| library_name: pyaging | |
| tags: | |
| - pyaging | |
| - aging-clock | |
| - biology | |
| - dna-methylation | |
| # mccartneysmoking | |
| Whole-blood DNAm LASSO score trained on log(smoking pack-years + 1), residualized for age, sex and ten genetic principal components. The returned linear score remains on that adjusted natural-log scale; it is not an absolute exposure in physical units. Evaluated out of sample in LBC1936. | |
| Model weights retain the original authors' terms; the pyaging software license does not relicense them. | |
| | | | | |
| |---|---| | |
| | **Predicts** | smoking exposure | | |
| | **Species** | Homo sapiens | | |
| | **Tissue** | whole blood | | |
| | **Data type** | DNA methylation | | |
| | **Model type** | LASSO regression | | |
| | **Year** | 2018 | | |
| ## Use with pyaging | |
| ```python | |
| import pyaging as pya | |
| pya.pred.predict_age(adata, ["mccartneysmoking"]) | |
| ``` | |
| Browse every clock in the [pyaging Clock Catalogue](https://pyaging.readthedocs.io). | |
| ## Citation | |
| McCartney, D. L., et al. “Epigenetic prediction of complex traits and death.” Genome Biology 19, 136 (2018). | |
| https://doi.org/10.1186/s13059-018-1514-1 | |