The major goal of two-color cDNA microarray experiments is to measure the relative gene
expression level (i.e., relative amount of mRNA) of each gene between samples in studies of
gene expression. More specifically, given an N-sample experiment, we need all N(N – 1)/2
relative expression levels of all sample pairs of each gene for identification of the differentially
expressed genes and for clustering of gene expression patterns. However, the intensities
observed from two-color cDNA microarray experiments do not simply represent the relative
gene expression level. They are composed of signal (gene expression level), noise, and
other factors. In discussions on the experimental design of two-color cDNA microarray
experiments, little attention has been given to the fact that different combinations of test
and control samples will produce microarray intensities data with varying intrinsic composition
of factors. As a consequence, not all experimental designs for two-color cDNA
microarray experiments are able to provide all possible relative gene expression levels. This
phenomenon has never been addressed. To obtain all possible relative gene expression levels,
a novel method for two-color cDNA microarray experimental design evaluation is necessary
that will allow the making of an accurate choice. In this study, we propose a model-based
approach to illustrate how the factor composition of microarray intensities changed with
different experimental designs in two-color cDNA microarray experiments. By analyzing 12
experimental designs (including 5 general forms), we demonstrate that not all experimental
designs are able to provide all possible relative gene expression levels due to the differences
in factor composition. Our results indicate that whether an experimental design can provide
all possible relative expression levels of all sample pairs for each gene should be the
first criterion to be considered in an evaluation of experimental designs for two-color cDNA
microarray experiments.
