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  • 1.
    Felleki, Majbritt
    et al.
    Dalarna University, School of Technology and Business Studies, Statistics.
    Lundeheim, Nils
    SLU.
    Genetic heteroscedasticity of teat count in pigs2015In: Journal of Animal Breeding and Genetics, ISSN 0931-2668, E-ISSN 1439-0388, Vol. 132, no 5, p. 392-398Article in journal (Refereed)
    Abstract [en]

    The genetic improvement in pig litter size has been substantial. The number of teats on the sowmust thus increase as well to meet the needs of the piglets, because each piglet needs access to itsown teat. We applied a genetic heterogeneity model to teat counts in pigs, and estimated a mediumheritability for teat counts (0.35), but found a low heritability for residual variance (0.06),indicating that selection for reduced residual variance might have a limited effect. A numericallypositive correlation (0.8) was estimated between the breeding values for the mean and the residualvariance. However, because of the low heritability of the residual variance, the residual variance will probably increase very slowly with the mean.

  • 2.
    Rönnegård, Lars
    Dalarna University, School of Technology and Business Studies, Statistics. Swedish University of Agricultural Sciences.
    The evolution of peer-reviewed papers.2019In: Journal of Animal Breeding and Genetics, ISSN 0931-2668, E-ISSN 1439-0388, Vol. 136, no 2, p. 77-78Article in journal (Other academic)
  • 3.
    Rönnegård, Lars
    et al.
    Dalarna University, School of Technology and Business Studies, Statistics.
    Al-Sarraj, Razaw
    von Rosen, Dietrich
    Non-iterative variance component estimation in QTL analysis.2009In: Journal of Animal Breeding and Genetics, ISSN 0931-2668, E-ISSN 1439-0388, Vol. 126, no 1, p. 110-116Article in journal (Refereed)
    Abstract [en]

    In variance component quantitative trait loci (QTL) analysis, a mixed model is used to detect the most likely chromosome position of a QTL. The putative QTL is included as a random effect and a method is needed to estimate the QTL variance. The standard estimation method used is an iterative method based on the restricted maximum likelihood (REML). In this paper, we present a novel non-iterative variance component estimation method. This method is based on Henderson's method 3, but relaxes the condition of unbiasedness. Two similar estimators were compared, which were developed from two different partitions of the sum of squares in Henderson's method 3. The approach was compared with REML on data from a European wild boar × domestic pig intercross. A meat quality trait was studied on chromosome 6 where a functional gene was known to be located. Both partitions resulted in estimated QTL variances close to the REML estimates. From the non-iterative estimates, we could also compute good approximations of the likelihood ratio curve on the studied chromosome.

  • 4.
    Rönnegård, Lars
    et al.
    Dalarna University, School of Technology and Business Studies, Statistics. Swedish University of Agricultural Sciences, Uppsala, Sweden.
    Lee, Y
    Seoul National University, Seoul, Korea.
    Exploring the potential of hierarchical generalized linear models in animal breeding and genetics2013In: Journal of Animal Breeding and Genetics, ISSN 0931-2668, E-ISSN 1439-0388, Vol. 130, no 6, p. 415-416Article in journal (Refereed)
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