Clock catalogue
All 178, generated from the registry that scores them
This page is written from the registry the package ships, so it cannot describe a catalogue different from the one that scores. Every column below is a field the scoring code reads.
scale_type is the load-bearing one. It is not a label: it decides which downstream operations FALCONAge will perform, and asking for age acceleration on a pace_ratio clock is refused rather than computed.
178 clocks, registry schema 1.1.0.
Availability is about provenance, not about quality. A bundled clock has a coefficient file whose origin was followed back to the paper or its supplement and checksummed, so the same numbers come out on any machine with no network. An untraced clock has no public source for its coefficients, and a licensed one has a source whose terms do not permit redistribution. Copying a coefficient vector out of another package would move clocks into the bundled column and is the one route not taken here, because a number with no source behind it cannot be checked against anything.
Bundled: 69 clocks
Coefficients ship with the package, or the clock is a formula with none to ship. Works offline, no network, no licence.
| Clock | Year | Predicts | Scale | Features | Tissue | Platform | Paper |
|---|---|---|---|---|---|---|---|
altumage |
2022 | chronological age | age_years |
20318 | multi-tissue | 27K, 450K | de Lima Camillo 2022 |
bohlin |
2016 | gestational age | gestational_weeks |
96 | cord blood | 450K | Bohlin 2016 |
cage |
2023 | chronological age | age_years |
3225 | whole blood | 450K, EPICv1 | Bernabeu 2023 |
cellpopage |
2024 | cell-population passage age | relative_score |
42 | cultured fibroblasts | EPICv1 | Lujan 2024 |
corticalclock |
2020 | chronological age | age_years |
347 | brain cortex | 450K | Shireby 2020 |
deconvolutebloodepicbcell |
2018 | B cell proportion | proportion |
450 | whole blood | 450K, EPICv1 | Salas 2018 |
deconvolutebloodepiccd4tcell |
2018 | CD4+ T cell proportion | proportion |
450 | whole blood | 450K, EPICv1 | Salas 2018 |
deconvolutebloodepiccd8tcell |
2018 | CD8+ T cell proportion | proportion |
450 | whole blood | 450K, EPICv1 | Salas 2018 |
deconvolutebloodepicmonocyte |
2018 | monocyte proportion | proportion |
450 | whole blood | 450K, EPICv1 | Salas 2018 |
deconvolutebloodepicneutrophil |
2018 | neutrophil proportion | proportion |
450 | whole blood | 450K, EPICv1 | Salas 2018 |
deconvolutebloodepicnkcell |
2018 | natural killer cell proportion | proportion |
450 | whole blood | 450K, EPICv1 | Salas 2018 |
depressionbarbu |
2021 | major depressive disorder | relative_score |
196 | whole blood | EPICv1 | Barbu 2021 |
dnamfili |
2022 | frailty risk | relative_score |
20 | whole blood | EPICv1, 450K | Li 2022 |
dnamic |
2025 | intrinsic capacity | relative_score |
91 | whole blood | EPICv1 | Fuentealba 2025 |
dnamphenoage |
2018 | phenotypic age | age_years |
513 | whole blood | 27K, 450K, EPICv1 | Levine 2018 |
dnamstress |
2023 | stress exposure | relative_score |
211 | whole blood | EPICv1 | Jung 2023 |
dnamtl |
2019 | leukocyte telomere length | telomere_kb |
140 | whole blood | 450K, EPICv1 | Lu 2019 |
downsyndrome |
2021 | Down syndrome methylation score | relative_score |
652 | neonatal blood spots | EPICv1 | Muskens 2021 |
dunedinpoam38 |
2020 | pace of aging | pace_ratio |
46 | whole blood | 450K | Belsky 2020 |
epicmithyper |
2020 | mitotic age | divisions |
184 | B cells | 450K, EPICv1 | Duran-Ferrer 2020 |
epicmithypo |
2020 | mitotic age | divisions |
1164 | B cells | 450K, EPICv1 | Duran-Ferrer 2020 |
epitoc1 |
2016 | mitotic age | divisions |
385 | multi-tissue, whole blood | 450K | Yang 2016 |
epitoc2 |
