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 …

Complex or quantitative traits are important in medicine, agriculture and evolution, yet, until
recently, few of the polymorphisms that cause variation in these traits were known. Genome …

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

Genome-wide association studies (GWAS) have rapidly spread across the globe over the
last few years becoming the de facto approach to identify candidate regions associated with …

The genome-wide association study (GWAS) approach has discovered hundreds of genetic
variants associated with diseases and quantitative traits. However, despite clinical overlap …

Over the last few years, many new genetic associations have been identified by genome‐
wide association studies (GWAS). There are potentially many uses of these identified …

Complex diseases are often highly heritable. However, for many complex traits only a small
proportion of the heritability can be explained by observed genetic variants in traditional …

One of the formative goals of genetics research is to understand how genetic variation leads
to phenotypic differences and human disease. Genome-wide association studies (GWASs) …

The brisk discovery of novel inherited disease markers by genome-wide association (GWA)
studies has raised expectations for predicting disease risk by analysing multiple common …

Genome-wide association studies (GWAS) for quantitative traits and disease in humans and
other species have shown that there are many loci that contribute to the observed …