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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 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 genome-wide association studies (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.
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Submitted on : Friday, January 14, 2022 - 12:34:37 PM
Last modification on : Wednesday, August 31, 2022 - 3:07:02 AM
Long-term archiving on: : Friday, April 15, 2022 - 6:43:46 PM


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Shiyang Ma, James Dalgleish, Justin Lee, Chen Wang, Linxi Liu, et al.. Powerful gene-based testing by integrating long-range chromatin interactions and knockoff genotypes. Proceedings of the National Academy of Sciences of the United States of America, 2021, 118 (47), pp.e2105191118. ⟨10.1073/pnas.2105191118⟩. ⟨pasteur-03526216⟩



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