CGHpower: exploring sample size calculations for chromosomal copy number experiments

<p>Abstract</p> <p>Background</p> <p>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 sam...

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Main Authors: Knuutila Sakari, Ferreira José A, Scheinin Ilari, Meijer Gerrit A, van de Wiel Mark A, Ylstra Bauke
Format: Article
Language:English
Published: BMC 2010-06-01
Series:BMC Bioinformatics
Online Access:http://www.biomedcentral.com/1471-2105/11/331
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author Knuutila Sakari
Ferreira José A
Scheinin Ilari
Meijer Gerrit A
van de Wiel Mark A
Ylstra Bauke
author_facet Knuutila Sakari
Ferreira José A
Scheinin Ilari
Meijer Gerrit A
van de Wiel Mark A
Ylstra Bauke
author_sort Knuutila Sakari
collection DOAJ
description <p>Abstract</p> <p>Background</p> <p>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).</p> <p>Results</p> <p>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.</p> <p>Conclusions</p> <p>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.</p> <p>The CGHpower web application and the program outputs from evaluation data sets can be freely accessed at <url>http://www.cangem.org/cghpower/</url></p>
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spelling doaj.art-c76aef491ac64e73b11cad1b038810262022-12-21T23:22:36ZengBMCBMC Bioinformatics1471-21052010-06-0111133110.1186/1471-2105-11-331CGHpower: exploring sample size calculations for chromosomal copy number experimentsKnuutila SakariFerreira José AScheinin IlariMeijer Gerrit Avan de Wiel Mark AYlstra Bauke<p>Abstract</p> <p>Background</p> <p>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).</p> <p>Results</p> <p>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.</p> <p>Conclusions</p> <p>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.</p> <p>The CGHpower web application and the program outputs from evaluation data sets can be freely accessed at <url>http://www.cangem.org/cghpower/</url></p>http://www.biomedcentral.com/1471-2105/11/331
spellingShingle Knuutila Sakari
Ferreira José A
Scheinin Ilari
Meijer Gerrit A
van de Wiel Mark A
Ylstra Bauke
CGHpower: exploring sample size calculations for chromosomal copy number experiments
BMC Bioinformatics
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
url http://www.biomedcentral.com/1471-2105/11/331
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