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

# intrinclock370

Author-demo IntrinClock at lambda.1se: 370 nonzero CpGs from the original serialized cv.glmnet fit. Predicts chronological age resistant to immune-cell-composition changes. This is a separately fitted regularization column, not the existing 380-CpG lambda.min model with ten sites removed. Returns years using the author's inverse Horvath transform.

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** | two-stage elastic net regression |
| **Year** | 2024 |

## Use with pyaging

```python
import pyaging as pya

pya.pred.predict_age(adata, ["intrinclock370"])
```

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

## Citation

Tomusiak, A., et al. “Development of an epigenetic clock resistant to changes in immune cell composition.” Communications Biology 7, 934 (2024).

https://doi.org/10.1038/s42003-024-06609-4