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Powerful gene-based testing by integrating long-range chromatin interactions and knockoff genotypes
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...
Autores principales: | , , , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
National Academy of Sciences
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8617518/ https://www.ncbi.nlm.nih.gov/pubmed/34799441 http://dx.doi.org/10.1073/pnas.2105191118 |
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author | Ma, Shiyang Dalgleish, James Lee, Justin Wang, Chen Liu, Linxi Gill, Richard Buxbaum, Joseph D. Chung, Wendy K. Aschard, Hugues Silverman, Edwin K. Cho, Michael H. He, Zihuai Ionita-Laza, Iuliana |
author_facet | Ma, Shiyang Dalgleish, James Lee, Justin Wang, Chen Liu, Linxi Gill, Richard Buxbaum, Joseph D. Chung, Wendy K. Aschard, Hugues Silverman, Edwin K. Cho, Michael H. He, Zihuai Ionita-Laza, Iuliana |
author_sort | Ma, Shiyang |
collection | PubMed |
description | 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. |
format | Online Article Text |
id | pubmed-8617518 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | National Academy of Sciences |
record_format | MEDLINE/PubMed |
spelling | pubmed-86175182021-12-09 Powerful gene-based testing by integrating long-range chromatin interactions and knockoff genotypes Ma, Shiyang Dalgleish, James Lee, Justin Wang, Chen Liu, Linxi Gill, Richard Buxbaum, Joseph D. Chung, Wendy K. Aschard, Hugues Silverman, Edwin K. Cho, Michael H. He, Zihuai Ionita-Laza, Iuliana Proc Natl Acad Sci U S A Biological Sciences 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. National Academy of Sciences 2021-11-19 2021-11-23 /pmc/articles/PMC8617518/ /pubmed/34799441 http://dx.doi.org/10.1073/pnas.2105191118 Text en Copyright © 2021 the Author(s). Published by PNAS. https://creativecommons.org/licenses/by-nc-nd/4.0/This open access article is distributed under Creative Commons Attribution-NonCommercial-NoDerivatives License 4.0 (CC BY-NC-ND) (https://creativecommons.org/licenses/by-nc-nd/4.0/) . |
spellingShingle | Biological Sciences Ma, Shiyang Dalgleish, James Lee, Justin Wang, Chen Liu, Linxi Gill, Richard Buxbaum, Joseph D. Chung, Wendy K. Aschard, Hugues Silverman, Edwin K. Cho, Michael H. He, Zihuai Ionita-Laza, Iuliana Powerful gene-based testing by integrating long-range chromatin interactions and knockoff genotypes |
title | Powerful gene-based testing by integrating long-range chromatin interactions and knockoff genotypes |
title_full | Powerful gene-based testing by integrating long-range chromatin interactions and knockoff genotypes |
title_fullStr | Powerful gene-based testing by integrating long-range chromatin interactions and knockoff genotypes |
title_full_unstemmed | Powerful gene-based testing by integrating long-range chromatin interactions and knockoff genotypes |
title_short | Powerful gene-based testing by integrating long-range chromatin interactions and knockoff genotypes |
title_sort | powerful gene-based testing by integrating long-range chromatin interactions and knockoff genotypes |
topic | Biological Sciences |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8617518/ https://www.ncbi.nlm.nih.gov/pubmed/34799441 http://dx.doi.org/10.1073/pnas.2105191118 |
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