The main focus in cDNA microarray analysis is determining which genes are
differentially expressed. Scientists apply known statistical methods to
model the structure of the experiment or develop new approaches for
assessing statistical significance and assume that the data consist of the
signal plus random noise. Here, we report the results of some exploratory
analyses of such data that show the existence of sources of significant
systematic variation which are not necessarily accounted for in standard
analyses. In particular, we construct a linearization procedure and
compare its effectiveness with that of Yang, et al. (2001). Furthermore,
we consider not only the variation due to the pin/print-tip as in previous
work, but also the row and column location on the microarray chip, and
the relative location from the well-plate. Removal of this extra
variation can affect both the size of differential gene expression, and
which genes are inferred to be differentially expressed.