Gene expression analysis is a widely used and powerful method for investigating the transcriptional behavior of biological systems, for classifying cell states in disease and for many other purposes. Recent studies indicate that common assumptions currently embedded in experimental and analytical practices can lead to misinterpretation of global gene expression data. We discuss these assumptions and describe solutions that should minimize erroneous interpretation of gene expression data from

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... tiple analysis platforms. Global Gene Expression Analysis Global gene expression analysis provides quantitative information about the population of RNA species in cells and tissues. It is an exceptionally powerful tool of molecular biology that is used to explore basic biology, diagnose disease, facilitate drug discovery and development, tailor therapeutics to specific pathologies and generate databases with information about living processes. Consequently, expression analysis is among the most commonly used methods in modern biology; there are over 750,000 expression datasets in the NCBI Gene Expression Omnibus (GEO) public database (Edgar et al., 2002) . Global gene expression analysis uses DNA microarrays, RNA-Seq, and other methods to measure the levels of RNA species in biological systems (