.org/10.1038/s43587-024-00600-8