A Powerful Gene-Based Test Accommodating Common and Low-Frequency Variants to Detect Both Main Effects and Gene-Gene Interaction Effects in Case-Control Studies
Next-generation sequencing (NGS) has been widely used in genetic association studies to identify both common and rare variants associated with complex diseases. Various statistical association tests have been developed to analyze NGS data; however, most focus on identifying the marginal effects of a...
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| Format: | Article |
| Language: | English |
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Frontiers Media S.A.
2018-01-01
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| Series: | Frontiers in Genetics |
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| Online Access: | http://journal.frontiersin.org/article/10.3389/fgene.2017.00228/full |
| _version_ | 1831519740652158976 |
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| author | Ren-Hua Chung Chen-Yu Kang |
| author_facet | Ren-Hua Chung Chen-Yu Kang |
| author_sort | Ren-Hua Chung |
| collection | DOAJ |
| description | Next-generation sequencing (NGS) has been widely used in genetic association studies to identify both common and rare variants associated with complex diseases. Various statistical association tests have been developed to analyze NGS data; however, most focus on identifying the marginal effects of a set of genetic variants on the disease. Only a few association tests for NGS data analysis have considered the interaction effects between genes. We developed three powerful gene-based gene-gene interaction tests for testing both the main effects and the interaction effects of common, low-frequency, and common with low-frequency variant pairs between two genes (the IGOF tests) in case-control studies using NGS data. We performed a comprehensive simulation study to verify that the proposed tests had appropriate type I error rates and significantly higher power than did other interaction tests for analyzing NGS data. The tests were applied to a whole-exome sequencing dataset for autism spectrum disorder (ASD) and the significant results were evaluated in another independent ASD cohort. The IGOF tests were implemented in C++ and are available at http://igof.sourceforge.net. |
| first_indexed | 2024-12-13T17:21:05Z |
| format | Article |
| id | doaj.art-2ff7f6b5744e49e59b8b2bf051a55db1 |
| institution | Directory Open Access Journal |
| issn | 1664-8021 |
| language | English |
| last_indexed | 2024-12-13T17:21:05Z |
| publishDate | 2018-01-01 |
| publisher | Frontiers Media S.A. |
| record_format | Article |
| series | Frontiers in Genetics |
| spelling | doaj.art-2ff7f6b5744e49e59b8b2bf051a55db12022-12-21T23:37:19ZengFrontiers Media S.A.Frontiers in Genetics1664-80212018-01-01810.3389/fgene.2017.00228306981A Powerful Gene-Based Test Accommodating Common and Low-Frequency Variants to Detect Both Main Effects and Gene-Gene Interaction Effects in Case-Control StudiesRen-Hua ChungChen-Yu KangNext-generation sequencing (NGS) has been widely used in genetic association studies to identify both common and rare variants associated with complex diseases. Various statistical association tests have been developed to analyze NGS data; however, most focus on identifying the marginal effects of a set of genetic variants on the disease. Only a few association tests for NGS data analysis have considered the interaction effects between genes. We developed three powerful gene-based gene-gene interaction tests for testing both the main effects and the interaction effects of common, low-frequency, and common with low-frequency variant pairs between two genes (the IGOF tests) in case-control studies using NGS data. We performed a comprehensive simulation study to verify that the proposed tests had appropriate type I error rates and significantly higher power than did other interaction tests for analyzing NGS data. The tests were applied to a whole-exome sequencing dataset for autism spectrum disorder (ASD) and the significant results were evaluated in another independent ASD cohort. The IGOF tests were implemented in C++ and are available at http://igof.sourceforge.net.http://journal.frontiersin.org/article/10.3389/fgene.2017.00228/fullgene-gene interactionnext-generation sequencingcase-control studyrare variant associationsimulationsautism spectrum disorders |
| spellingShingle | Ren-Hua Chung Chen-Yu Kang A Powerful Gene-Based Test Accommodating Common and Low-Frequency Variants to Detect Both Main Effects and Gene-Gene Interaction Effects in Case-Control Studies Frontiers in Genetics gene-gene interaction next-generation sequencing case-control study rare variant association simulations autism spectrum disorders |
| title | A Powerful Gene-Based Test Accommodating Common and Low-Frequency Variants to Detect Both Main Effects and Gene-Gene Interaction Effects in Case-Control Studies |
| title_full | A Powerful Gene-Based Test Accommodating Common and Low-Frequency Variants to Detect Both Main Effects and Gene-Gene Interaction Effects in Case-Control Studies |
| title_fullStr | A Powerful Gene-Based Test Accommodating Common and Low-Frequency Variants to Detect Both Main Effects and Gene-Gene Interaction Effects in Case-Control Studies |
| title_full_unstemmed | A Powerful Gene-Based Test Accommodating Common and Low-Frequency Variants to Detect Both Main Effects and Gene-Gene Interaction Effects in Case-Control Studies |
| title_short | A Powerful Gene-Based Test Accommodating Common and Low-Frequency Variants to Detect Both Main Effects and Gene-Gene Interaction Effects in Case-Control Studies |
| title_sort | powerful gene based test accommodating common and low frequency variants to detect both main effects and gene gene interaction effects in case control studies |
| topic | gene-gene interaction next-generation sequencing case-control study rare variant association simulations autism spectrum disorders |
| url | http://journal.frontiersin.org/article/10.3389/fgene.2017.00228/full |
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