In 1995, two methods of genome-wide expression profiling were first described: expression microarrays and serial analysis of gene expression (SAGE). In the subsequent 10 years, many hundreds of papers have been published describing the application of these technologies to a wide spectrum of biological and clinical questions. Common to all of this research is a basic process of data gathering and analysis. The techniques and statistical and bio-informatic tools involved in this process are reviewed. The processes of class discovery (using clustering and self-organizing maps), class prediction (weighted voting, k nearest neighbour, support vector machines, and artificial neural networks), target identification (fold change, discriminant analysis, and principal component analysis), and target validation (RT-PCR and tissue microarrays) are described. Finally, the diagnostic problem of adenocarcinomas that present as metastases of unknown origin is reviewed, and it is demonstrated how integration of expression profiling techniques promises to throw new light on this important clinical challenge.