A0491
Title: BRIDGE: A novel transcriptome-wide association analysis framework for biomarker identification
Authors: Zhaolong Yu - Yale University (United States) [presenting]
Abstract: Transcriptome-wide association studies (TWAS) have several advantages over traditional genome-wide association studies (GWAS) because TWAS performs gene-level association tests by which the multiple testing burden is reduced and association results are more interpretable. We will introduce a novel TWAS method based on joint bounded-variable least-squares. For imputation models, we trained the expression imputation models with genotype and RNA-sequencing data from the updated version of the Genotype-Tissue Expression (GTEx) project. We will show that the imputation accuracy of our method outperformed other state-of-the-art methods. Our pipeline also includes non-coding transcripts by performing specific expression adjustments. Using the gene imputation models, we performed TWAS on a number of complex traits based on their respective GWAS summary statistics and identified novel gene-trait associations.
