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A tutorial on how not to over-interpret STRUCTURE and ADMIXTURE bar plots

Author

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  • Daniel J. Lawson

    (University of Bristol, Integrative Epidemiology Unit, Population Health Sciences)

  • Lucy van Dorp

    (University College London
    University College London)

  • Daniel Falush

    (Milner Centre for Evolution, University of Bath)

Abstract

Genetic clustering algorithms, implemented in programs such as STRUCTURE and ADMIXTURE, have been used extensively in the characterisation of individuals and populations based on genetic data. A successful example is the reconstruction of the genetic history of African Americans as a product of recent admixture between highly differentiated populations. Histories can also be reconstructed using the same procedure for groups that do not have admixture in their recent history, where recent genetic drift is strong or that deviate in other ways from the underlying inference model. Unfortunately, such histories can be misleading. We have implemented an approach, badMIXTURE, to assess the goodness of fit of the model using the ancestry “palettes” estimated by CHROMOPAINTER and apply it to both simulated data and real case studies. Combining these complementary analyses with additional methods that are designed to test specific hypotheses allows a richer and more robust analysis of recent demographic history.

Suggested Citation

  • Daniel J. Lawson & Lucy van Dorp & Daniel Falush, 2018. "A tutorial on how not to over-interpret STRUCTURE and ADMIXTURE bar plots," Nature Communications, Nature, vol. 9(1), pages 1-11, December.
  • Handle: RePEc:nat:natcom:v:9:y:2018:i:1:d:10.1038_s41467-018-05257-7
    DOI: 10.1038/s41467-018-05257-7
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    Cited by:

    1. Estavoyer, Maxime & François, Olivier, 2022. "Theoretical analysis of principal components in an umbrella model of intraspecific evolution," Theoretical Population Biology, Elsevier, vol. 148(C), pages 11-21.
    2. Crystal M. Tomlin & Sitaram Rajaraman & Jeanne Theresa Sebesta & Anne-Cathrine Scheen & Mika Bendiksby & Yee Wen Low & Jarkko Salojärvi & Todd P. Michael & Victor A. Albert & Charlotte Lindqvist, 2024. "Allopolyploid origin and diversification of the Hawaiian endemic mints," Nature Communications, Nature, vol. 15(1), pages 1-17, December.
    3. Marie Louis & Petra Korlević & Milaja Nykänen & Frederick Archer & Simon Berrow & Andrew Brownlow & Eline D. Lorenzen & Joanne O’Brien & Klaas Post & Fernando Racimo & Emer Rogan & Patricia E. Rosel &, 2023. "Ancient dolphin genomes reveal rapid repeated adaptation to coastal waters," Nature Communications, Nature, vol. 14(1), pages 1-13, December.
    4. Pfaffelhuber, Peter & Rohde, Angelika, 2022. "A central limit theorem concerning uncertainty in estimates of individual admixture," Theoretical Population Biology, Elsevier, vol. 148(C), pages 28-39.
    5. Yee Wen Low & Sitaram Rajaraman & Crystal M. Tomlin & Joffre Ali Ahmad & Wisnu H. Ardi & Kate Armstrong & Parusuraman Athen & Ahmad Berhaman & Ruth E. Bone & Martin Cheek & Nicholas R. W. Cho & Le Min, 2022. "Genomic insights into rapid speciation within the world’s largest tree genus Syzygium," Nature Communications, Nature, vol. 13(1), pages 1-15, December.
    6. Hirzi Luqman & Daniel Wegmann & Simone Fior & Alex Widmer, 2023. "Climate-induced range shifts drive adaptive response via spatio-temporal sieving of alleles," Nature Communications, Nature, vol. 14(1), pages 1-15, December.

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