Evidence map›Paper›PMID 30640906›Full record

ArticlePLoS genetics2019

Estimating recent migration and population-size surfaces.

Hussein Al-Asadi, Desislava Petkova, Matthew Stephens, John Novembre

Open access · goldAbstract read
In one paragraph

Article in PLoS genetics, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 60 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
60citing papers in PubMed, 1 pooled it
9.0field-weighted citation impact, top 2% 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

60 citing papers in PubMed, 1 synthesis or guideline pooled it, 126 citations in OpenAlex.

  1. Estimating human mobility in Holocene Western Eurasia with large-scale ancient genomic data.Proceedings of the National Academy of Sciences of the United States of America · 2023
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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 at 2 institutions in 2 countries.

Hussein Al-AsadiEvolutionary Biology, University of Chicago, Chicago, Illinois, United States of America.ORCID 0000-0003-3469-6707
Desislava PetkovaWellcome Centre for Human Genetics, University of Oxford, Oxford, United Kingdom.
Matthew StephensDepartment of Statistics, University of Chicago, Illinois, United States of America.
John NovembreEvolutionary Biology, University of Chicago, Chicago, Illinois, United States of America.
University of Chicago · USCentre for Human Genetics · GB

Funding

Genome analysis: statistical methods and applicationsR01HG002585 · NHGRI · UNIVERSITY OF WASHINGTON · PI MATTHEW STEPHENS · 2002 to 2026
$8.4M
Population Genetic Consequences of Recent Explosive Population Growth in HumansR01GM108805 · NIGMS · CORNELL UNIVERSITY · PI CLARK, ANDREW G, KEINAN, ALON · 2014 to 2017
$2.2M
Haplotype-based analysis methods for population genomicsR01HG007089 · NHGRI · UNIVERSITY OF CHICAGO · PI NOVEMBRE, JOHN · 2013 to 2017
$1.5M
Tools for Visualization of Geographic Structure in Population Genomic DataU01CA198933 · NCI · UNIVERSITY OF CHICAGO · PI NOVEMBRE, JOHN · 2015 to 2017
$1.2M
NCI NIH HHS U01 CA198933NHGRI NIH HHS R01 HG002585NHGRI NIH HHS R01 HG007089NIGMS NIH HHS R01 GM108805
6 · The paper itself

Abstract

In many species a fundamental feature of genetic diversity is that genetic similarity decays with geographic distance; however, this relationship is often complex, and may vary across space and time. Methods to uncover and visualize such relationships have widespread use for analyses in molecular ecology, conservation genetics, evolutionary genetics, and human genetics. While several frameworks exist, a promising approach is to infer maps of how migration rates vary across geographic space. Such maps could, in principle, be estimated across time to reveal the full complexity of population histories. Here, we take a step in this direction: we present a method to infer maps of population sizes and migration rates associated with different time periods from a matrix of genetic similarity between every pair of individuals. Specifically, genetic similarity is measured by counting the number of long segments of haplotype sharing (also known as identity-by-descent tracts). By varying the length of these segments we obtain parameter estimates associated with different time periods. Using simulations, we show that the method can reveal time-varying migration rates and population sizes, including changes that are not detectable when using a similar method that ignores haplotypic structure. We apply the method to a dataset of contemporary European individuals (POPRES), and provide an integrated analysis of recent population structure and growth over the last ∼3,000 years in Europe.

Indexed as

Biological EvolutionGenetics, PopulationEuropeGenetic VariationHaplotypesHumansPopulation DensityPopulation Dynamics

Identifiers

PMID30640906
PMCPMC6347299
OpenAlexW2949839185

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.