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pchorvath2013 – AI Model by pyaging | AlphaNeural AI
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pyaging
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pchorvath2013
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pyaging
PCA + elastic net regression
aging-clock
biology
dna-methylation
mit
us
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pchorvath2013
Principal-component proxy of the 2013 Horvath pan-tissue clock, trained against the original clock score using substituted multi-tissue datasets.
Predicts
chronological age
Species
Homo sapiens
Tissue
multi-tissue
Data type
DNA methylation
Model type
PCA + elastic net regression
Year
2022
Use with pyaging
python
1
import
pyaging
as
pya
2
3
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
