Differential analysis of DNA microarray gene expression data
Article first published online: 6 FEB 2003
Volume 47, Issue 4, pages 871–877, February 2003
How to Cite
Hatfield, G. W., Hung, S.-p. and Baldi, P. (2003), Differential analysis of DNA microarray gene expression data. Molecular Microbiology, 47: 871–877. doi: 10.1046/j.1365-2958.2003.03298.x
- Issue published online: 6 FEB 2003
- Article first published online: 6 FEB 2003
- Accepted 7 October, 2002.
Here, we review briefly the sources of experimental and biological variance that affect the interpretation of high-dimensional DNA microarray experiments. We discuss methods using a regularized t-test based on a Bayesian statistical framework that allow the identification of differentially regulated genes with a higher level of confidence than a simple t-test when only a few experimental replicates are available. We also describe a computational method for calculating the global false-positive and false-negative levels inherent in a DNA microarray data set. This method provides a probability of differential expression for each gene based on experiment-wide false-positive and -negative levels driven by experimental error and biological variance.