Recently, genome‐wide association studies have substantially expanded our knowledge
about genetic variants that influence the susceptibility to complex diseases. Although …

Polygenic scores (PGS) summarize the genetic contribution of a person's genotype to a
disease or phenotype. They can be used to group participants into different risk categories …

The rapid identification of genetic markers for multifactorial diseases from genome-wide
association studies is fuelling interest in investigating the predictive ability and health care …

The transcriptome-wide association study (TWAS) has emerged as one of several promising
techniques for integrating multi-scale 'omics' data into traditional genome-wide association …

Most traits of agronomic importance are quantitative in nature, and genetic markers have
been used for decades to dissect such traits. Recently, genomic selection has earned …

Genetic risk prediction is an important problem in human genetics, and accurate prediction
can facilitate disease prevention and treatment. Calculating polygenic risk score (PRS) has …

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 …

Polygenic risk scores have shown great promise in predicting complex disease risk and will
become more accurate as training sample sizes increase. The standard approach for …

Abstract We consider applying Bayesian Variable Selection Regression, or BVSR, to
genome-wide association studies and similar large-scale regression problems. Currently …

We examine improvements to the linear mixed model (LMM) that better correct for
population structure and family relatedness in genome-wide association studies (GWAS) …