A comprehensive performance assessment of human genotyping arrays for analyzing polygenic risk scores among diverse populations

Regardless of the expansion of next-generation sequencing technologies, microarray-based genotyping remains a cost-effective means in genome-wide association studies and, more recently, in polygenic risk score (PRS) analysis. In this webinar, Dr. Vo presents data from a study in which he and his team performed a comprehensive performance assessment of 23 available human genotyping arrays in 6 ancestry groups using diverse public and in-house datasets. The analyses focused on the evaluation of derived imputation and PRS in three phenotypes, including height, BMI, and type 2 diabetes.

The study found that the arrays that are well-optimized for the targeted population, not the ones with a higher number of SNPs, achieved the best imputation performance. In addition, PRS estimated by imputed genotyping data and whole-genome sequencing data is highly correlated in most cases. When optimal arrays are used, the correlation of PRS between two types of data is higher than 0.97, but arrays with high density can result in lower PRS performance. The study results suggest the importance of properly selecting a suitable genotyping array for PRS analysis.

Learning objectives

1. Understand how imputation can affect the accuracy of a genotyping array
2. Know what factors are important in selecting a suitable genotyping array
3. Hear about one country’s experience analyzing PRS in under-represented populations

Speaker