| library_name: pyaging | |
| tags: | |
| - pyaging | |
| - aging-clock | |
| - biology | |
| - dna-methylation | |
| # replitalinorm | |
| Upstream starting-PD normalization model used during RepliTali construction. It was trained only in the chronologically youngest fetal skin fibroblast line (AG06561) to estimate the unobserved pre-culture replicative-history offset; it is not the final 87-CpG RepliTali model. | |
| Model weights retain the original authors' terms; the pyaging software license does not relicense them. | |
| | | | | |
| |---|---| | |
| | **Predicts** | replicative history | | |
| | **Species** | Homo sapiens | | |
| | **Tissue** | cultured fibroblasts | | |
| | **Data type** | DNA methylation | | |
| | **Model type** | elastic net regression | | |
| | **Year** | 2022 | | |
| ## Use with pyaging | |
| ```python | |
| import pyaging as pya | |
| pya.pred.predict_age(adata, ["replitalinorm"]) | |
| ``` | |
| Browse every clock in the [pyaging Clock Catalogue](https://pyaging.readthedocs.io). | |
| ## Citation | |
| Endicott, J.L., Nolte, P.A., Shen, H. & Laird, P.W. Cell division drives DNA methylation loss in late-replicating domains in primary human cells. Nature Communications 13, 6659 (2022). | |
| https://doi.org/10.1038/s41467-022-34268-8 | |