Zhangchen Zhao

This paper introduces TL-PRS, a transfer learning method for constructing polygenic risk scores across ancestries, achieving up to 42% average relative improvement in South Asian and African ancestry groups.

The paper improves rare variant association testing by introducing SAIGE-GENE+ which reduces type I error and computational costs, identifying 551 gene-phenotype associations in UK Biobank WES data.

SAIGE-GENE is a scalable generalized linear mixed model for region-based association tests in large cohorts, efficiently handling over 400,000 samples with controlled type I error rates.

The paper develops a region-based rare variant test for unbalanced binary phenotypes, showing improved type I error control and scalability, and identifies 10 rare variant associations in UK Biobank whole exome data.