| library_name: pyaging | |
| tags: | |
| - pyaging | |
| - aging-clock | |
| - biology | |
| - dna-methylation | |
| # epicmithyper | |
| Hypermethylation component of epiCMIT: a 184-CpG score ranging from 0 to 1 that tracks low-to-high relative proliferative history in normal and neoplastic B cells. | |
| Model weights retain the original authors' terms; the pyaging software license does not relicense them. | |
| | | | | |
| |---|---| | |
| | **Predicts** | mitotic age | | |
| | **Species** | Homo sapiens | | |
| | **Tissue** | B cells | | |
| | **Data type** | DNA methylation | | |
| | **Model type** | mean methylation aggregation | | |
| | **Year** | 2020 | | |
| ## Use with pyaging | |
| ```python | |
| import pyaging as pya | |
| pya.pred.predict_age(adata, ["epicmithyper"]) | |
| ``` | |
| Browse every clock in the [pyaging Clock Catalogue](https://pyaging.readthedocs.io). | |
| ## Citation | |
| Duran-Ferrer, M., et al. "The proliferative history shapes the DNA methylome of B-cell tumors and predicts clinical outcome." Nature Cancer 1 (2020): 1066-1081. | |
| https://doi.org/10.1038/s43018-020-00131-2 | |