2020 | mitotic age | divisions |
163 | whole blood | 450K | Teschendorff 2020 |
epitoc3 |
2020 | mitotic age | divisions |
170 | cultured primary human cells, whole blood, multi-tissue, cord blood | 450K, EPICv1 | Teschendorff 2020 |
hannum |
2013 | chronological age | age_years |
71 | whole blood | 450K | Hannum 2013 |
hd |
2013 | physiological dysregulation | relative_score |
— | blood | clinical laboratory assays | Cohen 2013 |
horvath2013 |
2013 | chronological age | age_years |
353 | multi-tissue | 27K, 450K | Horvath 2013 |
hrsinchphenoage |
2022 | phenotypic age | age_years |
959 | whole blood | 450K, EPICv1 | Higgins-Chen 2022 |
hypoclock |
2020 | mitotic age | divisions |
678 | multi-tissue | 450K | Teschendorff 2020 |
intrinclock |
2024 | chronological age | age_years |
370 | multi-tissue | 450K, EPICv1 | Tomusiak 2024 |
kdm |
2006 | biological age | age_years |
— | blood | clinical laboratory assays | Klemera 2006 |
knight |
2016 | gestational age | gestational_weeks |
148 | cord blood, neonatal blood spots | 27K, 450K | Knight 2016 |
leecontrol |
2019 | gestational age | gestational_weeks |
546 | placenta | 450K, EPICv1 | Lee 2019 |
leerefinedrobust |
2019 | gestational age | gestational_weeks |
395 | placenta | 450K, EPICv1 | Lee 2019 |
leerobust |
2019 | gestational age | gestational_weeks |
558 | placenta | 450K, EPICv1 | Lee 2019 |
lin |
2016 | chronological age | age_years |
99 | whole blood | 27K, 450K | Lin 2016 |
linage2 |
2025 | mortality risk | age_years |
59 | blood | clinical laboratory assays | Fong 2025 |
mayne |
2017 | gestational age | gestational_weeks |
62 | placenta | 27K, 450K | Mayne 2017 |
mccartneyalcohol |
2018 | alcohol consumption | gestational_weeks |
450 | whole blood | EPICv1 | McCartney 2018 |
mccartneybmi |
2018 | body mass index | relative_score |
1109 | whole blood | EPICv1 | McCartney 2018 |
mccartneybodyfat |
2018 | body fat percentage | relative_score |
968 | whole blood | EPICv1 | McCartney 2018 |
mccartneyeducation |
2018 | educational attainment | relative_score |
373 | whole blood | EPICv1 | McCartney 2018 |
mccartneyhdlcholesterol |
2018 | HDL cholesterol | relative_score |
737 | whole blood | EPICv1 | McCartney 2018 |
mccartneyldlcholesterol |
2018 | LDL cholesterol | relative_score |
233 | whole blood | EPICv1 | McCartney 2018 |
mccartneysmoking |
2018 | smoking exposure | relative_score |
233 | whole blood | EPICv1 | McCartney 2018 |
mccartneytotalcholesterol |
2018 | total cholesterol | relative_score |
204 | whole blood | EPICv1 | McCartney 2018 |
mccartneytotalhdlratio |
2018 | total-to-HDL cholesterol ratio | relative_score |
412 | whole blood | EPICv1 | McCartney 2018 |
mccartneywhr |
2018 | waist-to-hip ratio | relative_score |
226 | whole blood | EPICv1 | McCartney 2018 |
meer |
2018 | chronological age | age_years |
435 | multi-tissue | RRBS | Meer 2018 |
metaboage |
2020 | chronological age | age_years |
56 | blood | Nightingale Health 1H-NMR | van den Akker 2020 |
metabohealth |
2019 | mortality | mortality_log_hazard |
14 | blood | Nightingale Health 1H-NMR | Deelen 2019 |
pedbe |
2020 | chronological age | age_years |
94 | buccal epithelium | 450K, EPICv1 | McEwen 2020 |
phenoage |
2018 | phenotypic age | age_years |
10 | blood | clinical laboratory assays | Levine 2018 |
prostatecancerkirby |
2017 | prostate cancer | relative_score |
3 | prostate | 450K | Kirby 2017 |
replitali |
2022 | replicative history | divisions |
87 | cultured primary human cells | EPICv1 | Endicott 2022 |
skinandblood |
2018 | chronological age | age_years |
391 | buccal epithelium, whole blood, epithelium, cultured fibroblasts, skin, cord blood | 450K, EPICv1 | Horvath 2018 |
stemtoc |
2024 | mitotic age | divisions |
