Cargando…
Simple F Test Reveals Gene-Gene Interactions in Case-Control Studies
Missing heritability is still a challenge for Genome Wide Association Studies (GWAS). Gene-gene interactions may partially explain this residual genetic influence and contribute broadly to complex disease. To analyze the gene-gene interactions in case-control studies of complex disease, we propose a...
Autores principales: | , , , , , |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Libertas Academica
2012
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3399554/ https://www.ncbi.nlm.nih.gov/pubmed/22837643 http://dx.doi.org/10.4137/BBI.S9867 |
_version_ | 1782238417163124736 |
---|---|
author | Chen, Guanjie Yuan, Ao Zhou, Jie Bentley, Amy R. Adeyemo, Adebowale Rotimi, Charles N. |
author_facet | Chen, Guanjie Yuan, Ao Zhou, Jie Bentley, Amy R. Adeyemo, Adebowale Rotimi, Charles N. |
author_sort | Chen, Guanjie |
collection | PubMed |
description | Missing heritability is still a challenge for Genome Wide Association Studies (GWAS). Gene-gene interactions may partially explain this residual genetic influence and contribute broadly to complex disease. To analyze the gene-gene interactions in case-control studies of complex disease, we propose a simple, non-parametric method that utilizes the F-statistic. This approach consists of three steps. First, we examine the joint distribution of a pair of SNPs in cases and controls separately. Second, an F-test is used to evaluate the ratio of dependence in cases to that of controls. Finally, results are adjusted for multiple tests. This method was used to evaluate gene-gene interactions that are associated with risk of Type 2 Diabetes among African Americans in the Howard University Family Study. We identified 18 gene-gene interactions (P < 0.0001). Compared with the commonly-used logistical regression method, we demonstrate that the F-ratio test is an efficient approach to measuring gene-gene interactions, especially for studies with limited sample size. |
format | Online Article Text |
id | pubmed-3399554 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2012 |
publisher | Libertas Academica |
record_format | MEDLINE/PubMed |
spelling | pubmed-33995542012-07-26 Simple F Test Reveals Gene-Gene Interactions in Case-Control Studies Chen, Guanjie Yuan, Ao Zhou, Jie Bentley, Amy R. Adeyemo, Adebowale Rotimi, Charles N. Bioinform Biol Insights Short Report Missing heritability is still a challenge for Genome Wide Association Studies (GWAS). Gene-gene interactions may partially explain this residual genetic influence and contribute broadly to complex disease. To analyze the gene-gene interactions in case-control studies of complex disease, we propose a simple, non-parametric method that utilizes the F-statistic. This approach consists of three steps. First, we examine the joint distribution of a pair of SNPs in cases and controls separately. Second, an F-test is used to evaluate the ratio of dependence in cases to that of controls. Finally, results are adjusted for multiple tests. This method was used to evaluate gene-gene interactions that are associated with risk of Type 2 Diabetes among African Americans in the Howard University Family Study. We identified 18 gene-gene interactions (P < 0.0001). Compared with the commonly-used logistical regression method, we demonstrate that the F-ratio test is an efficient approach to measuring gene-gene interactions, especially for studies with limited sample size. Libertas Academica 2012-07-02 /pmc/articles/PMC3399554/ /pubmed/22837643 http://dx.doi.org/10.4137/BBI.S9867 Text en © the author(s), publisher and licensee Libertas Academica Ltd. This is an open access article. Unrestricted non-commercial use is permitted provided the original work is properly cited. |
spellingShingle | Short Report Chen, Guanjie Yuan, Ao Zhou, Jie Bentley, Amy R. Adeyemo, Adebowale Rotimi, Charles N. Simple F Test Reveals Gene-Gene Interactions in Case-Control Studies |
title | Simple F Test Reveals Gene-Gene Interactions in Case-Control Studies |
title_full | Simple F Test Reveals Gene-Gene Interactions in Case-Control Studies |
title_fullStr | Simple F Test Reveals Gene-Gene Interactions in Case-Control Studies |
title_full_unstemmed | Simple F Test Reveals Gene-Gene Interactions in Case-Control Studies |
title_short | Simple F Test Reveals Gene-Gene Interactions in Case-Control Studies |
title_sort | simple f test reveals gene-gene interactions in case-control studies |
topic | Short Report |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3399554/ https://www.ncbi.nlm.nih.gov/pubmed/22837643 http://dx.doi.org/10.4137/BBI.S9867 |
work_keys_str_mv | AT chenguanjie simpleftestrevealsgenegeneinteractionsincasecontrolstudies AT yuanao simpleftestrevealsgenegeneinteractionsincasecontrolstudies AT zhoujie simpleftestrevealsgenegeneinteractionsincasecontrolstudies AT bentleyamyr simpleftestrevealsgenegeneinteractionsincasecontrolstudies AT adeyemoadebowale simpleftestrevealsgenegeneinteractionsincasecontrolstudies AT rotimicharlesn simpleftestrevealsgenegeneinteractionsincasecontrolstudies |