Evidence map›Paper›PMID 35259336›Full record

ArticleAmerican journal of human genetics2022

The genomic signatures of natural selection in admixed human populations.

Sebastian Cuadros-Espinoza, Guillaume Laval, Lluis Quintana-Murci, Etienne Patin

Open access · greenAbstract read
In one paragraph

Article in American journal of human genetics, 2022. 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
6.2field-weighted citation impact, top 3% 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, 36 citations in OpenAlex.

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  19. Fast, accurate local ancestry inference with FLARE.American journal of human genetics · 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 1 institution in 1 country.

Sebastian Cuadros-EspinozaInstitut Pasteur, Université de Paris, CNRS UMR2000, Human Evolutionary Genetics Unit, Paris 75015, France; Sorbonne Université, Collège Doctoral, Paris 75005, France.
Guillaume LavalInstitut Pasteur, Université de Paris, CNRS UMR2000, Human Evolutionary Genetics Unit, Paris 75015, France.
Lluis Quintana-MurciInstitut Pasteur, Université de Paris, CNRS UMR2000, Human Evolutionary Genetics Unit, Paris 75015, France; Chair Human Genomics and Evolution, Collège de France, Paris 75005, France. Electronic address: quintana@pasteur.fr.
Etienne PatinInstitut Pasteur, Université de Paris, CNRS UMR2000, Human Evolutionary Genetics Unit, Paris 75015, France. Electronic address: epatin@pasteur.fr.
Centre National de la Recherche Scientifique · FR

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Admixture has been a pervasive phenomenon in human history, extensively shaping the patterns of population genetic diversity. There is increasing evidence to suggest that admixture can also facilitate genetic adaptation to local environments, i.e., admixed populations acquire beneficial mutations from source populations, a process that we refer to as "adaptive admixture." However, the role of adaptive admixture in human evolution and the power to detect it remain poorly characterized. Here, we use extensive computer simulations to evaluate the power of several neutrality statistics to detect natural selection in the admixed population, assuming multiple admixture scenarios. We show that statistics based on admixture proportions, F

Indexed as

GenomicsSelection, GeneticAdaptation, PhysiologicalApolipoprotein L1Black PeopleGene FlowGenetics, PopulationHumansPolymorphism, Single NucleotideAPOL1 protein, humanApolipoprotein L1admixturegenetic adaptationgenome scanhuman population geneticspositive selection

Identifiers

PMID35259336
PMCPMC9069077
OpenAlexW4221094397

What OpenQuestion holds

Textmetadata
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.