---
library_name: pyaging
tags:
- pyaging
- aging-clock
- biology
- dna-methylation
---

# pcdnamtl

Principal-component proxy trained to reproduce the original DNAmTL clock output; the returned score remains in kilobases. Figure-level base-pair deviations are a separate analysis-scale conversion.

Model weights retain the original authors' terms; the pyaging software license does not relicense them.

| | |
|---|---|
| **Predicts** | leukocyte telomere length |
| **Species** | Homo sapiens |
| **Tissue** | whole blood |
| **Data type** | DNA methylation |
| **Model type** | PCA + elastic net regression |
| **Year** | 2022 |

## Use with pyaging

```python
import pyaging as pya

pya.pred.predict_age(adata, ["pcdnamtl"])
```

Browse every clock in the [pyaging Clock Catalogue](https://pyaging.readthedocs.io).

## Citation

Higgins-Chen, Albert T., et al. "A computational solution for bolstering reliability of epigenetic clocks: implications for clinical trials and longitudinal tracking." Nature Aging 2 (2022): 644–661.

https://doi.org/10.1038/s43587-022-00248-2