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Sample Size Calculation in Genetic Association Studies: A Practical Approach

Genetic association studies, testing the relationship between genetic variants and disease status, are useful tools for identifying genes that grant susceptibility to complex disorders. In such studies, an inadequate sample size may provide unreliable results: a small sample is unable to accurately...

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Autores principales: Politi, Cristina, Roumeliotis, Stefanos, Tripepi, Giovanni, Spoto, Belinda
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9863799/
https://www.ncbi.nlm.nih.gov/pubmed/36676184
http://dx.doi.org/10.3390/life13010235
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author Politi, Cristina
Roumeliotis, Stefanos
Tripepi, Giovanni
Spoto, Belinda
author_facet Politi, Cristina
Roumeliotis, Stefanos
Tripepi, Giovanni
Spoto, Belinda
author_sort Politi, Cristina
collection PubMed
description Genetic association studies, testing the relationship between genetic variants and disease status, are useful tools for identifying genes that grant susceptibility to complex disorders. In such studies, an inadequate sample size may provide unreliable results: a small sample is unable to accurately describe the population, whereas a large sample makes the study expensive and complex to run. However, in genetic association studies, the sample size calculation is often overlooked or inadequately assessed for the small number of parameters included. In light of this, herein we list and discuss the role of the statistical and genetic parameters to be considered in the sample size calculation, show examples reporting incorrect estimation and, by using a genetic software program, we provide a practical approach for the assessment of the adequate sample size in a hypothetical study aimed at analyzing a gene–disease association.
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spelling pubmed-98637992023-01-22 Sample Size Calculation in Genetic Association Studies: A Practical Approach Politi, Cristina Roumeliotis, Stefanos Tripepi, Giovanni Spoto, Belinda Life (Basel) Review Genetic association studies, testing the relationship between genetic variants and disease status, are useful tools for identifying genes that grant susceptibility to complex disorders. In such studies, an inadequate sample size may provide unreliable results: a small sample is unable to accurately describe the population, whereas a large sample makes the study expensive and complex to run. However, in genetic association studies, the sample size calculation is often overlooked or inadequately assessed for the small number of parameters included. In light of this, herein we list and discuss the role of the statistical and genetic parameters to be considered in the sample size calculation, show examples reporting incorrect estimation and, by using a genetic software program, we provide a practical approach for the assessment of the adequate sample size in a hypothetical study aimed at analyzing a gene–disease association. MDPI 2023-01-14 /pmc/articles/PMC9863799/ /pubmed/36676184 http://dx.doi.org/10.3390/life13010235 Text en © 2023 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
spellingShingle Review
Politi, Cristina
Roumeliotis, Stefanos
Tripepi, Giovanni
Spoto, Belinda
Sample Size Calculation in Genetic Association Studies: A Practical Approach
title Sample Size Calculation in Genetic Association Studies: A Practical Approach
title_full Sample Size Calculation in Genetic Association Studies: A Practical Approach
title_fullStr Sample Size Calculation in Genetic Association Studies: A Practical Approach
title_full_unstemmed Sample Size Calculation in Genetic Association Studies: A Practical Approach
title_short Sample Size Calculation in Genetic Association Studies: A Practical Approach
title_sort sample size calculation in genetic association studies: a practical approach
topic Review
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9863799/
https://www.ncbi.nlm.nih.gov/pubmed/36676184
http://dx.doi.org/10.3390/life13010235
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