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pyaging/pchorvath2013

sourceHugging Facemitupdated 1mo agoView on Hugging Face
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Model Card

pchorvath2013

Principal-component proxy of the 2013 Horvath pan-tissue clock, trained against the original clock score using substituted multi-tissue datasets.

Predictschronological age
SpeciesHomo sapiens
Tissuemulti-tissue
Data typeDNA methylation
Model typePCA + elastic net regression
Year2022

Use with pyaging

python
import pyaging as pya

pya.pred.predict_age(adata, ["pchorvath2013"])

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): 644–661.

https://doi.org/10.1038/s43587-022-00248-2