371 | multi-tissue, cultured human cells, whole blood | 450K, EPICv1 | Zhu 2024 |
stemtocvitro |
2024 | mitotic age | divisions |
629 | multi-tissue, cultured human cells | 450K, EPICv1 | Zhu 2024 |
stoch |
2024 | chronological age | age_years |
353 | sorted monocytes | 450K | Tong 2024 |
stocp |
2024 | chronological age | age_years |
513 | sorted monocytes | 450K | Tong 2024 |
stocz |
2024 | chronological age | age_years |
514 | sorted monocytes | 450K | Tong 2024 |
vidalbralo |
2016 | chronological age | age_years |
8 | whole blood | 27K | Vidal-Bralo 2016 |
weidner |
2014 | chronological age | age_years |
3 | whole blood | 27K, bisulfite sequencing | Weidner 2014 |
yingadaptage |
2024 | adaptive epigenetic age | age_years_relative |
999 | whole blood | 450K | Ying 2024 |
yingcausage |
2024 | chronological age | age_years |
585 | whole blood | 450K | Ying 2024 |
yingdamage |
2024 | damaging epigenetic age | age_years_relative |
1089 | whole blood | 450K | Ying 2024 |
zhangblup |
2019 | chronological age | age_years |
319607 | whole blood, saliva | 450K, EPICv1 | Zhang 2019 |
zhangen |
2019 | chronological age | age_years |
514 | whole blood, saliva | 450K, EPICv1 | Zhang 2019 |
zhangmortality |
2017 | mortality risk | mortality_log_hazard |
10 | whole blood | 450K | Zhang 2017 |
Untraced: 52 clocks
Catalogued, but no primary source for the coefficients has been established, so nothing is bundled. The metadata is real; the numbers are absent.
| Clock | Year | Predicts | Scale | Features | Tissue | Platform | Paper |
|---|---|---|---|---|---|---|---|
abec |
2020 | chronological age | age_years |
— | whole blood | EPICv1 | Lee 2020 |
adbahadosingh |
2021 | late-onset Alzheimer’s disease | relative_score |
— | whole blood | EPICv1 | Bahado-Singh 2021 |
bocklandt |
2011 | EDARADD methylation | relative_score |
— | saliva | 27K | Bocklandt 2011 |
cabec |
2020 | chronological age | age_years |
— | whole blood | 450K, EPICv1 | Lee 2020 |
compil6 |
2021 | interleukin-6 | relative_score |
— | whole blood | 450K | Stevenson 2021 |
ctsliver |
2024 | chronological age | age_years |
— | liver | EPICv1 | Tong 2024 |
cvdwesterman |
2020 | cardiovascular disease risk | relative_score |
— | whole blood | 450K | Westerman 2020 |
dnamfitage |
2023 | physical-fitness biological age | age_years |
— | whole blood | 450K | McGreevy 2023 |
dnamfitagegaitf |
2023 | gait speed | relative_score |
— | whole blood | 450K | McGreevy 2023 |
dnamfitagegaitm |
2023 | gait speed | relative_score |
— | whole blood | 450K | McGreevy 2023 |
dnamfitagegripf |
2023 | grip strength | relative_score |
— | whole blood | 450K | McGreevy 2023 |
dnamfitagegripm |
2023 | grip strength | relative_score |
— | whole blood | 450K | McGreevy 2023 |
dnamfitagevo2max |
2023 | VO2max | relative_score |
— | whole blood | 450K | McGreevy 2023 |
eabec |
2020 | chronological age | age_years |
— | whole blood | EPICv1 | Lee 2020 |
encen100 |
2023 | chronological age | age_years |
— | whole blood, saliva, buccal epithelium | 450K, EPICv1 | Dec 2023 |
encen40 |
2023 | chronological age | age_years |
— | whole blood, saliva, buccal epithelium | 450K, EPICv1 | Dec 2023 |
ensembleagehumanmouse |
2025 | relative age | relative_score |
— | multi-tissue, whole blood | mammalian methylation array | Haghani 2025 |
ensembleagestatic |
2025 | intervention-responsive epigenetic age | age_years |
— | multi-tissue | Horvath MammalMethylChip40, Horvath MammalMethylChip320 | Haghani 2025 |
ensembleagestatictop |
2025 | intervention-responsive epigenetic age | age_years |
— | multi-tissue | Horvath MammalMethylChip40, Horvath MammalMethylChip320 | Haghani 2025 |
epicga |
2021 | gestational age | gestational_weeks |
