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Sync bohlin

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  1. README.md +38 -0
  2. bohlin.pt +3 -0
  3. config.json +35 -0
README.md ADDED
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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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+
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+ # bohlin
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+
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+ Official minimum-lambda variant of the Bohlin gestational-age LASSO: pyaging implements the 251-CpG lambda.min model and converts its day-scale output to weeks. The paper/package default one-standard-error variant uses 96 CpGs and has nearly identical predictive performance.
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+
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+ | | |
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+ |---|---|
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+ | **Predicts** | gestational age |
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+ | **Species** | Homo sapiens |
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+ | **Tissue** | cord blood |
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+ | **Data type** | DNA methylation |
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+ | **Model type** | LASSO regression |
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+ | **Year** | 2016 |
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+
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+ ## Use with pyaging
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+
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+ ```python
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+ import pyaging as pya
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+
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+ pya.pred.predict_age(adata, ["bohlin"])
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+ ```
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+
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+ Browse every clock in the [pyaging Clock Catalogue](https://pyaging.readthedocs.io).
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+
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+ ## Citation
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+
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+ Bohlin, J., Håberg, S. E., Magnus, P. et al. Prediction of gestational age based on genome-wide differentially methylated regions. Genome Biology 17, 207 (2016).
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+
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+ https://doi.org/10.1186/s13059-016-1063-4
bohlin.pt ADDED
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+ version https://git-lfs.github.com/spec/v1
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+ oid sha256:769d600b7294ac7030df139f8aa3b0d444b9eb2dc839cb1f8bd37095acdc9a19
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+ size 11493
config.json ADDED
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+ {
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+ "approved_by_author": "\u231b",
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+ "citation": "Bohlin, J., H\u00e5berg, S. E., Magnus, P. et al. Prediction of gestational age based on genome-wide differentially methylated regions. Genome Biology 17, 207 (2016).",
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+ "citations": 237,
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+ "citations_date": "2026-07-05",
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+ "clock_name": "bohlin",
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+ "data_type": "DNA methylation",
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+ "doi": "https://doi.org/10.1186/s13059-016-1063-4",
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+ "journal": "Genome Biology",
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+ "last_author": "Wenche Nystad",
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+ "model_type": "LASSO regression",
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+ "n_features": 251,
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+ "notes": "Official minimum-lambda variant of the Bohlin gestational-age LASSO: pyaging implements the 251-CpG lambda.min model and converts its day-scale output to weeks. The paper/package default one-standard-error variant uses 96 CpGs and has nearly identical predictive performance.",
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+ "platform": [
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+ "Illumina 450K"
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+ ],
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+ "population": "newborns",
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+ "postprocess": "days_to_weeks",
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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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+ "cord blood"
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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": 2016
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+ }