| --- |
| license: mit |
| library_name: pyaging |
| tags: |
| - pyaging |
| - aging-clock |
| - biology |
| - dna-methylation |
| --- |
| |
| # zhangblup |
|
|
| High-dimensional chronological-age predictor using best linear unbiased prediction across the full quality-controlled set of 319,607 methylation probes. |
|
|
| | | | |
| |---|---| |
| | **Predicts** | chronological age | |
| | **Species** | Homo sapiens | |
| | **Tissue** | whole blood, saliva | |
| | **Data type** | DNA methylation | |
| | **Model type** | best linear unbiased prediction | |
| | **Year** | 2019 | |
|
|
| ## Use with pyaging |
|
|
| ```python |
| import pyaging as pya |
| |
| pya.pred.predict_age(adata, ["zhangblup"]) |
| ``` |
|
|
| Browse every clock in the [pyaging Clock Catalogue](https://pyaging.readthedocs.io). |
|
|
| ## Citation |
|
|
| Zhang, Q., Vallerga, C.L., Walker, R.M. et al. Improved precision of epigenetic clock estimates across tissues and its implication for biological ageing. Genome Medicine 11, 54 (2019). |
|
|
| https://doi.org/10.1186/s13073-019-0667-1 |
|
|
