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© 2012 Springer-Verlag Wien. All rights are reserved.Since the introduction of microarray technology, it has become the workhorse for mRNA expression profiling. Its application ranges from investigating gene function, regulation, and co-expression, to clinical use in diagnosis and prognosis. Over the last decade, a large number of microarray experiments have become available in public repositories often addressing similar or related hypotheses. The large compendia of gene expression data provide the opportunity to conduct meta-analyses by combining data from various independent but related studies. Such data integration has the potential to enhance the reliability and generalizability of the results of individual microarray studies. This chapter describes the meta-analysis process including objectives, data collection, annotation, analysis methods, and visualizations. For each step we present a selection of tools available and discuss associated problems and difficulties.

Original publication





Book title

Computational Medicine: Tools and Challenges

Publication Date





59 - 77