Sync meer
Browse files- README.md +38 -0
- config.json +34 -0
- meer.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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# meer
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Whole Lifespan Multi-Tissue (WLMT) mouse clock trained by elastic net on RRBS methylation percentages from untreated wild-type C57BL/6 samples.
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|---|---|
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| **Predicts** | chronological age |
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| **Species** | Mus musculus |
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| **Tissue** | multi-tissue |
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| **Data type** | DNA methylation |
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| **Model type** | elastic net regression |
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| **Year** | 2018 |
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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, ["meer"])
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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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Meer, M. V., Podolskiy, D. I., Tyshkovskiy, A. & Gladyshev, V. N. A whole lifespan mouse multi-tissue DNA methylation clock. eLife 7, e40675 (2018).
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https://doi.org/10.7554/elife.40675
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config.json
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{
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"approved_by_author": "\u231b",
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"citation": "Meer, M. V., Podolskiy, D. I., Tyshkovskiy, A. & Gladyshev, V. N. A whole lifespan mouse multi-tissue DNA methylation clock. eLife 7, e40675 (2018).",
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"citations": 203,
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"citations_date": "2026-07-05",
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"clock_name": "meer",
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"data_type": "DNA methylation",
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"doi": "https://doi.org/10.7554/elife.40675",
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"journal": "eLife",
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"last_author": "Vadim N. Gladyshev",
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"model_type": "elastic net regression",
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"n_features": 435,
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"notes": "Whole Lifespan Multi-Tissue (WLMT) mouse clock trained by elastic net on RRBS methylation percentages from untreated wild-type C57BL/6 samples.",
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"platform": [
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"RRBS"
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],
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"population": "mice",
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"predicts": [
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"chronological age"
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],
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"research_only": null,
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"species": "Mus musculus",
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"tissue": [
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"multi-tissue"
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],
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"training_target": [
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"chronological age"
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],
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"unit": [
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"days"
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],
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"version": "v0.3.0",
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"year": 2018
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}
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meer.pt
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version https://git-lfs.github.com/spec/v1
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oid sha256:93efd890935eeaf923698ae7fa94e4abbb077bf4e01ebfacf13c07c34eb443d0
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size 18085
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