000			02951nab a22003977a 4500
999			_c59909 _d59901
001			59909
003			MX-TxCIM
005			20240919020950.0
008			190115s2019 uk |||po|p|||||0| 00eng d
022			_a1365-2540 (Online)
024	8		_ahttps://doi.org/10.1038/s41437-018-0109-7
040			_aMX-TxCIM
041			_aeng
100	1		_92700 _aMontesinos-Lopez, O.A.
245	1	2	_aA singular value decomposition Bayesian multiple-trait and multiple-environment genomic model
260			_aUnited Kingdom : _bSpringer, _c2019.
500			_aPeer review
500			_aOpen Access
520			_aToday, 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.
526			_aWC _cFP2 _cFP3
546			_aText in English
650		7	_2AGROVOC _94013 _aBayesian theory
650		7	_2AGROVOC _91132 _aGenomics
650		7	_aBreeding _gAGROVOC _2 _91029
650		7	_2AGROVOC _98703 _aBioinformatics
700	1		_92702 _aMontesinos-Lopez, A.
700	1		_aCrossa, J. _gGenetic Resources Program _8CCJL01 _959
700	0		_98260 _aKismiantini
700	1		_98261 _aRamirez-Alcaraz, J.M.
700	1		_aSingh, R.P. _gGlobal Wheat Program _8INT0610 _9825
700	1		_aMondal, S. _gFormerly Global Wheat Program _8INT3211 _9904
700	1		_aJULIANA P. _8001710082 _gFormerly ​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​Global Wheat Program _gFormerly BISA _92690
773	0		_gv. 122, p. 381-401 _tHeredity _w444336 _x1365-2540 _dUnited Kingdom : Springer, 2019.
856	4		_yOpen Access through DSpace _uhttps://hdl.handle.net/10883/19788
942			_2ddc _cJA _n0