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Biostatistics Advance Access originally published online on June 18, 2008
Biostatistics 2009 10(1):80-93; doi:10.1093/biostatistics/kxn017
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© The Author 2008. Published by Oxford University Press. All rights reserved. For permissions, please e-mail: journals.permissions@oxfordjournals.org.

Gene profiling for determining pluripotent genes in a time course microarray experiment

J. Tuke*, G. F. V. Glonek and P. J. Solomon

School of Mathematical Sciences, The University of Adelaide, Adelaide SA 5005, Australia, simon.tuke{at}adelaide.edu.au

* To whom correspondence should be addressed.

In microarray experiments, it is often of interest to identify genes which have a prespecified gene expression profile with respect to time. Methods available in the literature are, however, typically not stringent enough in identifying such genes, particularly when the profile requires equivalence of gene expression levels at certain time points. In this paper, the authors introduce a new methodology, called gene profiling, that uses simultaneous differential and equivalent gene expression level testing to rank genes according to a prespecified gene expression profile. Gene profiling treats the vector of true gene expression levels as a linear combination of appropriate vectors, for example, vectors that give the required criteria for the profile. This gene profile model is fitted to the data, and the resulting parameter estimates are summarized in a single test statistic that is then used to rank the genes. The theoretical underpinnings of gene profiling (equivalence testing, intersection–union tests) are discussed in this paper, and the gene profiling methodology is applied to our motivating stem-cell experiment.

Keywords: Gene expression; Gene profiling; Linear model; Microarray; Pluripotency; Stem cell; Time course experiment

Received July 31, 2007; revised January 23, 2008; revised February 25, 2008; revised March 26, 2008; accepted for publication May 12, 2008.


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