Powerful gene-based testing by integrating long-range chromatin interactions and knockoff genotypes

Abstract Gene-based tests are valuable techniques for identifying genetic factors in complex traits. Here we propose a novel gene-based testing framework that incorporates data on long-range chromatin interactions, several recent technical advances for region-based tests, and leverages the knockoff framework for synthetic genotype generation for improved gene discovery. Through simulations and applications to GWAS and whole-genome sequencing data for multiple diseases and traits we show that the proposed test increases the power over state-of-the-art gene-based tests in the literature, identifies genes that replicate in larger studies, and can provide a more narrow focus on the possible causal genes at a locus by reducing the confounding effect of linkage disequilibrium. Furthermore, our results show that incorporating genetic variation in distal regulatory elements tends to improve power over conventional tests. Results for UK Biobank and BioBank Japan traits are also available in a publicly accessible database that allows researchers to query gene-based results in an easy fashion. Significance Gene-based tests are important tools for elucidating the genetic basis of complex traits. Despite substantial recent efforts in this direction, the existing tests are still limited owing to low power and detection of false positive signals due to the confounding effects of linkage disequilibrium. In this paper we describe a novel gene-based test that attempts to address these limitations by incorporating data on long-range chromatin interactions, several recent technical advances for region-based testing, and the knockoff framework for synthetic genotype generation. Through extensive simulations and applications to multiple diseases and traits, we show that the proposed test increases the power over state-of-the-art gene-based tests and provides a narrower focus on the possible causal genes involved at a locus.