Harvey A. Risch

This study identifies novel genetic risk loci for pancreatic ductal adenocarcinoma in African ancestry individuals through admixture mapping and GWAS.

This study improves transcriptome-wide association studies by integrating pleiotropy-guided methods with GWAS data to identify new cancer susceptibility genes.

The paper uses a multi-layered approach combining GWAS, spatial autocorrelation, and Hi-C to identify novel genetic variants associated with pancreatic cancer susceptibility.

This paper develops a Bayesian method to detect copy number variants and assess their association with disease in large-scale studies, finding deletions near MYC and TUSC3 linked to pancreatic cancer.

This study assesses polygenicity and risk prediction using common variants across 14 cancers, finding varying numbers of susceptibility variants and risk score effectiveness.

This study combines genome-wide association data from four cancers to identify shared and novel genetic associations and pleiotropic effects.