Revealing the range of equally likely estimates in the admixture model

Many ancestry inference tools, including Structure and Admixture, rely on the admixture model to infer both, allele frequencies p and individual admixture proportions q for a collection of individuals relative to a set of hypothetical ancestral populations. We show that under realistic conditions the likelihood in the admixture model is typically flat in some direction around a maximum-likelihood estimate (q^,p^). In particular, the maximum-likelihood estimator is nonunique and there is a complete spectrum of possible estimates. Common inference tools typically identify only a few points within this spectrum. We provide an algorithm which computes the set of equally likely (q~,p~), when starting from (q^,p^). It is analytic for K=2 ancestral populations and numeric for K>2. We apply our algorithm to data from the 1000 genomes project, and show that inter-European estimators of q can come with a large set of equally likely possibilities. In general, markers with large allele frequency differences between populations in combination with individuals with concentrated admixture proportions lead to small areas with a flat likelihood. Our findings imply that care must be taken when interpreting results from STRUCTURE and ADMIXTURE if populations are not separated well enough.

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Publication Details

Journal
G3 Genes Genomes Genetics
Published
2025-06-19
DOI
https://doi.org/10.1093/g3journal/jkaf142
Citations
1
Primary Topic
Remote Sensing and LiDAR Applications
Type
article
Field-Weighted Citation Impact
0.80

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article

Revealing the range of equally likely estimates in the admixture model

Franz Baumdicker, Peter Pfaffelhuber, Carola Sophia Heinzel
1 citations
G3 Genes Genomes Genetics
Remote Sensing and LiDAR Applications
0.80
article

Revealing the range of equally likely estimates in the admixture model

Franz Baumdicker, Peter Pfaffelhuber, Carola Sophia Heinzel
article en
1 citations

Abstract

Many ancestry inference tools, including Structure and Admixture, rely on the admixture model to infer both, allele frequencies p and individual admixture proportions q for a collection of individuals relative to a set of hypothetical ancestral populations. We show that under realistic conditions the likelihood in the admixture model is typically flat in some direction around a maximum-likelihood estimate (q^,p^). In particular, the maximum-likelihood estimator is nonunique and there is a complete spectrum of possible estimates. Common inference tools typically identify only a few points within this spectrum. We provide an algorithm which computes the set of equally likely (q~,p~), when starting from (q^,p^). It is analytic for K=2 ancestral populations and numeric for K>2. We apply our algorithm to data from the 1000 genomes project, and show that inter-European estimators of q can come with a large set of equally likely possibilities. In general, markers with large allele frequency differences between populations in combination with individuals with concentrated admixture proportions lead to small areas with a flat likelihood. Our findings imply that care must be taken when interpreting results from STRUCTURE and ADMIXTURE if populations are not separated well enough.

G3 Genes Genomes GeneticsVol. 15(8)
University of Freiburg (DE), University of Tübingen (DE)
California Department of Fish and Game, Deutsche Forschungsgemeinschaft
Openalex Percentile: Top 28%
Remote Sensing and LiDAR Applications
0.80
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Revealing the range of equally likely estimates in the admixture model — Franz Baumdicker, Peter Pfaffelhuber, et al. · G3 Genes Genomes Genetics (2025) | TGRS Research Map | TGRS