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Activity Number: 4 - Utilizing Public Genomic Data for the Public Good: Improving Understanding of Disease Etiology and Treatment
Type: Invited
Date/Time: Monday, August 3, 2020 : 10:00 AM to 11:50 AM
Sponsor: WNAR
Abstract #309309
Title: Model Checking and More Powerful Inference in Transcriptome-Wide Association Studies
Author(s): Wei Pan*
Companies: University of Minnesota
Keywords: 2SLS; causal inference; instrumental variables regression; Mendelian randomization; GWAS; TWAS
Abstract:

Transcriptome-wide association studies (TWAS, or PrediXcan) have been increasingly used to identify causal genes by integrating GWAS with eQTL data. The basic methodology underlying TWAS (and Mendelian randomization, MR) is the (two-sample) two-stage least squares (2SLS) instrumental variables regression for causal inference, which imposes strong assumptions on the SNPs to be valid instrumental variables (IVs). These assumptions are most likely to be violated in practice, e.g. due to widespread horizontal pleiotropy of the SNPs. We first consider some simple and powerful methods to detect invalid IVs/SNPs, then propose more robust and more powerful methods than existing ones for causal inference in the presence of invalid IVs.


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