HASAN HAFEZIAN
Articles written in Journal of Genetics
Volume 98 All articles Published: 6 November 2019 Article ID 0102 RESEARCH ARTICLE
Comparison of parametric, semiparametric and nonparametric methods in genomic evaluation
HAMID SAHEBALAM MOHSEN GHOLIZADEH HASAN HAFEZIAN AYOUB FARHADI
Access to dense panels of molecular markers has facilitated genomic selection in animal breeding. The purpose of this study was to compare the nonparametric (random forest and support vector machine), semiparametric reproducing kernel Hilbert spaces (RKHS), and parametric methods (ridge regression and Bayes A) in prediction of genomic breeding values for traits with different genetic architecture. The predictive performance of different methods was compared in different combinations of distribution of QTL effects (normal and uniform), two levels of QTL numbers (50 and 200), three levels of heritability (0.1, 0.3 and 0.5), and two levels of training set individuals (1000 and 2000). To do this, a genome containing four chromosomes each 100-cM long was simulated on which 500, 1000 and 2000 evenly spaced single-nucleotide markers were distributed. With an increase in heritability and the number of markers, all the methods showed an increase in prediction accuracy (
Volume 101 All articles Published: 2 March 2022 Article ID 0019 RESEARCH ARTICLE
Evaluation of Bagging approach versus GBLUP and Bayesian LASSO in genomic prediction
HAMID SAHEBALAM MOHSEN GHOLIZADEH HASAN HAFEZIAN FATEMEH EBRAHIMI
The present study aimed to evaluate the predictive performance of bootstrap aggregating sampling technique (Bagging) in the context of genomic best linear unbiased prediction (GBLUP) method versus GBLUP and Bayesian least absolute shrinkage and selection operator (LASSO), in genomic prediction of livestock populations in different genetic architectures. For this purpose, different combinations of heritability (0.1 and 0.5), number of quantitative trait loci (QTL) (100 and 500) and distribution of QTL effects (normal, gamma, beta, Weibull and uniform) were considered. Also, a genome containing six chromosomes, 1 Morgan each, was simulated along which 1500 single-nucleotide polymorphism markers were evenly distributed. The prediction accuracies of the statistical models were obtained using the correlations between true (simulated) and predicted genomic breeding values. Results showed that, in different scenarios, the prediction accuracy using the GBLUP method was higher than that of the Bagging method (
Volume 102, 2023
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