| library_name: pyaging | |
| tags: | |
| - pyaging | |
| - aging-clock | |
| - biology | |
| - dna-methylation | |
| # mayne | |
| Placental elastic-net clock trained on pooled healthy human placenta methylation datasets; 62 selected CpGs predict gestational age and were used to test age acceleration in early-onset preeclampsia. | |
| 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** | 2017 | | |
| ## Use with pyaging | |
| ```python | |
| import pyaging as pya | |
| pya.pred.predict_age(adata, ["mayne"]) | |
| ``` | |
| Browse every clock in the [pyaging Clock Catalogue](https://pyaging.readthedocs.io). | |
| ## Citation | |
| Mayne, Benjamin T., et al. "Accelerated placental aging in early onset preeclampsia pregnancies identified by DNA methylation." Epigenomics 9 (2017): 279–289. | |
| https://doi.org/10.2217/epi-2016-0103 | |