Predicting complex phenotypes from genomic data is a fundamental aim of animal and plant
breeding, where we wish to predict genetic merits of selection candidates; and of human …

Predicting individual quantitative trait phenotypes from high-resolution genomic
polymorphism data is important for personalized medicine in humans, plant and animal …

The study of genetic architecture of complex traits has been dramatically influenced by
implementing genome-wide analytical approaches during recent years. Of particular interest …

Identification of genetic loci in complex traits has focused largely on one-dimensional
genome scans to search for associations between single markers and the phenotype. There …

Background In recent years, with the development of high-throughput sequencing
technology and the commercial availability of genotyping bead chips, more attention is …

The prediction of phenotypic traits using high-density genomic data has many applications
such as the selection of plants and animals of commercial interest; and it is expected to play …

Genomic and pedigree-based best linear unbiased prediction methodologies (G-BLUP and
P-BLUP) have proven themselves efficient for partitioning the phenotypic variance of …

Background Compared to medium-density single nucleotide polymorphism (SNP) data, high-
density SNP data contain abundant genetic variants and provide more information for the …

In genome-based prediction there is considerable uncertainty about the statistical model
and method required to maximize prediction accuracy. For traits influenced by a small …

Background Differences in linkage disequilibrium and in allele substitution effects of QTL
(quantitative trait loci) may hinder genomic prediction across populations. Our objective was …