epitoc3 / config.json
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{
"approved_by_author": "\u231b",
"citation": "Teschendorff, Andrew E. \"A comparison of epigenetic mitotic-like clocks for cancer risk prediction.\" Genome Medicine 12 (2020): 56.",
"citations": 155,
"citations_date": "2026-07-05",
"clock_name": "epitoc3",
"data_type": "DNA methylation",
"doi": "https://doi.org/10.1186/s13073-020-00752-3",
"journal": "Genome Medicine",
"last_author": "Andrew E. Teschendorff",
"model_type": "dynamic methylation transmission model",
"n_features": 170,
"notes": "Code-defined 170-CpG extension of the dynamic mitotic model. Official EpiMitClocks data show that all 170 sites are a subset of the 371 stemTOC vivo-mitCpGs derived from fetal/neonatal references, six normal proliferating cell lines, and three adult whole-blood cohorts. The assigned 2020 dynamic-model paper does not name or define epiTOC3.",
"platform": [
"Illumina 450K",
"Illumina EPIC"
],
"population": "all ages",
"predicts": [
"mitotic age"
],
"preprocess": "nan_to_zero",
"reference_values": true,
"research_only": null,
"species": "Homo sapiens",
"tissue": [
"cultured primary human cells",
"whole blood",
"multi-tissue",
"cord blood"
],
"training_target": [
"population doublings"
],
"unit": [
"cell divisions per stem cell"
],
"version": "0.5.0",
"year": 2020
}