— | cord blood | EPICv1 | Haftorn 2021 |
fiage |
2025 | frailty index | relative_score |
53 | whole blood | EPICv1 | no primary source traced, catalogued at |
garagnani |
2012 | ELOVL2 methylation | relative_score |
— | whole blood | 450K | Garagnani 2012 |
gliasin |
2024 | chronological age | age_years |
— | brain cortex | 450K | Tong 2024 |
han |
2020 | chronological age | age_years |
— | whole blood | 450K | Han 2020 |
hep |
2024 | chronological age | age_years |
— | liver | EPICv1 | Tong 2024 |
hepatoxu |
2017 | hepatocellular carcinoma | relative_score |
— | plasma cell-free DNA | targeted bisulfite sequencing | Xu 2017 |
mammalian1 |
2023 | chronological age | age_years |
— | multi-tissue | Horvath MammalMethylChip40 | Lu 2023 |
mammalian2 |
2023 | chronological age | age_years |
— | multi-tissue | Horvath MammalMethylChip40 | Lu 2023 |
mammalian3 |
2023 | chronological age | age_years |
— | multi-tissue | Horvath MammalMethylChip40 | Lu 2023 |
mammalianblood2 |
2023 | chronological age | age_years |
— | blood | Horvath MammalMethylChip40 | Lu 2023 |
mammalianblood3 |
2023 | chronological age | age_years |
— | blood | Horvath MammalMethylChip40 | Lu 2023 |
mammalianfemale |
2023 | sex | relative_score |
— | multi-tissue | mammalian methylation array | Li 2023 |
mammalianlifespan |
2024 | species maximum lifespan | age_years |
— | multi-tissue | Horvath MammalMethylChip40 | Li 2024 |
mammalianskin2 |
2023 | chronological age | age_years |
— | skin | Horvath MammalMethylChip40 | Lu 2023 |
mammalianskin3 |
2023 | chronological age | age_years |
— | skin | Horvath MammalMethylChip40 | Lu 2023 |
neusin |
2024 | chronological age | age_years |
— | brain cortex | 450K | Tong 2024 |
petkovich |
2017 | chronological age | age_years |
— | whole blood | bisulfite sequencing | Petkovich 2017 |
pipekelasticnet |
2022 | chronological age | age_years |
— | multi-tissue | 27K, 450K, EPICv1 | Pipek 2022 |
pipekfilteredh |
2022 | chronological age | age_years |
— | multi-tissue | 27K, 450K, EPICv1 | Pipek 2022 |
pipekretrainedh |
2022 | chronological age | age_years |
— | multi-tissue | 27K, 450K, EPICv1 | Pipek 2022 |
reedbmi |
2020 | BMI methylation score | relative_score |
— | whole blood, cord blood | 450K | Reed 2020 |
replitalinorm |
2022 | replicative history | divisions |
— | cultured fibroblasts | EPICv1 | Endicott 2022 |
retroelementagev1 |
2024 | chronological age | age_years |
— | whole blood | EPICv1 | Ndhlovu 2024 |
retroelementagev2 |
2024 | chronological age | age_years |
— | whole blood | EPICv1 | Ndhlovu 2024 |
senchronoage |
2026 | chronological age | age_years |
— | whole blood | 450K, EPICv1 | Kasamoto 2026 |
sencultureage |
2026 | cellular senescence | relative_score |
— | cultured fibroblasts, cultured mesenchymal stromal cells | 450K, EPICv1 | Kasamoto 2026 |
senmortalityage |
2026 | mortality risk | mortality_log_hazard |
— | whole blood | 450K, EPICv1 | Kasamoto 2026 |
stubbs |
2017 | chronological age | age_years |
— | multi-tissue, liver, lung, heart, brain cortex, skeletal muscle, cerebellum, spleen | RRBS | Stubbs 2017 |
thompson |
2018 | chronological age | age_years |
— | adipose tissue, blood, cerebellum, brain cortex, heart, kidney, liver, lung, skeletal muscle, spleen | RRBS | Thompson 2018 |
wu |
2019 | chronological age | age_years |
— | whole blood | 27K, 450K | Wu 2019 |
xchrom |
2021 | X-chromosome dosage | relative_score |
— | whole blood | 450K, EPICv1 | Wang 2021 |
ychrom |
2021 | Y-chromosome presence | relative_score |
— | whole blood | 450K, EPICv1 | Wang 2021 |
Licensed: 57 clocks
The architecture is implemented and tested; the coefficients are research-use-only and are not ours to distribute. Obtain a file and register it.
