Sync zhangblup
Browse files- README.md +38 -0
- config.json +38 -0
- zhangblup.pt +3 -0
README.md
ADDED
|
@@ -0,0 +1,38 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
---
|
| 2 |
+
license: bsd-3-clause
|
| 3 |
+
library_name: pyaging
|
| 4 |
+
tags:
|
| 5 |
+
- pyaging
|
| 6 |
+
- aging-clock
|
| 7 |
+
- biology
|
| 8 |
+
- dna-methylation
|
| 9 |
+
---
|
| 10 |
+
|
| 11 |
+
# zhangblup
|
| 12 |
+
|
| 13 |
+
High-dimensional chronological-age predictor using best linear unbiased prediction across the full quality-controlled set of 319,607 methylation probes.
|
| 14 |
+
|
| 15 |
+
| | |
|
| 16 |
+
|---|---|
|
| 17 |
+
| **Predicts** | chronological age |
|
| 18 |
+
| **Species** | Homo sapiens |
|
| 19 |
+
| **Tissue** | whole blood, saliva |
|
| 20 |
+
| **Data type** | DNA methylation |
|
| 21 |
+
| **Model type** | best linear unbiased prediction |
|
| 22 |
+
| **Year** | 2019 |
|
| 23 |
+
|
| 24 |
+
## Use with pyaging
|
| 25 |
+
|
| 26 |
+
```python
|
| 27 |
+
import pyaging as pya
|
| 28 |
+
|
| 29 |
+
pya.pred.predict_age(adata, ["zhangblup"])
|
| 30 |
+
```
|
| 31 |
+
|
| 32 |
+
Browse every clock in the [pyaging Clock Catalogue](https://pyaging.readthedocs.io).
|
| 33 |
+
|
| 34 |
+
## Citation
|
| 35 |
+
|
| 36 |
+
Zhang, Q., Vallerga, C.L., Walker, R.M. et al. Improved precision of epigenetic clock estimates across tissues and its implication for biological ageing. Genome Medicine 11, 54 (2019).
|
| 37 |
+
|
| 38 |
+
https://doi.org/10.1186/s13073-019-0667-1
|
config.json
ADDED
|
@@ -0,0 +1,38 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
{
|
| 2 |
+
"approved_by_author": "\u231b",
|
| 3 |
+
"citation": "Zhang, Q., Vallerga, C.L., Walker, R.M. et al. Improved precision of epigenetic clock estimates across tissues and its implication for biological ageing. Genome Medicine 11, 54 (2019).",
|
| 4 |
+
"citations": 519,
|
| 5 |
+
"citations_date": "2026-07-05",
|
| 6 |
+
"clock_name": "zhangblup",
|
| 7 |
+
"data_type": "DNA methylation",
|
| 8 |
+
"doi": "https://doi.org/10.1186/s13073-019-0667-1",
|
| 9 |
+
"journal": "Genome Medicine",
|
| 10 |
+
"last_author": "Peter M. Visscher",
|
| 11 |
+
"model_type": "best linear unbiased prediction",
|
| 12 |
+
"n_features": 319607,
|
| 13 |
+
"notes": "High-dimensional chronological-age predictor using best linear unbiased prediction across the full quality-controlled set of 319,607 methylation probes.",
|
| 14 |
+
"platform": [
|
| 15 |
+
"Illumina 450K",
|
| 16 |
+
"Illumina EPIC"
|
| 17 |
+
],
|
| 18 |
+
"population": "all ages",
|
| 19 |
+
"predicts": [
|
| 20 |
+
"chronological age"
|
| 21 |
+
],
|
| 22 |
+
"preprocess": "scale_row",
|
| 23 |
+
"reference_values": true,
|
| 24 |
+
"research_only": null,
|
| 25 |
+
"species": "Homo sapiens",
|
| 26 |
+
"tissue": [
|
| 27 |
+
"whole blood",
|
| 28 |
+
"saliva"
|
| 29 |
+
],
|
| 30 |
+
"training_target": [
|
| 31 |
+
"chronological age"
|
| 32 |
+
],
|
| 33 |
+
"unit": [
|
| 34 |
+
"years"
|
| 35 |
+
],
|
| 36 |
+
"version": "v0.3.0",
|
| 37 |
+
"year": 2019
|
| 38 |
+
}
|
zhangblup.pt
ADDED
|
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
version https://git-lfs.github.com/spec/v1
|
| 2 |
+
oid sha256:d46a72e644419f65dcc29f87220afed07969093c7369bac1eab9d5e7224f01e4
|
| 3 |
+
size 11835941
|