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dc.contributor.authorAGUILAR, I.eng
dc.contributor.authorLEGARRA, A.eng
dc.contributor.authorCARDOSO, F. F.eng
dc.contributor.authorMASUDA, Y.eng
dc.contributor.authorLOURENCO, D.eng
dc.contributor.authorMISZTAL, I.eng
dc.date.accessioned2020-01-06T18:24:04Z-
dc.date.available2020-01-06T18:24:04Z-
dc.date.created2020-01-06
dc.date.issued2019
dc.identifier.citationGenetics Selection Evolution, v. 51, n. 28, 20 June 2019.eng
dc.identifier.urihttp://www.alice.cnptia.embrapa.br/alice/handle/doc/1118159-
dc.descriptionBackground: Single-step genomic best linear unbiased prediction (SSGBLUP) is a comprehensive method for genomic prediction. Point estimates of marker effects from SSGBLUP are often used for genome-wide association studies (GWAS) without a formal framework of hypothesis testing. Our objective was to implement p-values for singlemarker GWAS studies within the single-step GWAS (SSGWAS) framework by deriving computational algorithms and procedures, and by applying these to a large beef cattle population. Methods: P-values were obtained based on the prediction error (co)variances for single nucleotide polymorphisms (SNPs), which were obtained from the prediction error (co)variances of genomic predictions based on the inverse of the coefficient matrix and formulas to estimate SNP effects. Results: Computation of p-values took a negligible time for a dataset with almost 2 million animals in the pedigree and 1424 genotyped sires, and no inflation of statistics was observed. The SNPs that passed the Bonferroni threshold of 10-5.9 were the same as those that explained the highest proportion of additive genetic variance, but even at the same significance levels and effects, some of them explained less genetic variance due to lower allele frequency. Conclusions: The use of a p-value for SSGWAS is a very general and efficient strategy to identify quantitative trait loci (QTL). It can be used for complex datasets such as those used in animal breeding, where only a proportion of the pedigreed animals are genotyped.eng
dc.language.isoengeng
dc.rightsopenAccesseng
dc.subjectGado Anguseng
dc.subjectPredição Genômicaeng
dc.titleFrequentist p-values for large-scale-single step genome-wide association, with an application to birth weight in American Angus cattle.eng
dc.typeArtigo de periódicoeng
dc.date.updated2020-01-06T18:24:04Z
dc.subject.thesagroBovinoeng
dc.subject.thesagroMarcador Genéticoeng
dc.subject.thesagroMelhoramento Genético Animaleng
riaa.ainfo.id1118159eng
riaa.ainfo.lastupdate2020-01-06
dc.identifier.doidoi.org/10.1186/s12711-019-0469-3eng
dc.contributor.institutionIgnacio Aguilar, INIA; Andres Legarra, INRA; FERNANDO FLORES CARDOSO, CPPSUL; Yutaka Masuda, University of Georgia; Daniela Lourenco, University of Georgia; Ignacy Misztal, University of Georgia.eng
Aparece en las colecciones:Artigo em periódico indexado (CPPSUL)

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