Gene expression analysis by quantitative reverse transcription PCR (qRT–PCR) allows accurate quantifications of messenger RNA (mRNA) levels over different samples. Corrective methods for different steps in the qRT–PCR reaction have been reported; however, statistical analysis and presentation of substantially variable biological repeats present problems and are often not meaningful, for example, in a biological system such as mouse embryonic stem cell differentiation. Based on a series of sequential corrections, including log transformation, mean centering, and autoscaling, we describe a robust and powerful standardization method that can be used on highly variable data sets to draw statistically reliable conclusions.