| --- |
| 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 |
|
|
