Evidence map›Paper›PMID 38038347›Full record

ArticleeLife2023

The genomic footprint of social stratification in admixing American populations.

Alex Mas-Sandoval, Sara Mathieson, Matteo Fumagalli

Abstract read
In one paragraph

Article in eLife, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.

0numbers the graph read from it
0cells of the map it votes in
10citing 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

10 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
  4. Article
  5. Article
  6. Article
  7. Article
  8. Using the phenotype differences model to identify genetic effects in samples of partially genotyped sibling pairs.Proceedings of the National Academy of Sciences of the United States of America · 2024
    Article
  9. Review
  10. 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

3 authors.

Alex Mas-SandovalDepartment of Life Sciences, Silwood Park Campus, Imperial College London, London, United Kingdom.ORCID 0000-0002-1712-9404
Sara MathiesonDepartment of Computer Science, Haverford College, Haverford, United States.ORCID 0000-0002-0484-0838
Matteo FumagalliDepartment of Life Sciences, Silwood Park Campus, Imperial College London, London, United Kingdom.

Funding

Adaptive evolutionary inference frameworks for understudied populations using generative neural networksR15HG011528 · NHGRI · HAVERFORD COLLEGE · PI MATHIESON, SARA · 2021 to 2024
$783k
NHGRI NIH HHS R15 HG011528NIH HHS R15HG011528
6 · The paper itself

Abstract

Cultural and socioeconomic differences stratify human societies and shape their genetic structure beyond the sole effect of geography. Despite mating being limited by sociocultural stratification, most demographic models in population genetics often assume random mating. Taking advantage of the correlation between sociocultural stratification and the proportion of genetic ancestry in admixed populations, we sought to infer the former process in the Americas. To this aim, we define a mating model where the individual proportions of the genome inherited from Native American, European, and sub-Saharan African ancestral populations constrain the mating probabilities through ancestry-related assortative mating and sex bias parameters. We simulate a wide range of admixture scenarios under this model. Then, we train a deep neural network and retrieve good performance in predicting mating parameters from genomic data. Our results show how population stratification, shaped by socially constructed racial and gender hierarchies, has constrained the admixture processes in the Americas since the European colonization and the subsequent Atlantic slave trade.

Indexed as

Genetics, PopulationSocial StatusGenome, HumanGenomicsHumansRacial Groupsadmixtureassortative matingdeep learningevolutionary biologygeneticsgenetic structuregenomicshumanpopulation stratificationsex bias

Identifiers

PMID38038347
PMCPMC10776089

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.