Andreas J. Mayr

This paper investigates how polygenic risk scores (PRS) transfer between populations by simulating demographic changes and dominance coefficients, finding that recessive traits are more conserved.

This study evaluates the ability of a polygenic risk score to refine colorectal cancer risk in Lynch syndrome individuals, finding weak associations in specific subgroups.

This paper introduces an efficient boosting algorithm for polygenic risk scores, showing improved computational efficiency and prediction accuracy compared to existing methods.

The paper applies statistical learning methods to develop sparser polygenic models for LDL-cholesterol prediction using UK Biobank data, showing competitive performance compared to classical approaches.