Evidence map›Paper›PMID 23821598›Full record

ArticleGenetics2013

Robust identification of local adaptation from allele frequencies.

Torsten Günther, Graham Coop

Abstract read
In one paragraph

Article in Genetics, 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 255 papers.

0numbers the graph read from it
0cells of the map it votes in
255citing 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

255 citing papers in PubMed.

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  13. Conservation Units for Anadromous Arctic Char (Evolutionary applications · 2026
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195 more citing papers are in PubMed but not listed here.

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

2 authors.

Torsten GüntherInstitute of Plant Breeding, Seed Science, and Population Genetics, University of Hohenheim, 70593 Stuttgart, Germany.
Graham Coop

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Comparing allele frequencies among populations that differ in environment has long been a tool for detecting loci involved in local adaptation. However, such analyses are complicated by an imperfect knowledge of population allele frequencies and neutral correlations of allele frequencies among populations due to shared population history and gene flow. Here we develop a set of methods to robustly test for unusual allele frequency patterns and correlations between environmental variables and allele frequencies while accounting for these complications based on a Bayesian model previously implemented in the software Bayenv. Using this model, we calculate a set of "standardized allele frequencies" that allows investigators to apply tests of their choice to multiple populations while accounting for sampling and covariance due to population history. We illustrate this first by showing that these standardized frequencies can be used to detect nonparametric correlations with environmental variables; these correlations are also less prone to spurious results due to outlier populations. We then demonstrate how these standardized allele frequencies can be used to construct a test to detect SNPs that deviate strongly from neutral population structure. This test is conceptually related to FST and is shown to be more powerful, as we account for population history. We also extend the model to next-generation sequencing of population pools-a cost-efficient way to estimate population allele frequencies, but one that introduces an additional level of sampling noise. The utility of these methods is demonstrated in simulations and by reanalyzing human SNP data from the Human Genome Diversity Panel populations and pooled next-generation sequencing data from Atlantic herring. An implementation of our method is available from http://gcbias.org.

Indexed as

Gene FrequencyModels, GeneticSoftwareAdaptation, PhysiologicalAnimalsEnvironmentEvolution, MolecularHumansPolymorphism, Single NucleotidePopulationadaptationcorrelationdifferentiationenvironmentpool-seq

Identifiers

PMID23821598
PMCPMC3761302

What OpenQuestion holds

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Read underepoch 390

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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.