ArticleGenetics2019
Reconstructing the History of Polygenic Scores Using Coalescent Trees.
Article in Genetics, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 29 papers.
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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.
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Who cites it
29 citing papers in PubMed, 49 citations in OpenAlex.
- Estimating uncertainty in family-based GWAS.bioRxiv : the preprint server for biology · 2026Article
- Genetic prediction with ARG-powered linear algebra.Genetics · 2026Article
- Polygenic and single-locus selection on BMI during Polynesian expansion.Journal of human genetics · 2026Article
- Article
- Evaluating ARG-estimation methods in the context of estimating population-mean polygenic score histories.Genetics · 2025Article
- Error rates in QST-FST comparisons depend on genetic architecture and estimation procedures.Genetics · 2025Article
- Inference and applications of ancestral recombination graphs.Nature reviews. Genetics · 2025Review
- Evaluating ARG-estimation methods in the context of estimating population-mean polygenic score histories.bioRxiv : the preprint server for biology · 2024Article
- The Promise of Inferring the Past Using the Ancestral Recombination Graph.Genome biology and evolution · 2024Article
- Unveiling recent and ongoing adaptive selection in human populations.PLoS biology · 2024Article
- Article
- Locus-level antagonistic selection shaped the polygenic architecture of human complex diseases.Human genetics · 2022Article
- Article
- Evolution in small steps and giant leaps.Evolution; international journal of organic evolution · 2022Review
- A selection pressure landscape for 870 human polygenic traits.Nature human behaviour · 2021Article
- Using singleton densities to detect recent selection inEvolution letters · 2021Article
- Allele frequency differentiation at height-associated SNPs among continental human populations.European journal of human genetics : EJHG · 2021Article
- Rapid Evolutionary Adaptation in Response to Selection on Quantitative Traits.Life (Basel, Switzerland) · 2021Review
- Review
- Disentangling selection on genetically correlated polygenic traits via whole-genome genealogies.American journal of human genetics · 2021Article
Corrections and comments
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Authors and funding
2 authors at 1 institution in 1 country.
Funding
Abstract
Genome-wide association studies (GWAS) have revealed that many traits are highly polygenic, in that their within-population variance is governed, in part, by small-effect variants at many genetic loci. Standard population-genetic methods for inferring evolutionary history are ill-suited for polygenic traits: when there are many variants of small effect, signatures of natural selection are spread across the genome and are subtle at any one locus. In the last several years, various methods have emerged for detecting the action of natural selection on polygenic scores, sums of genotypes weighted by GWAS effect sizes. However, most existing methods do not reveal the timing or strength of selection. Here, we present a set of methods for estimating the historical time course of a population-mean polygenic score using local coalescent trees at GWAS loci. These time courses are estimated by using coalescent theory to relate the branch lengths of trees to allele-frequency change. The resulting time course can be tested for evidence of natural selection. We present theory and simulations supporting our procedures, as well as estimated time courses of polygenic scores for human height. Because of its grounding in coalescent theory, the framework presented here can be extended to a variety of demographic scenarios, and its usefulness will increase as both GWAS and ancestral-recombination-graph inference continue to progress.
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Registered trials
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.