| Clock | Year | Predicts | Scale | Features | Tissue | Platform | Paper |
|---|---|---|---|---|---|---|---|
cpgptgrimage3 |
2024 | biological age | age_years |
— | whole blood | 450K | de Lima Camillo 2024 |
cpgptpcgrimage3 |
2024 | biological age | age_years |
— | whole blood | 450K | de Lima Camillo 2024 |
dnamemrage |
2026 | electronic medical record age | age_years |
— | whole blood | 450K, EPICv1 | Chen 2026 |
dunedinpace |
2022 | pace of aging | pace_ratio |
— | whole blood | EPICv1 | Belsky 2022 |
grimage |
2019 | mortality risk | age_years |
— | whole blood | 450K | Lu 2019 |
grimage2 |
2022 | mortality risk | age_years |
— | whole blood | 450K | Lu 2022 |
grimage2adm |
2022 | adrenomedullin | relative_score |
— | whole blood | 450K | Lu 2022 |
grimage2b2m |
2022 | beta-2-microglobulin | relative_score |
— | whole blood | 450K | Lu 2022 |
grimage2cystatinc |
2022 | cystatin C | relative_score |
— | whole blood | 450K | Lu 2022 |
grimage2gdf15 |
2022 | GDF-15 | relative_score |
— | whole blood | 450K | Lu 2022 |
grimage2leptin |
2022 | leptin | relative_score |
— | whole blood | 450K | Lu 2022 |
grimage2loga1c |
2022 | hemoglobin A1c | relative_score |
— | whole blood | 450K | Lu 2022 |
grimage2logcrp |
2022 | C-reactive protein | relative_score |
— | whole blood | 450K | Lu 2022 |
grimage2packyrs |
2022 | smoking exposure | relative_score |
— | whole blood | 450K | Lu 2022 |
grimage2pai1 |
2022 | PAI-1 | relative_score |
— | whole blood | 450K | Lu 2022 |
grimage2timp1 |
2022 | TIMP-1 | relative_score |
— | whole blood | 450K | Lu 2022 |
omicmage |
2026 | biological age | age_years |
— | whole blood | 450K, EPICv1 | Chen 2026 |
pcdnamtl |
2022 | leukocyte telomere length | telomere_kb |
— | whole blood | 450K | Higgins-Chen 2022 |
pcgrimage |
2022 | mortality risk | age_years |
— | whole blood | 450K | Higgins-Chen 2022 |
pcgrimageadm |
2022 | adrenomedullin | relative_score |
— | whole blood | 450K, EPICv1 | Higgins-Chen 2022 |
pcgrimageb2m |
2022 | beta-2 microglobulin | relative_score |
— | whole blood | 450K, EPICv1 | Higgins-Chen 2022 |
pcgrimagecystatinc |
2022 | cystatin C | relative_score |
— | whole blood | 450K, EPICv1 | Higgins-Chen 2022 |
pcgrimagegdf15 |
2022 | growth differentiation factor 15 | relative_score |
— | whole blood | 450K, EPICv1 | Higgins-Chen 2022 |
pcgrimageleptin |
2022 | leptin | relative_score |
— | whole blood | 450K, EPICv1 | Higgins-Chen 2022 |
pcgrimagepackyrs |
2022 | smoking pack-years | relative_score |
— | whole blood | 450K, EPICv1 | Higgins-Chen 2022 |
pcgrimagepai1 |
2022 | plasminogen activator inhibitor 1 | relative_score |
— | whole blood | 450K, EPICv1 | Higgins-Chen 2022 |
pcgrimagetimp1 |
2022 | TIMP metallopeptidase inhibitor 1 | relative_score |
— | whole blood | 450K, EPICv1 | Higgins-Chen 2022 |
pchannum |
2022 | chronological age | age_years |
— | whole blood | 450K | Higgins-Chen 2022 |
pchorvath2013 |
2022 | chronological age | age_years |
— | multi-tissue | 450K, EPICv1 | Higgins-Chen 2022 |
pcphenoage |
2022 | phenotypic age | age_years |
— | whole blood | 450K, EPICv1 | Higgins-Chen 2022 |
pcskinandblood |
2022 | chronological age | age_years |
— | skin, whole blood, cultured fibroblasts | 450K, EPICv1 | Higgins-Chen 2022 |
retroclock |
2025 | retroelement methylation age | age_years |
— | whole blood | 450K, EPICv1 | Sehgal 2025 |
systemsage |
2025 | multisystem biological age | age_years |
