A singular value decomposition Bayesian multiple-trait and multiple-environment genomic model

dc.creatorMontesinos-Lopez, O.A.
dc.creatorMontesinos-Lopez, A.
dc.creatorCrossa, J.
dc.creatorKismiantini
dc.creatorRamirez-Alcaraz, J.M.
dc.creatorSingh, R.P.
dc.creatorMondal, S.
dc.creatorJuliana, P.
dc.date2019-01-15T17:44:37Z
dc.date2019-01-15T17:44:37Z
dc.date2019
dc.date.accessioned2023-07-17T20:03:23Z
dc.date.available2023-07-17T20:03:23Z
dc.identifier1365-2540
dc.identifierISSN: 0018-067X
dc.identifierESSN: 1365-2540
dc.identifierhttps://hdl.handle.net/10883/19788
dc.identifier10.1038/s41437-018-0109-7
dc.identifier.urihttps://repositorioslatinoamericanos.uchile.cl/handle/2250/7511661
dc.descriptionToday, breeders perform genomic-assisted breeding to improve more than one trait. However, frequently there are several traits under study at one time, and the implementation of current genomic multiple-trait and multiple-environment models is challenging. Consequently, we propose a four-stage analysis for multiple-trait data in this paper. In the first stage, we perform singular value decomposition (SVD) on the resulting matrix of trait responses; in the second stage, we perform multiple trait analysis on transformed responses. In stages three and four, we collect and transform the traits back to their original state and obtain the parameter estimates and the predictions on these scale variables prior to transformation. The results of the proposed method are compared, in terms of parameter estimation and prediction accuracy, with the results of the Bayesian multiple-trait and multiple-environment model (BMTME) previously described in the literature. We found that the proposed method based on SVD produced similar results, in terms of parameter estimation and prediction accuracy, to those obtained with the BMTME model. Moreover, the proposed multiple-trait method is atractive because it can be implemented using current single-trait genomic prediction software, which yields a more efficient algorithm in terms of computation.
dc.description381-401
dc.formatPDF
dc.languageEnglish
dc.publisherSpringer Nature
dc.relationhttps://static-content.springer.com/esm/art%3A10.1038%2Fs41437-018-0109-7/MediaObjects/41437_2018_109_MOESM1_ESM.docx
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dc.rightsOpen Access
dc.source122
dc.sourceHeredity
dc.subjectAGRICULTURAL SCIENCES AND BIOTECHNOLOGY
dc.subjectBAYESIAN THEORY
dc.subjectBIOINFORMATICS
dc.subjectGENOMICS
dc.subjectAGRICULTURE
dc.titleA singular value decomposition Bayesian multiple-trait and multiple-environment genomic model
dc.typeArticle
dc.typePublished Version
dc.coverageUnited Kingdom


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