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Briefings in Bioinformatics Advance Access published online on February 3, 2006
Briefings in Bioinformatics, doi:10.1093/bib/bbk002
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© The Author 2006. Published by Oxford University Press. For Permissions, please email: journals.permissions@oxfordjournals.org
Received July 21, 2005
Accepted November 2, 2005

Original Article

Estimation and control of multiple testing error rates for microarray studies

Stanley B. Pounds *

* To whom correspondence should be addressed.
Stanley B. Pounds, E-mail: stanley.pounds{at}stjude.org


  Abstract

The analysis of microarray data often involves performing a large number of statistical tests, usually at least one test per queried gene. Each test has a certain probability of reaching an incorrect inference; therefore, it is crucial to estimate or control error rates that measure the occurrence of erroneous conclusions in reporting and interpreting the results of a microarray study. In recent years, many innovative statistical methods have been developed to estimate or control various error rates for microarray studies. Researchers need guidance choosing the appropriate statistical methods for analysing these types of data sets. This review describes a family of methods that use a set of P-values to estimate or control the false discovery rate and similar error rates. Finally, these methods are classified in a manner that suggests the appropriate method for specific applications and diagnostic procedures that can identify problems in the analysis are described.

Keywords: microarray; gene expression; multiple testing; false discovery rate; error rate; statistical analysis.
Stanley Pounds is an assistant member of the department of biostatistics, St. Jude Children's Research Hospital, Memphis, TN, USA. His research focuses on developing and improving statistical methods for the analysis of microarray gene expression data, with special emphasis on methods that estimate or control multiple testing error rates.
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