miage

Mitotic-age estimator using the authors’ 268-CpG fitted b/c/d parameters and five-start bounded L-BFGS-B least squares (bounds of 10–10,000 on the relative-mitotic-age scale). The scale is identifiable only up to an unknown common factor, so scores are not absolute division counts. The scalar optimizer runs on CPU in float64, including when other clocks run on CUDA. Missing CpGs and supplied NaNs are omitted from each sample’s objective. The original all-NaN tie returns 2,008; this is an optimizer starting value with no biological meaning, so measured clock CpGs are required for interpretation. Original author function_library.r and site_specific_parameters.Rdata are preserved by an archived mirror at anilpsori/DNAm_pipelines_and_biomarkers commit d84d6adfc039355d5f9c962fc5faa7d1054f56b2; the original Columbia download returned HTTP403 during verification. All 268 CpG IDs and shared annotation fields match the original publisher supplement in order. No software/weight license is declared by the archived author files; the separate publisher supplement is CC BY4.0.

Model weights retain the original authors' terms; the pyaging software license does not relicense them.

Predicts mitotic age
Species Homo sapiens
Tissue multi-tissue
Data type DNA methylation
Model type dynamic methylation transmission model
Year 2018

Use with pyaging

import pyaging as pya

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

Browse every clock in the pyaging Clock Catalogue.

Citation

Youn, A., and Wang, S. (2018). The MiAge Calculator: a DNA methylation-based mitotic age calculator of human tissue types. Epigenetics, 13(2), 192–206.

https://doi.org/10.1080/15592294.2017.1389361

Downloads last month
49
Inference Providers NEW
This model isn't deployed by any Inference Provider. 🙋 Ask for provider support