New challenges have arisen with the development of large marker panels for livestock species. Models easily become overparameterized when all available markers are included. Solutions have led to the development of shrinkage or regularization techniques. The objective of this study was the application and comparison of Bayesian LASSO (B-L), thick-tailed (Student-t), and semiparametric multiple ...

One objective of this study was to provide readers with a clear and unified understanding of parametric statistical and kernel methods, used for genomic prediction, and to compare some of these in the context of rice breeding for quantitative traits. Furthermore, another objective was to provide a simple and user-friendly R package, named KRMM, which allows users to perform RKHS regression with...

The rapid increase in high-throughput single-nucleotide polymorphism data has led to a great interest in applying genome-wide evaluation methods to identify an individual's genetic merit. Genome-wide evaluation combines statistical methods with genomic data to predict genetic values for complex traits. Considerable uncertainty currently exists in determining which genome-wide evaluation method ...

Machine learning (ML) is perhaps the most useful tool for interpretation of large genomic datasets. However, performance a single machine method in selection (GS) currently unsatisfactory. To improve predictions, we constructed stacking ensemble framework (SELF), integrating three methods, to predict estimated breeding values (GEBVs). The present study evaluated prediction ability SELF by analy...

Predicting disease resistance is one of the most prominent applications aquaculture selective breeding. Reductions in genotyping costs have allowed implementation genomic selection an abundance species and their related diseases showing promising results. Machine learning (ML) models can be value for prediction purposes, as suggested by several studies both plants livestock. The current study a...

The objective of this study was to assess the quality of genomic predictions for rebreeding success or failure after calving, age at first calving, and early pregnancy occurrence in Nellore females. There were 1,853 individuals that had 305,348 SNPs each used in genomic selection analyses. Three genomic prediction methods were used: GBLUP, a Bayesian method (BAYESCπ), and a lasso method (IBLASS...

Increased concern for the welfare of pedigree dogs has led to development of selection programs against inherited diseases. An example is canine hip dysplasia (CHD), which has a moderate heritability and a high prevalence in some large-sized breeds. To date, selection using phenotypes has led to only modest improvement, and alternative strategies such as genomic selection (GS) may prove more ef...

Abstract Plant breeders need efficient systems to identify which inbreds combine create new hybrid cultivars. The North Carolina Design II (NC DII) is a useful mating design evaluate the potential of varieties and their inbred parents. Genomic best linear unbiased prediction (GBLUP) models, either with or without inclusion dominance term in model, have been found be an method for using rich mar...