| library_name: pyaging | |
| tags: | |
| - pyaging | |
| - aging-clock | |
| - biology | |
| - dna-methylation | |
| # stoch | |
| Stochastic chronological-age clock built from simulated methylation trajectories at the Horvath clock CpGs; it is a stochastic counterpart, not the original Horvath clock. | |
| 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, ["stoch"]) | |
| ``` | |
| 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 | |