| library_name: pyaging | |
| tags: | |
| - pyaging | |
| - aging-clock | |
| - biology | |
| - dna-methylation | |
| # dunedinpace | |
| Whole-blood elastic-net pace-of-aging biomarker trained at age 45 against a 20-year longitudinal slope composite of 19 organ-system biomarkers. PyAging follows the official 20,000-probe quantile-normalization panel: 173 scoring CpGs plus 19,827 background probes. | |
| Model weights retain the original authors' terms; the pyaging software license does not relicense them. These weights are restricted to research use under the authors' terms. | |
| | | | | |
| |---|---| | |
| | **Predicts** | pace of aging | | |
| | **Species** | Homo sapiens | | |
| | **Tissue** | whole blood | | |
| | **Data type** | DNA methylation | | |
| | **Model type** | elastic net regression | | |
| | **Year** | 2022 | | |
| ## Use with pyaging | |
| ```python | |
| import pyaging as pya | |
| pya.pred.predict_age(adata, ["dunedinpace"]) | |
| ``` | |
| Browse every clock in the [pyaging Clock Catalogue](https://pyaging.readthedocs.io). | |
| ## Citation | |
| Belsky, D. W., Caspi, A., Corcoran, D. L., et al. (2022). DunedinPACE, a DNA methylation biomarker of the pace of aging. eLife, 11, e73420. | |
| https://doi.org/10.7554/elife.73420 | |