Description
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. Overall design: Polyadenylated RNA depleted of ribosomal content was used for preparation of two independent sequencing libraries (low-Myc & high-Myc). A panel of synthetic RNA''s was added to these populations, based on cell number.