Gerhard Moser

The paper introduces a Bayesian model, BayesRR-RC, to infer the genetic architecture of complex traits and finds that most genetic variance is attributed to non-proximal regulatory and coding regions.

This paper introduces SBayesR, a Bayesian method for polygenic prediction using GWAS summary statistics, achieving higher accuracy and efficiency than existing methods.

This study compares LDSC and GREML methods for estimating genetic correlation, showing GREML provides higher accuracy, especially in the presence of genetic heterogeneity.