pcphenoage
Principal-component DNAm PhenoAge model trained directly on phenotypic-age scores rather than as a proxy of the original CpG clock.
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 | PCA + elastic net regression |
| Year | 2022 |
Use with pyaging
import pyaging as pya
pya.pred.predict_age(adata, ["pcphenoage"])
Browse every clock in the pyaging Clock Catalogue.
Citation
Higgins-Chen, Albert T., et al. "A computational solution for bolstering reliability of epigenetic clocks: implications for clinical trials and longitudinal tracking." Nature Aging 2 (2022): 644β661.
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