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CGHpower: exploring sample size calculations for chromosomal copy number experiments

BACKGROUND: Determining a suitable sample size is an important step in the planning of microarray experiments. Increasing the number of arrays gives more statistical power, but adds to the total cost of the experiment. Several approaches for sample size determination have been developed for expressi...

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Autores principales: Scheinin, Ilari, Ferreira, José A, Knuutila, Sakari, Meijer, Gerrit A, van de Wiel, Mark A, Ylstra, Bauke
Formato: Texto
Lenguaje:English
Publicado: BioMed Central 2010
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2911457/
https://www.ncbi.nlm.nih.gov/pubmed/20565750
http://dx.doi.org/10.1186/1471-2105-11-331
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author Scheinin, Ilari
Ferreira, José A
Knuutila, Sakari
Meijer, Gerrit A
van de Wiel, Mark A
Ylstra, Bauke
author_facet Scheinin, Ilari
Ferreira, José A
Knuutila, Sakari
Meijer, Gerrit A
van de Wiel, Mark A
Ylstra, Bauke
author_sort Scheinin, Ilari
collection PubMed
description BACKGROUND: Determining a suitable sample size is an important step in the planning of microarray experiments. Increasing the number of arrays gives more statistical power, but adds to the total cost of the experiment. Several approaches for sample size determination have been developed for expression array studies, but so far none has been proposed for array comparative genomic hybridization (aCGH). RESULTS: Here we explore power calculations for aCGH experiments comparing two groups. In a pilot experiment CGHpower estimates the biological diversity between groups and provides a statistical framework for estimating average power as a function of sample size. As the method requires pilot data, it can be used either in the planning stage of larger studies or in estimating the power achieved in past experiments. CONCLUSIONS: The proposed method relies on certain assumptions. According to our evaluation with public and simulated data sets, they do not always hold true. Violation of the assumptions typically leads to unreliable sample size estimates. Despite its limitations, this method is, at least to our knowledge, the only one currently available for performing sample size calculations in the context of aCGH. Moreover, the implementation of the method provides diagnostic plots that allow critical assessment of the assumptions on which it is based and hence on the feasibility and reliability of the sample size calculations in each case. The CGHpower web application and the program outputs from evaluation data sets can be freely accessed at http://www.cangem.org/cghpower/
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spelling pubmed-29114572010-07-29 CGHpower: exploring sample size calculations for chromosomal copy number experiments Scheinin, Ilari Ferreira, José A Knuutila, Sakari Meijer, Gerrit A van de Wiel, Mark A Ylstra, Bauke BMC Bioinformatics Software BACKGROUND: Determining a suitable sample size is an important step in the planning of microarray experiments. Increasing the number of arrays gives more statistical power, but adds to the total cost of the experiment. Several approaches for sample size determination have been developed for expression array studies, but so far none has been proposed for array comparative genomic hybridization (aCGH). RESULTS: Here we explore power calculations for aCGH experiments comparing two groups. In a pilot experiment CGHpower estimates the biological diversity between groups and provides a statistical framework for estimating average power as a function of sample size. As the method requires pilot data, it can be used either in the planning stage of larger studies or in estimating the power achieved in past experiments. CONCLUSIONS: The proposed method relies on certain assumptions. According to our evaluation with public and simulated data sets, they do not always hold true. Violation of the assumptions typically leads to unreliable sample size estimates. Despite its limitations, this method is, at least to our knowledge, the only one currently available for performing sample size calculations in the context of aCGH. Moreover, the implementation of the method provides diagnostic plots that allow critical assessment of the assumptions on which it is based and hence on the feasibility and reliability of the sample size calculations in each case. The CGHpower web application and the program outputs from evaluation data sets can be freely accessed at http://www.cangem.org/cghpower/ BioMed Central 2010-06-17 /pmc/articles/PMC2911457/ /pubmed/20565750 http://dx.doi.org/10.1186/1471-2105-11-331 Text en Copyright ©2010 Scheinin et al; 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 Software
Scheinin, Ilari
Ferreira, José A
Knuutila, Sakari
Meijer, Gerrit A
van de Wiel, Mark A
Ylstra, Bauke
CGHpower: exploring sample size calculations for chromosomal copy number experiments
title CGHpower: exploring sample size calculations for chromosomal copy number experiments
title_full CGHpower: exploring sample size calculations for chromosomal copy number experiments
title_fullStr CGHpower: exploring sample size calculations for chromosomal copy number experiments
title_full_unstemmed CGHpower: exploring sample size calculations for chromosomal copy number experiments
title_short CGHpower: exploring sample size calculations for chromosomal copy number experiments
title_sort cghpower: exploring sample size calculations for chromosomal copy number experiments
topic Software
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2911457/
https://www.ncbi.nlm.nih.gov/pubmed/20565750
http://dx.doi.org/10.1186/1471-2105-11-331
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