A comparison of genomic selection methods for breeding value prediction

Recent advances in molecular genetics techniques have made dense marker maps available, and the prediction of breeding value at the genome level has been employed in genetics research. However, an increasingly large number of markers raise both statistical and computational issues in genomic selection (GS), and many methods have been developed for genomic prediction to address these problems, including ridge regression-best linear unbiased...