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Testing gene-environment interactions for rare and/or common variants in sequencing association studies

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Article describes study in which novel approaches to test the effects of gene-environment (GE) interactions of rare and/or common risk, and/or protective variants in sequencing association studies were developed.

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15 p.

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Zhao, Zihan; Zhang, Jianjun; Sha, Qiuying & Hao, Han March 10, 2020.

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Article describes study in which novel approaches to test the effects of gene-environment (GE) interactions of rare and/or common risk, and/or protective variants in sequencing association studies were developed.

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15 p.

Notes

Abstract: The risk of many complex diseases is determined by a complex interplay of genetic and environmental factors. Advanced next generation sequencing technology makes identification of gene-environment (GE) interactions for both common and rare variants possible. However, most existing methods focus on testing the main effects of common and/or rare genetic variants. There are limited methods developed to test the effects of GE interactions for rare variants only or rare and common variants simultaneously. In this study, we develop novel approaches to test the effects of GE interactions of rare and/or common risk, and/or protective variants in sequencing association studies. We propose two approaches: 1) testing the effects of an optimally weighted combination of GE interactions for rare variants (TOW-GE); 2) testing the effects of a weighted combination of GE interactions for both rare and common variants (variable weight TOW-GE, VW-TOW-GE). Extensive simulation studies based on the Genetic Analysis Workshop 17 data show that the type I error rates of the proposed methods are well controlled. Compared to the existing interaction sequence kernel association test (ISKAT), TOW-GE is more powerful when there are GE interactions’ effects for rare risk and/or protective variants; VW-TOW-GE is more powerful when there are GE interactions’ effects for both rare and common risk and protective variants. Both TOW-GE and VW-TOW-GE are robust to the directions of effects of causal GE interactions. We demonstrate the applications of TOW-GE and VW-TOW-GE using an imputed data from the COPDGene Study.

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  • PLoS ONE, 15(3), Public Library of Science, March 2020

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  • Publication Title: PLoS ONE
  • Volume: 15
  • Issue: 3
  • Pages: 15
  • Peer Reviewed: Yes

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UNT Scholarly Works

Materials from the UNT community's research, creative, and scholarly activities and UNT's Open Access Repository. Access to some items in this collection may be restricted.

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  • March 10, 2020

Added to The UNT Digital Library

  • June 5, 2020, 4:16 p.m.

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  • Nov. 6, 2023, 2:08 p.m.

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Zhao, Zihan; Zhang, Jianjun; Sha, Qiuying & Hao, Han. Testing gene-environment interactions for rare and/or common variants in sequencing association studies, article, March 10, 2020; (https://digital.library.unt.edu/ark:/67531/metadc1639382/: accessed April 17, 2024), University of North Texas Libraries, UNT Digital Library, https://digital.library.unt.edu; crediting UNT College of Science.

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