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Genetic model misspecification in genetic association studies
OBJECTIVE: The underlying model of the genetic determinant of a trait is generally not known with certainty a priori. Hence, in genetic association studies, a dominant model might be erroneously modelled as additive, an error investigated previously. We explored this question, for candidate gene stu...
Autores principales: | , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2017
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5678796/ https://www.ncbi.nlm.nih.gov/pubmed/29115983 http://dx.doi.org/10.1186/s13104-017-2911-3 |
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author | Gaye, Amadou Davis, Sharon K. |
author_facet | Gaye, Amadou Davis, Sharon K. |
author_sort | Gaye, Amadou |
collection | PubMed |
description | OBJECTIVE: The underlying model of the genetic determinant of a trait is generally not known with certainty a priori. Hence, in genetic association studies, a dominant model might be erroneously modelled as additive, an error investigated previously. We explored this question, for candidate gene studies, by evaluating the sample size required to compensate for the misspecification and improve inference at the analysis stage. Power calculations were carried out with (1) the true dominant model and (2) the incorrect additive model. Empirical power, sample size and effect size were compared between scenarios (1) and (2). In each of the scenarios the estimates were evaluated for a rare (minor allele frequency < 0.01), low frequency (0.01 ≤ minor allele frequency < 0.05) and common (minor allele frequency ≥ 0.05) single nucleotide polymorphism. RESULTS: The results confirm the detrimental effect of the misspecification error on power and effect size for any minor allele frequency. The implications of the error are not negligible; therefore, candidate gene studies should consider the more conservative sample size to compensate for the effect of error. When it is not possible to extend the sample size, methods that help mitigate the impact of the error should be systematically used. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (10.1186/s13104-017-2911-3) contains supplementary material, which is available to authorized users. |
format | Online Article Text |
id | pubmed-5678796 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2017 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-56787962017-11-17 Genetic model misspecification in genetic association studies Gaye, Amadou Davis, Sharon K. BMC Res Notes Research Note OBJECTIVE: The underlying model of the genetic determinant of a trait is generally not known with certainty a priori. Hence, in genetic association studies, a dominant model might be erroneously modelled as additive, an error investigated previously. We explored this question, for candidate gene studies, by evaluating the sample size required to compensate for the misspecification and improve inference at the analysis stage. Power calculations were carried out with (1) the true dominant model and (2) the incorrect additive model. Empirical power, sample size and effect size were compared between scenarios (1) and (2). In each of the scenarios the estimates were evaluated for a rare (minor allele frequency < 0.01), low frequency (0.01 ≤ minor allele frequency < 0.05) and common (minor allele frequency ≥ 0.05) single nucleotide polymorphism. RESULTS: The results confirm the detrimental effect of the misspecification error on power and effect size for any minor allele frequency. The implications of the error are not negligible; therefore, candidate gene studies should consider the more conservative sample size to compensate for the effect of error. When it is not possible to extend the sample size, methods that help mitigate the impact of the error should be systematically used. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (10.1186/s13104-017-2911-3) contains supplementary material, which is available to authorized users. BioMed Central 2017-11-07 /pmc/articles/PMC5678796/ /pubmed/29115983 http://dx.doi.org/10.1186/s13104-017-2911-3 Text en © The Author(s) 2017 Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated. |
spellingShingle | Research Note Gaye, Amadou Davis, Sharon K. Genetic model misspecification in genetic association studies |
title | Genetic model misspecification in genetic association studies |
title_full | Genetic model misspecification in genetic association studies |
title_fullStr | Genetic model misspecification in genetic association studies |
title_full_unstemmed | Genetic model misspecification in genetic association studies |
title_short | Genetic model misspecification in genetic association studies |
title_sort | genetic model misspecification in genetic association studies |
topic | Research Note |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5678796/ https://www.ncbi.nlm.nih.gov/pubmed/29115983 http://dx.doi.org/10.1186/s13104-017-2911-3 |
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