Most existing tools for constructing genetic prediction models begin with the assumption that
all genetic variants contribute equally towards the phenotype. However, this represents a …

Accurate prediction of an individual's phenotype from their DNA sequence is one of the great
promises of genomics and precision medicine. We extend a powerful individual-level data …

To the Editor—Despite recent work highlighting the advantages of linear mixedmodel (LMM)
methods for genome-wide association studies (GWAS) in datasets containing relatedness or …

The success of genome-wide association studies (GWASs) has led to increasing interest in
making predictions of complex trait phenotypes, including disease, from genotype data …

We develop a method, SBayesRC, that integrates genome-wide association study (GWAS)
summary statistics with functional genomic annotations to improve polygenic prediction of …

Genetically informed, deep-phenotyped biobanks are an important research resource and it
is imperative that the most powerful, versatile, and efficient analysis approaches are used …

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 …

Compared to univariate analysis of genome-wide association (GWA) studies, machine
learning–based models have been shown to provide improved means of learning such …

Background Genomic selection has gained much attention and the main goal is to increase
the predictive accuracy and the genetic gain in livestock using dense marker information …

There is currently much debate regarding the best model for how heritability varies across
the genome. The authors of GCTA recommend the GCTA-LDMS-I model, the authors of LD …