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Segregation distortion: Utilizing simulated genotyping data to evaluate statistical methods

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  • Alexander Coulton
  • Alexandra M Przewieslik-Allen
  • Amanda J Burridge
  • Daniel S Shaw
  • Keith J Edwards
  • Gary L A Barker

Abstract

Segregation distortion is the phenomenon in which genotypes deviate from expected Mendelian ratios in the progeny of a cross between two varieties or species. There is not currently a widely used consensus for the appropriate statistical test, or more specifically the multiple testing correction procedure, used to detect segregation distortion for high-density single-nucleotide polymorphism (SNP) data. Here we examine the efficacy of various multiple testing procedures, including chi-square test with no correction for multiple testing, false-discovery rate correction and Bonferroni correction using an in-silico simulation of a biparental mapping population. We find that the false discovery rate correction best approximates the traditional p-value threshold of 0.05 for high-density marker data. We also utilize this simulation to test the effect of segregation distortion on the genetic mapping process, specifically on the formation of linkage groups during marker clustering. Only extreme segregation distortion was found to effect genetic mapping. In addition, we utilize replicate empirical mapping populations of wheat varieties Avalon and Cadenza to assess how often segregation distortion conforms to the same pattern between closely related wheat varieties.

Suggested Citation

  • Alexander Coulton & Alexandra M Przewieslik-Allen & Amanda J Burridge & Daniel S Shaw & Keith J Edwards & Gary L A Barker, 2020. "Segregation distortion: Utilizing simulated genotyping data to evaluate statistical methods," PLOS ONE, Public Library of Science, vol. 15(2), pages 1-19, February.
    • Handle: RePEc:plo:pone00:0228951
    DOI: 10.1371/journal.pone.0228951
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    References listed on IDEAS

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    1. Yonghui Wu & Prasanna R Bhat & Timothy J Close & Stefano Lonardi, 2008. "Efficient and Accurate Construction of Genetic Linkage Maps from the Minimum Spanning Tree of a Graph," PLOS Genetics, Public Library of Science, vol. 4(10), pages 1-11, October.
    2. Ronald L. Wasserstein & Allen L. Schirm & Nicole A. Lazar, 2019. "Moving to a World Beyond “p," The American Statistician, Taylor & Francis Journals, vol. 73(S1), pages 1-19, March.
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