| library_name: pyaging | |
| tags: | |
| - pyaging | |
| - aging-clock | |
| - biology | |
| - dna-methylation | |
| # leecontrol | |
| Control placental clock trained on placentas designated as controls, with known major placental pathology excluded. | |
| Model weights retain the original authors' terms; the pyaging software license does not relicense them. | |
| | | | | |
| |---|---| | |
| | **Predicts** | gestational age | | |
| | **Species** | Homo sapiens | | |
| | **Tissue** | placenta | | |
| | **Data type** | DNA methylation | | |
| | **Model type** | elastic net regression | | |
| | **Year** | 2019 | | |
| ## Use with pyaging | |
| ```python | |
| import pyaging as pya | |
| pya.pred.predict_age(adata, ["leecontrol"]) | |
| ``` | |
| Browse every clock in the [pyaging Clock Catalogue](https://pyaging.readthedocs.io). | |
| ## Citation | |
| Lee, Y., et al. “Placental epigenetic clocks: estimating gestational age using placental DNA methylation levels.” Aging 11(12): 4238–4253 (2019). | |
| https://doi.org/10.18632/aging.102049 | |