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Abstract
High density oligonucleotide array technology is widely used in many areas of biomedical
research for quantitative and highly parallel measurements of gene expression. Affymetrix
GeneChip arrays are the most popular. In this technology each gene is typically represented
by a set of 11-20 pairs of probes. In order to obtain expression measures it is necessary
to summarize the probe level data. Using two extensive spike-in studies and a dilution
study, we developed a set of tools for assessing the effectiveness of expression measures.
We found that the performance of the current version of the default expression measure
provided by Affymetrix Microarray Suite can be significantly improved by the use of
probe level summaries derived from empirically motivated statistical models. In particular,
improvements in the ability to detect differentially expressed genes are demonstrated.