Evidence map›Paper›PMID 38040695›Full record

ArticleNature communications2023

Haplotype-based inference of recent effective population size in modern and ancient DNA samples.

Romain Fournier, Zoi Tsangalidou, David Reich, Pier Francesco Palamara

Abstract read
In one paragraph

Article in Nature communications, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 35 papers.

0numbers the graph read from it
0cells of the map it votes in
35citing 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

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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

35 citing papers in PubMed.

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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

4 authors.

Romain FournierDepartment of Statistics, University of Oxford, Oxford, UK.ORCID 0000-0003-2790-2445
Zoi TsangalidouDepartment of Statistics, University of Oxford, Oxford, UK.
David ReichDepartment of Genetics, Harvard Medical School, Boston, MA, USA.ORCID 0000-0002-7037-5292
Pier Francesco PalamaraDepartment of Statistics, University of Oxford, Oxford, UK. palamara@stats.ox.ac.uk.ORCID 0000-0002-7999-1972

Funding

Solving ascertainment bias in ancient DNA using Ultima Genomics sequencingR01HG012287 · NHGRI · HARVARD MEDICAL SCHOOL · PI REICH, DAVID E · 2021 to 2025
$2.7M
Population mixture in evolutionary and medical geneticsR01GM100233 · NIGMS · HARVARD MEDICAL SCHOOL · PI PATTERSON, NICK J, REICH, DAVID E · 2012 to 2019
$2.7M
Efficient methods for identifying cryptic relatedness in millions of individualsR21HG010748 · NHGRI · DANA-FARBER CANCER INST · PI GUSEV, ALEXANDER · 2019 to 2020
$372k
NHGRI NIH HHS R01 HG012287NHGRI NIH HHS R21 HG010748NIGMS NIH HHS R01 GM100233Wellcome Trust
6 · The paper itself

Abstract

Individuals sharing recent ancestors are likely to co-inherit large identical-by-descent (IBD) genomic regions. The distribution of these IBD segments in a population may be used to reconstruct past demographic events such as effective population size variation, but accurate IBD detection is difficult in ancient DNA data and in underrepresented populations with limited reference data. In this work, we introduce an accurate method for inferring effective population size variation during the past ~2000 years in both modern and ancient DNA data, called HapNe. HapNe infers recent population size fluctuations using either IBD sharing (HapNe-IBD) or linkage disequilibrium (HapNe-LD), which does not require phasing and can be computed in low coverage data, including data sets with heterogeneous sampling times. HapNe shows improved accuracy in a range of simulated demographic scenarios compared to currently available methods for IBD-based and LD-based inference of recent effective population size, while requiring fewer computational resources. We apply HapNe to several modern populations from the 1,000 Genomes Project, the UK Biobank, the Allen Ancient DNA Resource, and recently published samples from Iron Age Britain, detecting multiple instances of recent effective population size variation across these groups.

Indexed as

DNA, AncientGenomicsGenetics, PopulationHaplotypesHumansLinkage DisequilibriumPolymorphism, Single NucleotidePopulation DensityDNA, Ancient

Identifiers

PMID38040695
PMCPMC10692198

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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.