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New insights into genomic selection through population-based non-parametric prediction methods Scientia Agricola
Lima,Leísa Pires; Azevedo,Camila Ferreira; Resende,Marcos Deon Vilela de; Silva,Fabyano Fonseca e; Suela,Matheus Massariol; Nascimento,Moysés; Viana,José Marcelo Soriano.
ABSTRACT: Genome-wide selection (GWS) is based on a large number of markers widely distributed throughout the genome. Genome-wide selection provides for the estimation of the effect of each molecular marker on the phenotype, thereby allowing for the capture of all genes affecting the quantitative traits of interest. The main statistical tools applied to GWS are based on random regression or dimensionality reduction methods. In this study a new non-parametric method, called Delta-p was proposed, which was then compared to the Genomic Best Linear Unbiased Predictor (G-BLUP) method. Furthermore, a new selection index combining the genetic values obtained by the G-BLUP and Delta-p, named Delta-p/G-BLUP methods, was proposed. The efficiency of the proposed...
Tipo: Info:eu-repo/semantics/article Palavras-chave: Genomic prediction; Selection index; Genetic gain; Asian rice.
Ano: 2019 URL: http://www.scielo.br/scielo.php?script=sci_arttext&pid=S0103-90162019001400290
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