Microarray truths and consequences

For many, analysis of a microarray experiment starts with a spreadsheet of expression levels. While great attention is duly paid to RNA extraction, preparation and hybridization, relatively little care is devoted to extraction of expression levels from the fluorescent image. By delegating this step to a click of the mouse the exact extraction process is masked and researchers may be unwittingly compromising their data. In this review, we describe the most common mistakes committed on the path from the image to the spreadsheet and their impact on data quality. Remedies are further proposed for most of the popular microarray platforms in use today.