Evidence map›Paper›PMID 36046618›Full record

ArticleCell reports methods2022

Temporal population structure, a genetic dating method for ancient Eurasian genomes from the past 10,000 years.

Sara Behnamian, Umberto Esposito, Grace Holland, Ghadeer Alshehab, Ann M Dobre, Mehdi Pirooznia, Conrad S Brimacombe, Eran Elhaik

Abstract read
In one paragraph

Article in Cell reports methods, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
–field-weighted citation impact
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

2 citing papers in PubMed.

  1. Article
  2. Article
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

8 authors.

Sara BehnamianDepartment of Biology, Lund University, 22362 Lund, Sweden.
Umberto EspositoDepartment of Animal and Plant Sciences, University of Sheffield, Sheffield S10 2TN, UK.
Grace HollandDepartment of Animal and Plant Sciences, University of Sheffield, Sheffield S10 2TN, UK.
Ghadeer AlshehabDepartment of Automatic Control and Systems Engineering, University of Sheffield, Sheffield S1 3JD, UK.
Ann M DobreDepartment of Animal and Plant Sciences, University of Sheffield, Sheffield S10 2TN, UK.
Mehdi PiroozniaNational Heart, Lung, and Blood Institute (NHLBI), Bethesda, MD 20892, USA.
Conrad S BrimacombeDepartment of Animal and Plant Sciences, University of Sheffield, Sheffield S10 2TN, UK.
Eran ElhaikDepartment of Biology, Lund University, 22362 Lund, Sweden.

Funding

Medical Research Council MR/R025126/1
6 · The paper itself

Abstract

Radiocarbon dating is the gold standard in archeology to estimate the age of skeletons, a key to studying their origins. Many published ancient genomes lack reliable and direct dates, which results in obscure and contradictory reports. We developed the temporal population structure (TPS), a DNA-based dating method for genomes ranging from the Late Mesolithic to today, and applied it to 3,591 ancient and 1,307 modern Eurasians. TPS predictions aligned with the known dates and correctly accounted for kin relationships. TPS dating of poorly dated Eurasian samples resolved conflicting reports in the literature, as illustrated by one test case. We also demonstrated how TPS improved the ability to study phenotypic traits over time. TPS can be used when radiocarbon dating is unfeasible or uncertain or to develop alternative hypotheses for samples younger than 10,000 years ago, a limitation that may be resolved over time as ancient data accumulate.

Indexed as

Genetic TechniquesRadiometric DatingArchaeologySkeletonancient DNADNA-based dating methodgenomic datinggenomics datingpaleogenomicsphenotypic traitsradiocarbon datingrandom forest regressionsupervised learningtemporal population structureTPS

Identifiers

PMID36046618
PMCPMC9421539

What Socratic holds

Textmetadata
LicenceCC BY
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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 Socratic graph.