genomic selection (gs) is a tool for prediction of breeding values for quantitative traits. for a successful application of gs, accuracy of predicted genomic breeding value (gebv) is a key issue to consider. here we investigated the accuracy of gebv in 345 genotyped iranian holstein cattle. the study was performed on milk, fat, protein yield and somatic cell count. four methods g-blup, bayes b,...

the objective of this study was to compare six statistical methods for prediction of genomic breedingvalues for traits with different genetic architecture in term of gene effects distributions and number ofquantitative traits loci (qtls). a genome consisted of 500 bi-allelic single nucleotide polymorphism(snp) markers distributed over a chromosomes with 100 cm length was simulated. three differ...

Following a Bayesian statistical inference paradigm, we provide an alternative methodology for analyzing a multivariate logistic regression. We use a multivariate normal prior in the Bayesian analysis. We present a unique Bayes estimator associated with a prior which is admissible. The Bayes estimators of the coefficients of the model are obtained via MCMC methods. The proposed procedure...

BACKGROUND Five main methods, commonly applied in genomic selection, were used to estimate the GEBV on the 15th QTLMAS workshop dataset: GBLUP, LASSO, Bayes A and two Bayes B type of methods (BBn and BBt). GBLUP is a mixed model approach where GEBV are obtained using a relationship matrix calculated from the SNP genotypes. The remaining methods are regression-based approaches where the SNP effe...

This document provides example R code demonstrating how to use the BayesSingleSub package (Section 1), and the technical details for the sampling routines (Section 2). 1 Tutorial for computing de Vries and Morey's Bayes factors Here, we show how to compute the Bayes factors B ar , B trend , B int , and B t+i , and how to obtain and plot the posterior distributions of the model parameters. First...

BACKGROUND A method for estimating genomic breeding values (GEBV) based on the Horseshoe prior was introduced and used on the analysis of the 16(th) QTLMAS workshop dataset, which resembles three milk production traits. The method was compared with five commonly used methods: Bayes A, Bayes B, Bayes C, Bayesian Lasso and GLUP. METHODS The main difference between the methods is the prior distr...

a two-factor experiment with interaction between factors wherein observations follow an inverse gaussian model is considered. analysis of the experiment is approached via an empirical bayes procedure. the conjugate family of prior distributions is considered. bayes and empirical bayes estimators are derived. application of the procedure is illustrated on a data set, which has previously been an...