Sync leecontrol
Browse files- README.md +38 -0
- config.json +35 -0
- leecontrol.pt +3 -0
README.md
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---
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license: bsd-3-clause
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library_name: pyaging
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tags:
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- pyaging
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- aging-clock
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- biology
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- dna-methylation
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---
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# leecontrol
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Control placental clock trained on placentas designated as controls, with known major placental pathology excluded.
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| **Predicts** | gestational age |
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| **Species** | Homo sapiens |
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| **Tissue** | placenta |
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| **Data type** | DNA methylation |
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| **Model type** | elastic net regression |
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| **Year** | 2019 |
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## Use with pyaging
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```python
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import pyaging as pya
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pya.pred.predict_age(adata, ["leecontrol"])
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```
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Browse every clock in the [pyaging Clock Catalogue](https://pyaging.readthedocs.io).
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## Citation
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Lee, Y., et al. “Placental epigenetic clocks: estimating gestational age using placental DNA methylation levels.” Aging 11(12): 4238–4253 (2019).
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https://doi.org/10.18632/aging.102049
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config.json
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{
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"approved_by_author": "\u2705",
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"citation": "Lee, Y., et al. \u201cPlacental epigenetic clocks: estimating gestational age using placental DNA methylation levels.\u201d Aging 11(12): 4238\u20134253 (2019).",
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"citations": 170,
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"citations_date": "2026-07-05",
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"clock_name": "leecontrol",
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"data_type": "DNA methylation",
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"doi": "https://doi.org/10.18632/aging.102049",
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"journal": "Aging",
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"last_author": "Steve Horvath",
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"model_type": "elastic net regression",
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"n_features": 546,
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"notes": "Control placental clock trained on placentas designated as controls, with known major placental pathology excluded.",
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"platform": [
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"Illumina 450K",
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"Illumina EPIC"
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],
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"population": "pregnancies",
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"predicts": [
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"gestational age"
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],
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"research_only": null,
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"species": "Homo sapiens",
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"tissue": [
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"placenta"
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],
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"training_target": [
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"gestational age"
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],
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"unit": [
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"weeks"
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],
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"version": "v0.3.0",
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"year": 2019
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}
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leecontrol.pt
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version https://git-lfs.github.com/spec/v1
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oid sha256:bbf522dca4a97e691705de9519a99d0bf018e19410352a5e2c9768b9165e8b4c
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size 19621
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