| library_name: pyaging | |
| tags: | |
| - pyaging | |
| - aging-clock | |
| - biology | |
| - dna-methylation | |
| # dnamphenoage | |
| Blood DNA-methylation estimator trained by elastic net on 513 CpGs common to the 27K, 450K and EPIC arrays to reproduce a mortality-derived clinical Phenotypic Age. The parent DNAmPhenoAge coefficients were fitted on InCHIANTI 450K whole-blood data; the selected sites also occur on 27K and EPIC arrays. | |
| Model weights retain the original authors' terms; the pyaging software license does not relicense them. | |
| | | | | |
| |---|---| | |
| | **Predicts** | phenotypic age | | |
| | **Species** | Homo sapiens | | |
| | **Tissue** | whole blood | | |
| | **Data type** | DNA methylation | | |
| | **Model type** | elastic net regression | | |
| | **Year** | 2018 | | |
| ## Use with pyaging | |
| ```python | |
| import pyaging as pya | |
| pya.pred.predict_age(adata, ["dnamphenoage"]) | |
| ``` | |
| Browse every clock in the [pyaging Clock Catalogue](https://pyaging.readthedocs.io). | |
| ## Citation | |
| Levine, M. E., et al. "An epigenetic biomarker of aging for lifespan and healthspan." Aging 10.4 (2018): 573-591. | |
| https://doi.org/10.18632/aging.101414 | |