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The Empirical Power of Rare Variant Association Methods: Results from Sanger Sequencing in 1,998 Individuals
The role of rare genetic variation in the etiology of complex disease remains unclear. However, the development of next-generation sequencing technologies offers the experimental opportunity to address this question. Several novel statistical methodologies have been recently proposed to assess the c...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Public Library of Science
2012
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3271058/ https://www.ncbi.nlm.nih.gov/pubmed/22319458 http://dx.doi.org/10.1371/journal.pgen.1002496 |
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author | Ladouceur, Martin Dastani, Zari Aulchenko, Yurii S. Greenwood, Celia M. T. Richards, J. Brent |
author_facet | Ladouceur, Martin Dastani, Zari Aulchenko, Yurii S. Greenwood, Celia M. T. Richards, J. Brent |
author_sort | Ladouceur, Martin |
collection | PubMed |
description | The role of rare genetic variation in the etiology of complex disease remains unclear. However, the development of next-generation sequencing technologies offers the experimental opportunity to address this question. Several novel statistical methodologies have been recently proposed to assess the contribution of rare variation to complex disease etiology. Nevertheless, no empirical estimates comparing their relative power are available. We therefore assessed the parameters that influence their statistical power in 1,998 individuals Sanger-sequenced at seven genes by modeling different distributions of effect, proportions of causal variants, and direction of the associations (deleterious, protective, or both) in simulated continuous trait and case/control phenotypes. Our results demonstrate that the power of recently proposed statistical methods depend strongly on the underlying hypotheses concerning the relationship of phenotypes with each of these three factors. No method demonstrates consistently acceptable power despite this large sample size, and the performance of each method depends upon the underlying assumption of the relationship between rare variants and complex traits. Sensitivity analyses are therefore recommended to compare the stability of the results arising from different methods, and promising results should be replicated using the same method in an independent sample. These findings provide guidance in the analysis and interpretation of the role of rare base-pair variation in the etiology of complex traits and diseases. |
format | Online Article Text |
id | pubmed-3271058 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2012 |
publisher | Public Library of Science |
record_format | MEDLINE/PubMed |
spelling | pubmed-32710582012-02-08 The Empirical Power of Rare Variant Association Methods: Results from Sanger Sequencing in 1,998 Individuals Ladouceur, Martin Dastani, Zari Aulchenko, Yurii S. Greenwood, Celia M. T. Richards, J. Brent PLoS Genet Research Article The role of rare genetic variation in the etiology of complex disease remains unclear. However, the development of next-generation sequencing technologies offers the experimental opportunity to address this question. Several novel statistical methodologies have been recently proposed to assess the contribution of rare variation to complex disease etiology. Nevertheless, no empirical estimates comparing their relative power are available. We therefore assessed the parameters that influence their statistical power in 1,998 individuals Sanger-sequenced at seven genes by modeling different distributions of effect, proportions of causal variants, and direction of the associations (deleterious, protective, or both) in simulated continuous trait and case/control phenotypes. Our results demonstrate that the power of recently proposed statistical methods depend strongly on the underlying hypotheses concerning the relationship of phenotypes with each of these three factors. No method demonstrates consistently acceptable power despite this large sample size, and the performance of each method depends upon the underlying assumption of the relationship between rare variants and complex traits. Sensitivity analyses are therefore recommended to compare the stability of the results arising from different methods, and promising results should be replicated using the same method in an independent sample. These findings provide guidance in the analysis and interpretation of the role of rare base-pair variation in the etiology of complex traits and diseases. Public Library of Science 2012-02-02 /pmc/articles/PMC3271058/ /pubmed/22319458 http://dx.doi.org/10.1371/journal.pgen.1002496 Text en Ladouceur et al. http://creativecommons.org/licenses/by/4.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are properly credited. |
spellingShingle | Research Article Ladouceur, Martin Dastani, Zari Aulchenko, Yurii S. Greenwood, Celia M. T. Richards, J. Brent The Empirical Power of Rare Variant Association Methods: Results from Sanger Sequencing in 1,998 Individuals |
title | The Empirical Power of Rare Variant Association Methods: Results from Sanger Sequencing in 1,998 Individuals |
title_full | The Empirical Power of Rare Variant Association Methods: Results from Sanger Sequencing in 1,998 Individuals |
title_fullStr | The Empirical Power of Rare Variant Association Methods: Results from Sanger Sequencing in 1,998 Individuals |
title_full_unstemmed | The Empirical Power of Rare Variant Association Methods: Results from Sanger Sequencing in 1,998 Individuals |
title_short | The Empirical Power of Rare Variant Association Methods: Results from Sanger Sequencing in 1,998 Individuals |
title_sort | empirical power of rare variant association methods: results from sanger sequencing in 1,998 individuals |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3271058/ https://www.ncbi.nlm.nih.gov/pubmed/22319458 http://dx.doi.org/10.1371/journal.pgen.1002496 |
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