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

# replitalinorm

Upstream starting-PD normalization model used during RepliTali construction. It was trained only in the chronologically youngest fetal skin fibroblast line (AG06561) to estimate the unobserved pre-culture replicative-history offset; it is not the final 87-CpG RepliTali model.

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

| | |
|---|---|
| **Predicts** | replicative history |
| **Species** | Homo sapiens |
| **Tissue** | cultured fibroblasts |
| **Data type** | DNA methylation |
| **Model type** | elastic net regression |
| **Year** | 2022 |

## Use with pyaging

```python
import pyaging as pya

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

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

## Citation

Endicott, J.L., Nolte, P.A., Shen, H. & Laird, P.W. Cell division drives DNA methylation loss in late-replicating domains in primary human cells. Nature Communications 13, 6659 (2022).

https://doi.org/10.1038/s41467-022-34268-8