Polygenic risk scores (PRS) estimate an individual's genetic likelihood of complex traits and
diseases by aggregating information across multiple genetic variants identified from genome …

Accurate genetic prediction of complex traits can facilitate disease screening, improve early
intervention, and aid in the development of personalized medicine. Genetic prediction of …

Polygenic risk scores (PRS) calculated from genome-wide association studies (GWAS) of
Europeans are known to have substantially reduced predictive accuracy in non-European …

Accurate polygenic scores (PGSs) facilitate the genetic prediction of complex traits and aid
in the development of personalized medicine. Here, we develop a statistical method called …

Polygenic risk scores (PRSs) have wide applications in human genetics research, but often
include tuning parameters which are difficult to optimize in practice due to limited access to …

Polygenic risk score (PRS) has been recently developed for predicting complex traits and
drug responses. It remains unknown whether multi-trait PRS (mtPRS) methods, by …

We present a new procedure for enhanced variable selection for component-wise gradient
boosting. Statistical boosting is a computational approach that emerged from machine …

Background Polygenic hazard scores (PHS) can identify individuals with increased risk of
prostate cancer. We estimated the benefit of additional SNPs on performance of a previously …

Multi-task learning has emerged as a powerful machine learning paradigm for integrating
data from multiple sources, leveraging similarities between tasks to improve overall model …

Existing high-dimensional statistical methods are largely established for analyzing individual-
level data. In this work, we study estimation and inference for high-dimensional linear …