ABSTRACT
Independently of the platform and the analysis methods used, the result of a microarray experiment is, in most cases, a list of genes found to be differentially expressed.1 The common challenge faced by the researchers is to translate such lists of differentially regulated genes into a better understanding
of the automatic ontological analysis approach discussed in Chapter 23. Currently, this over-representation (ORA) approach is the de facto standard for the secondary analysis of high throughput experiments and a large number of tools have been developed for this purpose. Since 2001 when the first such tool appeared, over a dozen other tools have been proposed for this type of analysis and more tools continue to appear every day (see Fig. 25.1). Although these tools use the same general approach, they differ greatly in many respects that influence in an essential way the results of the analysis. In most cases, researchers using such tools are either unaware of, or confused about certain crucial features.
