Power and Type-I Error in a Global Test of Differential Genetic Expression

Abstract

Methods have been proposed to test for differential gene expression in microarray experiments. These include gene-specific tests and global-type tests, such as fitting mixture models to the distribution of test statistics or p-values or fitting an ANOVA model and testing for a gene-treatment interaction effect. This talk focuses on the latter for a particular microarray experimental design and discusses the effects of violations of ANOVA assumptions (e.g., correlated expressions, unequal variances, and nonnormal data) on type-I error and power. The residual bootstrap is considered as a way to compensate for effects of these violations. Finally, the distributions of gene-specific p-values are compared when computed using usual t-tests versus using effects estimated from the ANOVA model.

Department(s)

Mathematics and Statistics

Keywords and Phrases

anova; microarray; p-valve; power

Document Type

Article - Conference proceedings

Document Version

Citation

File Type

text

Language(s)

English

Rights

© 2005 American Statistical Association, All rights reserved.

Publication Date

01 Jan 2005

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