Microarray technology has revolutionized biomedical research because it is now possible to concurrently determine the gene expression levels for the whole genome of a target organism. The accuracy of the computed gene expression levels is extremely important for the successful use of this technology. However, microarray gene expression measurements are inherently very ‘noisy’, meaning that appropriate techniques are required to compute accurate gene expression levels. Therefore, the pre-processing of microarray data warrants special consideration. Although there are many candidate techniques for the pre-processing of microarray data, there is no clear-cut best option. In this review, we discuss some of the most important pre-processing techniques applicable to the Affymetrix microarray platform. We also discuss the problems involved in evaluating the different candidate techniques and consider other crucial issues related to the preprocessing of Affymetrix microarray data.
Keywords: Low-level processing, normalization, hybridization, summarization, PM probes, MM probes, background
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