Digging into the extremes: a useful approach for the analysis of rare variants with continuous traits?

The common disease/rare variant hypothesis predicts that rare variants with large effects will have a strong impact on corresponding phenotypes. Therefore it is assumed that rare functional variants are enriched in the extremes of the phenotype distribution. In this analysis of the Genetic Analysis...

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Autor principal: Lamina, Claudia
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2011
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3287828/
https://www.ncbi.nlm.nih.gov/pubmed/22373517
http://dx.doi.org/10.1186/1753-6561-5-S9-S105
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author Lamina, Claudia
author_facet Lamina, Claudia
author_sort Lamina, Claudia
collection PubMed
description The common disease/rare variant hypothesis predicts that rare variants with large effects will have a strong impact on corresponding phenotypes. Therefore it is assumed that rare functional variants are enriched in the extremes of the phenotype distribution. In this analysis of the Genetic Analysis Workshop 17 data set, my aim is to detect genes with rare variants that are associated with quantitative traits using two general approaches: analyzing the association with the complete distribution of values by means of linear regression and using statistical tests based on the tails of the distribution (bottom 10% of values versus top 10%). Three methods are used for this extreme phenotype approach: Fisher’s exact test, weighted-sum method, and beta method. Rare variants were collapsed on the gene level. Linear regression including all values provided the highest power to detect rare variants. Of the three methods used in the extreme phenotype approach, the beta method performed best. Furthermore, the sample size was enriched in this approach by adding additional samples with extreme phenotype values. Doubling the sample size using this approach, which corresponds to only 40% of sample size of the original continuous trait, yielded a comparable or even higher power than linear regression. If samples are selected primarily for sequencing, enriching the analysis by gathering a greater proportion of individuals with extreme values in the phenotype of interest rather than in the general population leads to a higher power to detect rare variants compared to analyzing a population-based sample with equivalent sample size.
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spelling pubmed-32878282012-02-28 Digging into the extremes: a useful approach for the analysis of rare variants with continuous traits? Lamina, Claudia BMC Proc Proceedings The common disease/rare variant hypothesis predicts that rare variants with large effects will have a strong impact on corresponding phenotypes. Therefore it is assumed that rare functional variants are enriched in the extremes of the phenotype distribution. In this analysis of the Genetic Analysis Workshop 17 data set, my aim is to detect genes with rare variants that are associated with quantitative traits using two general approaches: analyzing the association with the complete distribution of values by means of linear regression and using statistical tests based on the tails of the distribution (bottom 10% of values versus top 10%). Three methods are used for this extreme phenotype approach: Fisher’s exact test, weighted-sum method, and beta method. Rare variants were collapsed on the gene level. Linear regression including all values provided the highest power to detect rare variants. Of the three methods used in the extreme phenotype approach, the beta method performed best. Furthermore, the sample size was enriched in this approach by adding additional samples with extreme phenotype values. Doubling the sample size using this approach, which corresponds to only 40% of sample size of the original continuous trait, yielded a comparable or even higher power than linear regression. If samples are selected primarily for sequencing, enriching the analysis by gathering a greater proportion of individuals with extreme values in the phenotype of interest rather than in the general population leads to a higher power to detect rare variants compared to analyzing a population-based sample with equivalent sample size. BioMed Central 2011-11-29 /pmc/articles/PMC3287828/ /pubmed/22373517 http://dx.doi.org/10.1186/1753-6561-5-S9-S105 Text en Copyright ©2011 Lamina; licensee BioMed Central Ltd. http://creativecommons.org/licenses/by/2.0 This is an open access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Proceedings
Lamina, Claudia
Digging into the extremes: a useful approach for the analysis of rare variants with continuous traits?
title Digging into the extremes: a useful approach for the analysis of rare variants with continuous traits?
title_full Digging into the extremes: a useful approach for the analysis of rare variants with continuous traits?
title_fullStr Digging into the extremes: a useful approach for the analysis of rare variants with continuous traits?
title_full_unstemmed Digging into the extremes: a useful approach for the analysis of rare variants with continuous traits?
title_short Digging into the extremes: a useful approach for the analysis of rare variants with continuous traits?
title_sort digging into the extremes: a useful approach for the analysis of rare variants with continuous traits?
topic Proceedings
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3287828/
https://www.ncbi.nlm.nih.gov/pubmed/22373517
http://dx.doi.org/10.1186/1753-6561-5-S9-S105
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