File size: 1,015 Bytes
89db002
 
 
 
 
 
 
 
 
 
 
 
 
3f64342
 
89db002
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
---
library_name: pyaging
tags:
- pyaging
- aging-clock
- biology
- dna-methylation
---

# cabec

Common Adult Blood-based EPIC Clock trained on the extended adult whole-blood dataset but restricted to autosomal CpGs shared by the Illumina 450K and EPIC arrays.

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

| | |
|---|---|
| **Predicts** | chronological age |
| **Species** | Homo sapiens |
| **Tissue** | whole blood |
| **Data type** | DNA methylation |
| **Model type** | elastic net regression |
| **Year** | 2020 |

## Use with pyaging

```python
import pyaging as pya

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

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

## Citation

Lee, Yunsung, et al. "Blood-based epigenetic estimators of chronological age in human adults using DNA methylation data from the Illumina MethylationEPIC array." BMC genomics 21 (2020): 1-13.

https://doi.org/10.1186/s12864-020-07168-8