Sync adbahadosingh

README.md

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+---
+license: bsd-3-clause
+library_name: pyaging
+tags:
+- pyaging
+- aging-clock
+- biology
+- dna-methylation
+---
+
+# adbahadosingh
+
+PyAging implements the paper’s conventional four-CpG logistic-regression equation and applies a sigmoid to return LOAD case probability; it does not implement the separate high-dimensional deep-learning classifiers also evaluated in the paper.
+
+| | |
+|---|---|
+| **Predicts** | late-onset Alzheimer's disease |
+| **Species** | Homo sapiens |
+| **Tissue** | whole blood |
+| **Data type** | DNA methylation |
+| **Model type** | logistic regression |
+| **Year** | 2021 |
+
+## Use with pyaging
+
+```python
+import pyaging as pya
+
+pya.pred.predict_age(adata, ["adbahadosingh"])
+```
+
+Browse every clock in the [pyaging Clock Catalogue](https://pyaging.readthedocs.io).
+
+## Citation
+
+Bahado-Singh, R. O., Vishweswaraiah, S., Aydas, B., et al. (2021). Artificial intelligence and leukocyte epigenomics: Evaluation and prediction of late-onset Alzheimer's disease. PLOS ONE, 16(4), e0248375.
+
+https://doi.org/10.1371/journal.pone.0248375

adbahadosingh.pt

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+oid sha256:43502e4a45b0d8113617641a3e3d3cfae8541a9c7d438b11c4f8ddc1dfd28b1d
+size 4837

config.json

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+{
+ "approved_by_author": "\u231b",
+ "citation": "Bahado-Singh, R. O., Vishweswaraiah, S., Aydas, B., et al. (2021). Artificial intelligence and leukocyte epigenomics: Evaluation and prediction of late-onset Alzheimer's disease. PLOS ONE, 16(4), e0248375.",
+ "citations": 33,
+ "citations_date": "2026-07-05",
+ "clock_name": "adbahadosingh",
+ "data_type": "DNA methylation",
+ "doi": "https://doi.org/10.1371/journal.pone.0248375",
+ "journal": "PLOS ONE",
+ "last_author": "Uppala Radhakrishna",
+ "model_type": "logistic regression",
+ "n_features": 4,
+ "notes": "PyAging implements the paper\u2019s conventional four-CpG logistic-regression equation and applies a sigmoid to return LOAD case probability; it does not implement the separate high-dimensional deep-learning classifiers also evaluated in the paper.",
+ "platform": [
+  "Illumina EPIC"
+ ],
+ "population": "older adults",
+ "postprocess": "sigmoid",
+ "predicts": [
+  "late-onset Alzheimer's disease"
+ ],
+ "research_only": null,
+ "species": "Homo sapiens",
+ "tissue": [
+  "whole blood"
+ ],
+ "training_target": [
+  "late-onset Alzheimer's disease"
+ ],
+ "unit": [
+  "probability"
+ ],
+ "version": "v0.3.0",
+ "year": 2021
+}