Standardization of real-time PCR gene expression data from independent biological replicates

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.