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

# altumage

Pan-tissue chronological-age predictor using a five-hidden-layer neural network and 20,318 CpGs shared across the 27K, 450K and EPIC manifests; the actual training data came from 27K and 450K datasets.

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

| | |
|---|---|
| **Predicts** | chronological age |
| **Species** | Homo sapiens |
| **Tissue** | multi-tissue |
| **Data type** | DNA methylation |
| **Model type** | deep neural network |
| **Year** | 2022 |

## Use with pyaging

```python
import pyaging as pya

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

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

## Citation

de Lima Camillo, L.P., Lapierre, L.R. & Singh, R. A pan-tissue DNA-methylation epigenetic clock based on deep learning. npj Aging 8, 4 (2022).

https://doi.org/10.1038/s41514-022-00085-y