000			02906nab|a22004217a|4500
001			68140
003			MX-TxCIM
005			20241220154346.0
008			202411s2024||||mx |||p|op||||00||0|eng|d
022			_a2160-1836 (Online)
024	8		_ahttps://doi.org/10.1093/g3journal/jkae246
040			_aMX-TxCIM
041			_aeng
100	1		_aMontesinos-Lopez, A. _92702
245	1	0	_aRefining penalized ridge regression : _ba novel method for optimizing the regularization parameter in genomic prediction
260			_aBethesda, MD (United States of America) : _bOxford University Press, _c2024.
500			_aPeer review
500			_aOpén Access
520			_aThe popularity of genomic selection as an efficient and cost-effective approach to estimate breeding values continues to increase, due in part to the significant saving in genotyping. Ridge regression is one ofthe most popular methods used for genomic prediction; however, its efficiency (in terms of prediction performance) depends on the appropriate tunning of the penalization parameter. In this paper we propose a novel, more efficient method to select the optimal penalization parameter for Ridge regression. We compared the proposed method with the conventional method to select the penalization parameter in 14 real data sets and we found that in 13 of these, the proposed method outperformed the conventional method and across data sets the gains in prediction accuracy in terms of Pearson's correlation was of 56.15%, with not-gains observed in terms of normalized mean square error. Finally, our results show evidence of the potential of the proposed method, and we encourage its adoption to improve the selection of candidate lines in the context of plant breeding.
546			_aText in English
591			_aMontesinos-Lopez, O.A. : No CIMMYT Affiliation
650		7	_aGenomics _2AGROVOC _91132
650		7	_aPlant breeding _2AGROVOC _91203
650		7	_aBreeding Value _2AGROVOC _98947
650		7	_aMarker-assisted selection _2AGROVOC _910737
650		7	_aBest linear unbiased predictor _2AGROVOC _926493
650		7	_aStatistical models _2AGROVOC _930393
700	1		_aMontesinos-Lopez, O.A. _gGenetic Resources Program _8I1706800 _92700
700	1		_aLecumberry, F. _937614
700	1		_aFariello, M.I. _937615
700	1		_aMontesinos-Lopez, J.C. _94950
700	1		_aCrossa, J. _gGenetic Resources Program _8CCJL01 _959
773	0		_tG3: Genes, Genomes, Genetics _dBethesda, MD (United States of America) : Oxford University Press, 2024. _x2160-1836 _gv. 14, no. 12, art. jkae246 _w56922
856	4		_yOpen Access through DSpace _uhttps://hdl.handle.net/10883/35128
942			_cJA _n0 _2ddc
999			_c68140 _d68132