The predictive performance of polygenic scores (PGS) is largely dependent on the number
of samples available to train the PGS. Increasing the sample size for a specific phenotype is …

The accuracy of polygenic risk scores (PRSs) to predict complex diseases increases with the
training sample size. PRSs are generally derived based on summary statistics from large …

Polygenic risk scores (PRS) have attenuated cross-population predictive performance. As
existing genome-wide association studies (GWAS) have been conducted predominantly in …

Genomic prediction has the potential to contribute to precision medicine. However, to date,
the utility of such predictors is limited due to low accuracy for most traits. Here theory and …

Motivation As increasing sample sizes from genome-wide association studies (GWASs),
polygenic risk scores (PRSs) have shown great potential in personalized medicine with …

Polygenic scores (PGS) are important tools for carrying out genetic prediction of common
diseases and disease related complex traits, facilitating the development of precision …

Polygenic scores (PGS) have emerged as the tool of choice for genomic prediction in a wide
range of fields. We show that PGS performance varies broadly across contexts and …

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

A primary goal of polygenic scores, which aggregate the effects of thousands of trait-
associated DNA variants discovered in genome-wide association studies (GWASs), is to …