| { | |
| "approved_by_author": "\u231b", | |
| "citation": "Higgins-Chen, Albert T., et al. \"A computational solution for bolstering reliability of epigenetic clocks: implications for clinical trials and longitudinal tracking.\" Nature Aging 2 (2022): 644\u2013661.", | |
| "citations": 546, | |
| "citations_date": "2026-10-02", | |
| "clock_name": "pcdnamtl", | |
| "data_type": "DNA methylation", | |
| "doi": "https://doi.org/10.1038/s43587-022-00248-2", | |
| "journal": "Nature Aging", | |
| "last_author": "Morgan E. Levine", | |
| "model_type": "PCA + elastic net regression", | |
| "n_features": 78464, | |
| "notes": "Principal-component proxy trained to reproduce the original DNAmTL clock output; the returned score remains in kilobases. Figure-level base-pair deviations are a separate analysis-scale conversion.", | |
| "platform": [ | |
| "Illumina 450K" | |
| ], | |
| "population": "adults", | |
| "predicts": [ | |
| "leukocyte telomere length" | |
| ], | |
| "reference_values": true, | |
| "research_only": null, | |
| "species": "Homo sapiens", | |
| "tissue": [ | |
| "whole blood" | |
| ], | |
| "training_target": [ | |
| "DNAmTL output" | |
| ], | |
| "unit": [ | |
| "kilobases" | |
| ], | |
| "version": "0.5.7", | |
| "year": 2022 | |
| } |