Sync replitalinorm
Browse files- README.md +38 -0
- config.json +34 -0
- replitalinorm.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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# replitalinorm
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Upstream starting-PD normalization model used during RepliTali construction. It was trained only in the chronologically youngest fetal skin fibroblast line (AG06561) to estimate the unobserved pre-culture replicative-history offset; it is not the final 87-CpG RepliTali model.
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|---|---|
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| **Predicts** | replicative history |
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| **Species** | Homo sapiens |
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| **Tissue** | cultured fibroblasts |
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| **Data type** | DNA methylation |
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| **Model type** | elastic net regression |
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| **Year** | 2022 |
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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, ["replitalinorm"])
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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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Endicott, J.L., Nolte, P.A., Shen, H. & Laird, P.W. Cell division drives DNA methylation loss in late-replicating domains in primary human cells. Nature Communications 13, 6659 (2022).
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https://doi.org/10.1038/s41467-022-34268-8
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config.json
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{
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"approved_by_author": "\u231b",
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"citation": "Endicott, J.L., Nolte, P.A., Shen, H. & Laird, P.W. Cell division drives DNA methylation loss in late-replicating domains in primary human cells. Nature Communications 13, 6659 (2022).",
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"citations": 86,
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"citations_date": "2026-07-05",
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"clock_name": "replitalinorm",
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"data_type": "DNA methylation",
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"doi": "https://doi.org/10.1038/s41467-022-34268-8",
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"journal": "Nature Communications",
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"last_author": "Peter W. Laird",
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"model_type": "elastic net regression",
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"n_features": 218,
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"notes": "Upstream starting-PD normalization model used during RepliTali construction. It was trained only in the chronologically youngest fetal skin fibroblast line (AG06561) to estimate the unobserved pre-culture replicative-history offset; it is not the final 87-CpG RepliTali model.",
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"platform": [
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"Illumina EPIC"
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],
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"population": "human cell cultures",
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"predicts": [
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"replicative history"
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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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"cultured fibroblasts"
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],
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"training_target": [
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"population doublings"
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],
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"unit": [
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"population doublings"
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],
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"version": "v0.3.0",
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"year": 2022
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}
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replitalinorm.pt
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version https://git-lfs.github.com/spec/v1
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oid sha256:46f56ccc429b2a1343ea61be98415f27128458cfe96079d06e2b0974bf81234c
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size 10661
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