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 multiple analysis platforms.