Fahlén J, Landfors M, Freyhult E, Bylesjö M, Trygg J, Hvidsten TR, Rydén P
Bioinformatic strategies for cDNA-microarray data processing
In: Batch Effects and Noise in Microarray Experiments: Sources and Solutions, Edited by A. Scherer, John Wiley & Sons 2009, 61-74

Pre-processing plays a vital role in cDNA-microarray data analysis. Without proper preprocessing
it is likely that the biological conclusions will be misleading. However, there
are many alternatives and in order to choose a proper pre-processing procedure it is
necessary to understand the effect of different methods. This chapter discusses several
pre-processing steps, including image analysis, background correction, normalization, and
filtering. Spike-in data are used to illustrate how different procedures affect the analytical
ability to detect differentially expressed genes and estimate their regulation. The result
shows that pre-processing has a major impact on both the experiment’s sensitivity and
its bias. However, general recommendations are hard to give, since pre-processing consists
of several actions that are highly dependent on each other. Furthermore, it is likely
that pre-processing have a major impact on downstream analysis, such as clustering and
classification, and pre-processing methods should be developed and evaluated with this
in mind.