View article

Quantitative reverse transcription polymerase chain reaction (qRT-PCR) is currently viewed as the most precise technique to quantify levels of messenger RNA. Relative quantification compares the expression of a target gene under two or more experimental conditions normalized to the measured expression of a control gene. The statistical methods and software currently available for the analysis of relative quantification of RT-PCR data lack the flexibility and statistical properties to produce valid inferences in a wide range of experimental situations. In this paper we present a novel method for the analysis of relative quantification of qRT-PCR data, which consists of the analysis of cycles to threshold values (C_T) for a target and a control gene using a general linear mixed model methodology. Our method allows testing of a broader class of hypotheses than traditional analyses such as the classical comparative C_T …