Cargando…
A Novel Approach for the Simultaneous Analysis of Common and Rare Variants in Complex Traits
Genome-wide association studies (GWAS) have been successful in detecting common genetic variants underlying common traits and diseases. Despite the GWAS success stories, the percent trait variance explained by GWAS signals, the so called “missing heritability” has been, at best, modest. Also, the pr...
Autores principales: | , , , , |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Libertas Academica
2012
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3273305/ https://www.ncbi.nlm.nih.gov/pubmed/22346348 http://dx.doi.org/10.4137/BBI.S8852 |
_version_ | 1782222918280806400 |
---|---|
author | Yuan, Ao Chen, Guanjie Zhou, Yanxun Bentley, Amy Rotimi, Charles |
author_facet | Yuan, Ao Chen, Guanjie Zhou, Yanxun Bentley, Amy Rotimi, Charles |
author_sort | Yuan, Ao |
collection | PubMed |
description | Genome-wide association studies (GWAS) have been successful in detecting common genetic variants underlying common traits and diseases. Despite the GWAS success stories, the percent trait variance explained by GWAS signals, the so called “missing heritability” has been, at best, modest. Also, the predictive power of common variants identified by GWAS has not been encouraging. Given these observations along with the fact that the effects of rare variants are often, by design, unaccounted for by GWAS and the availability of sequence data, there is a growing need for robust analytic approaches to evaluate the contribution of rare variants to common complex diseases. Here we propose a new method that enables the simultaneous analysis of the association between rare and common variants in disease etiology. We refer to this method as SCARVA (simultaneous common and rare variants analysis). SCARVA is simple to use and is efficient. We used SCARVA to analyze two independent real datasets to identify rare and common variants underlying variation in obesity among participants in the Africa America Diabetes Mellitus (AADM) study and plasma triglyceride levels in the Dallas Heart Study (DHS). We found common and rare variants associated with both traits, consistent with published results. |
format | Online Article Text |
id | pubmed-3273305 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2012 |
publisher | Libertas Academica |
record_format | MEDLINE/PubMed |
spelling | pubmed-32733052012-02-16 A Novel Approach for the Simultaneous Analysis of Common and Rare Variants in Complex Traits Yuan, Ao Chen, Guanjie Zhou, Yanxun Bentley, Amy Rotimi, Charles Bioinform Biol Insights Methodology Genome-wide association studies (GWAS) have been successful in detecting common genetic variants underlying common traits and diseases. Despite the GWAS success stories, the percent trait variance explained by GWAS signals, the so called “missing heritability” has been, at best, modest. Also, the predictive power of common variants identified by GWAS has not been encouraging. Given these observations along with the fact that the effects of rare variants are often, by design, unaccounted for by GWAS and the availability of sequence data, there is a growing need for robust analytic approaches to evaluate the contribution of rare variants to common complex diseases. Here we propose a new method that enables the simultaneous analysis of the association between rare and common variants in disease etiology. We refer to this method as SCARVA (simultaneous common and rare variants analysis). SCARVA is simple to use and is efficient. We used SCARVA to analyze two independent real datasets to identify rare and common variants underlying variation in obesity among participants in the Africa America Diabetes Mellitus (AADM) study and plasma triglyceride levels in the Dallas Heart Study (DHS). We found common and rare variants associated with both traits, consistent with published results. Libertas Academica 2012-01-22 /pmc/articles/PMC3273305/ /pubmed/22346348 http://dx.doi.org/10.4137/BBI.S8852 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 | Methodology Yuan, Ao Chen, Guanjie Zhou, Yanxun Bentley, Amy Rotimi, Charles A Novel Approach for the Simultaneous Analysis of Common and Rare Variants in Complex Traits |
title | A Novel Approach for the Simultaneous Analysis of Common and Rare Variants in Complex Traits |
title_full | A Novel Approach for the Simultaneous Analysis of Common and Rare Variants in Complex Traits |
title_fullStr | A Novel Approach for the Simultaneous Analysis of Common and Rare Variants in Complex Traits |
title_full_unstemmed | A Novel Approach for the Simultaneous Analysis of Common and Rare Variants in Complex Traits |
title_short | A Novel Approach for the Simultaneous Analysis of Common and Rare Variants in Complex Traits |
title_sort | novel approach for the simultaneous analysis of common and rare variants in complex traits |
topic | Methodology |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3273305/ https://www.ncbi.nlm.nih.gov/pubmed/22346348 http://dx.doi.org/10.4137/BBI.S8852 |
work_keys_str_mv | AT yuanao anovelapproachforthesimultaneousanalysisofcommonandrarevariantsincomplextraits AT chenguanjie anovelapproachforthesimultaneousanalysisofcommonandrarevariantsincomplextraits AT zhouyanxun anovelapproachforthesimultaneousanalysisofcommonandrarevariantsincomplextraits AT bentleyamy anovelapproachforthesimultaneousanalysisofcommonandrarevariantsincomplextraits AT rotimicharles anovelapproachforthesimultaneousanalysisofcommonandrarevariantsincomplextraits AT yuanao novelapproachforthesimultaneousanalysisofcommonandrarevariantsincomplextraits AT chenguanjie novelapproachforthesimultaneousanalysisofcommonandrarevariantsincomplextraits AT zhouyanxun novelapproachforthesimultaneousanalysisofcommonandrarevariantsincomplextraits AT bentleyamy novelapproachforthesimultaneousanalysisofcommonandrarevariantsincomplextraits AT rotimicharles novelapproachforthesimultaneousanalysisofcommonandrarevariantsincomplextraits |