Minta Thomas

The paper compares ancestry calibration methods for a colorectal cancer polygenic risk score using All of Us data, finding that using admixture and diverse training sets improves normality and tail accuracy.

The paper selects and validates ten polygenic risk scores for clinical use in diverse populations, focusing on chronic diseases and addressing disparities in predictive performance.

This study improves polygenic risk scores for colorectal cancer by combining Asian and European ancestry data, enhancing risk prediction across diverse racial and ethnic groups.