Simultaneous fitting of genomic-BLUP and Bayes-C components in a genomic prediction model

When the assumed genotype error rate was correct (Figs.  3 and 4 ) and [see Additional file  3 : Figures S4 and S5] or when the evaluation dataset was used to estimate

GP with genic SNPs from WGS (the WGS_genic data) provided the highest predictive abil- ity compared to that obtained when all SNPs from WGS data were used. This implies that

(PCR) can provide a useful alternative method for gen- omic prediction. Our results showed that, on average, PCR yielded lower accuracies than the more commonly used GREML

In real data, the multivariate model identified most selected SNPs to be associated with all three milk yield traits (fat, milk and protein yield) but we found little evidence

Conclusions: The present study proposes GROH as a novel method to estimate genomic relationship matrices and predict GEBV based on runs of homozygosity and shows that it can result

6 Accuracy of the genomic relationship matrix either restricted by eigenvalues (EIG) or with the inverse derived by using the algorithm for proven and young (APY) based on number

Methods: In an attempt to alleviate potential discrepancies between assumptions of linear models and multi-population data, two types of alternative models were used: (1) a

We compared the speed of emBayesR with BayesR and fastBayesB using three criteria: the time complexity of each iteration (the function in terms of number of SNPs and individuals