Genomic prediction of blood biomarkers of metabolic disorders in Holstein cattle using parametric and nonparametric models

CONCLUSIONS: Our results indicate that the Stack approach was more accurate in predicting metabolic disturbances than GBLUP, BayesB, ENET, and GBM and seemed to be competitive for predicting complex phenotypes with various degrees of mode of inheritance, i.e. additive and non-additive effects. Selecting markers based on GBM improved accuracy of GBLUP.PMID:38684971 | PMC:PMC11057143 | DOI:10.1186/s12711-024-00903-9

Source: Genet Sel Evol - April 29, 2024 Category: Genetics & Stem Cells Authors: Lucio F M Mota Diana Giannuzzi Sara Pegolo Enrico Sturaro Daniel Gianola Riccardo Negrini Erminio Trevisi Paolo Ajmone Marsan Alessio Cecchinato Source Type: research