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    • Keywords


      backcross model; EM algorithm; genotyping errors; maximum likelihood estimation; QTL mapping.

    • Abstract


      Accurate genetic data are important prerequisite of performing genetic linkage test or association test. Currently, most analytical methods assume that the observed genotypes are correct. However, due to the constraint at the technical level, most of the genetic data that people used so far contain errors. In this paper, we considered the problem of QTL mapping based on biological data with genotyping errors. By analysing all possible genotypes of each individual in framework of multiple-interval mapping, we proposed an algorithm of inferring all model parameters through the expectation-maximization (EM) algorithm and discussed the hypothesis testing of the existence of QTL. We carried out extensive simulation studies to assess the proposed method. Simulation results showed that the new method outperforms the method that does not take the genotyping errors into account, and therefore it can decrease the impact of genotyping errors on QTL mapping. The proposed method was also applied to analyse a real barley dataset.

    • Author Affiliations


      Liang Tong1 2 Weijun Ma1 Haidong Liu1 Chaofeng Yuan1 Ying Zhou1

      1. School of Mathematical Sciences, Heilongjiang University, Harbin 150080, People’s Republic of China
      2. School of Information Engineering, Suihua University, Suihua 152061, People’s Republic of China
    • Dates

  • Journal of Genetics | News

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      Posted on July 25, 2019

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