Evidence map›Paper›PMID 34053192›Full record

ArticleMolecular ecology resources2021

Optimal sample size for calibrating DNA methylation age estimators.

Benjamin Mayne, Oliver Berry, Simon Jarman

Open access · hybridAbstract read
In one paragraph

Article in Molecular ecology resources, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 25 papers.

0numbers the graph read from it
0cells of the map it votes in
25citing papers in PubMed
2.1field-weighted citation impact, top 12% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

25 citing papers in PubMed, 41 citations in OpenAlex.

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  13. Estimating Polar Bear (Ecology and evolution · 2025
    Article
  14. Article
  15. A Sex-Specific Minimal CpG-Based Model for Biological Aging UsingInternational journal of molecular sciences · 2025
    Article
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

3 authors at 2 institutions in 1 country.

Benjamin MayneEnvironomics Future Science Platform, Indian Ocean Marine Research Centre, Commonwealth Scientific and Industrial Research Organisation (CSIRO), Crawley, WA, Australia.ORCID https://orcid.org/0000-0002-6750-8832
Oliver BerryEnvironomics Future Science Platform, Indian Ocean Marine Research Centre, Commonwealth Scientific and Industrial Research Organisation (CSIRO), Crawley, WA, Australia.ORCID https://orcid.org/0000-0001-7545-5083
Simon JarmanSchool of Biological Sciences, The University of Western Australia, Perth, WA, Australia.
Commonwealth Scientific and Industrial Research Organisation · AUThe University of Western Australia · AU

Funding

CSIRO
6 · The paper itself

Abstract

Age is a fundamental parameter in wildlife management as it is used to determine the risk of extinction, manage invasive species, and regulate sustainable harvest. In a broad variety of vertebrates species, age can be determined by measuring DNA methylation. Animals with known ages are initially required during development, calibration, and validation of these epigenetic clocks. However, wild animals with known ages are frequently difficult to obtain. Here, we perform Monte-Carlo simulations to determine the optimal sample size required to create an accurate calibration model for age estimation by elastic net regression modelling of cytosine-phosphate-guanine methylation data. Our results suggest a minimum calibration population size of 70, but ideally 134 individuals or more for accurate and precise models. We also provide estimates to the extent a model can be extrapolated beyond a distribution of ages that was used during calibration. The findings can assist researchers to better design age estimation models and decide if their model is adequate for determining key population attributes.

Indexed as

DNA MethylationEpigenesis, GeneticAnimalsEpigenomicsHumansMonte Carlo MethodSample Sizeage estimationDNA methylationepigenetic clocksample sizewildlife

Identifiers

PMID34053192
PMCPMC8518423
OpenAlexW3165610706

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.