— | whole blood | 450K, EPICv1 | Sehgal 2025 |
systemsageageprediction |
2025 | chronological age | age_years |
— | whole blood | 450K, EPICv1 | Sehgal 2025 |
systemsageblood |
2025 | blood-system biological age | age_years |
— | whole blood | 450K, EPICv1 | Sehgal 2025 |
systemsagebrain |
2025 | brain-system biological age | age_years |
— | whole blood | 450K, EPICv1 | Sehgal 2025 |
systemsageheart |
2025 | cardiovascular-system biological age | age_years |
— | whole blood | 450K, EPICv1 | Sehgal 2025 |
systemsagehormone |
2025 | endocrine-system biological age | age_years |
— | whole blood | 450K, EPICv1 | Sehgal 2025 |
systemsageimmune |
2025 | immune-system biological age | age_years |
— | whole blood | 450K, EPICv1 | Sehgal 2025 |
systemsageinflammation |
2025 | inflammatory-system biological age | age_years |
— | whole blood | 450K, EPICv1 | Sehgal 2025 |
systemsagekidney |
2025 | renal-system biological age | age_years |
— | whole blood | 450K, EPICv1 | Sehgal 2025 |
systemsageliver |
2025 | hepatic-system biological age | age_years |
— | whole blood | 450K, EPICv1 | Sehgal 2025 |
systemsagelung |
2025 | pulmonary-system biological age | age_years |
— | whole blood | 450K, EPICv1 | Sehgal 2025 |
systemsagemetabolic |
2025 | metabolic-system biological age | age_years |
— | whole blood | 450K, EPICv1 | Sehgal 2025 |
systemsagemusculoskeletal |
2025 | musculoskeletal-system biological age | age_years |
— | whole blood | 450K, EPICv1 | Sehgal 2025 |
twelvecelldeconvolutebloodepicbas |
2022 | basophil proportion | proportion |
— | purified blood leukocytes | EPICv1 | Salas 2022 |
twelvecelldeconvolutebloodepicbmem |
2022 | memory B cell proportion | proportion |
— | purified blood leukocytes | EPICv1 | Salas 2022 |
twelvecelldeconvolutebloodepicbnv |
2022 | naive B cell proportion | proportion |
— | purified blood leukocytes | EPICv1 | Salas 2022 |
twelvecelldeconvolutebloodepiccd4mem |
2022 | memory CD4+ T cell proportion | proportion |
— | purified blood leukocytes | EPICv1 | Salas 2022 |
twelvecelldeconvolutebloodepiccd4nv |
2022 | naive CD4+ T cell proportion | proportion |
— | purified blood leukocytes | EPICv1 | Salas 2022 |
twelvecelldeconvolutebloodepiccd8mem |
2022 | memory CD8+ T cell proportion | proportion |
— | purified blood leukocytes | EPICv1 | Salas 2022 |
twelvecelldeconvolutebloodepiccd8nv |
2022 | naive CD8+ T cell proportion | proportion |
— | purified blood leukocytes | EPICv1 | Salas 2022 |
twelvecelldeconvolutebloodepiceos |
2022 | eosinophil proportion | proportion |
— | purified blood leukocytes | EPICv1 | Salas 2022 |
twelvecelldeconvolutebloodepicmono |
2022 | monocyte proportion | proportion |
— | purified blood leukocytes | EPICv1 | Salas 2022 |
twelvecelldeconvolutebloodepicneu |
2022 | neutrophil proportion | proportion |
— | purified blood leukocytes | EPICv1 | Salas 2022 |
twelvecelldeconvolutebloodepicnk |
2022 | natural killer cell proportion | proportion |
— | purified blood leukocytes | EPICv1 | Salas 2022 |
twelvecelldeconvolutebloodepictreg |
2022 | regulatory T-cell proportion | proportion |
— | purified blood leukocytes | EPICv1 | Salas 2022 |
Querying it from code
reg = fa.registry.load()
reg.filter(availability="bundled", scale_type="age_years")
reg.search("mortality")
reg.compatible_with(data)
reg.get("horvath2013")list_clocks(tier = "bundled")
list_clocks(search = "mortality")
compatible_clocks(d)
clock_info("horvath2013")