Polymerase chain reaction (PCR) was developed in 1983 by Kary Mullis and colleagues(Saiki et al., 1985). It involves logarithmic amplification of DNA based on the matrixand designed primers that bind to it. PCR is a process driven by cyclical alternation ofreaction temperatures in order to enable three key reactions to take place in thefollowing order: matrix denaturation, primer hybridization and elongation. If reactionsproceed with a theoretical efficiency of 100%, each complete cycle should produceduplication of basal material (Kozera and Rapacz, 2013). qPCR differs from classicalPCR by the measurement of the amplified PCR product at each cycle throughout thePCR reaction. In practice, light detector continually measures light with specificwavelength emitted by the excited fluorochrome incorporated into the newly synthesizedPCR product. Therefore, the accumulation of amplification products is followed in real-time during the exponential phase of the run, and this allows the amount of startingmaterial to be determined precisely. Real-time imaging is possible through the use ofspecial fluorescent dyes, including SYBR® green, which binds preferably to double-stranded DNA (dsDNA) (Figure 1.) Nearly 1000-fold increase in fluorescence intensityis observed when dye-DNA complex is formed (Huggett and Bustin, 2011). The mainadvantage compared to end-point PCR techniques, is that the result is independent fromthe plateau caused by the depletion and saturation of the reaction components, the latterleading to inaccurate quantification (Gachon et al., 2004). qPCR provides a highsensitivity for the detection of DNA due to a combination of the amplification performedby the PCR step and the system of detection (Bustin, 2000). Thus, it is a convenienttechnique for studies with a limited amount of starting material (Bago et al., 2002), orfor assessing the expression of a high number of genes in a swift way (Gachon et al.,2004). Compared with classical PCR, one of the main advantages of qPCR is its rapidityto provide reliable data. Gathering meaningful biological data using qPCR depends on10the whole process, from sample collection to post-qPCR data processing andnormalising procedures. Therefore, specificity, sensibility, reproducibility androbustness of the process is associated with highly standardised pre-analytical steps, liketissue sampling and storage, nucleic acid (NA) extraction and storage, NA quantity andquality control, and optimized optimized reverse transcription (RT) and/or PCRperformance (Bustin, 2004).The most important event in qPCR data analysis is to decide at which point ofamplification curve to take the sole “quantification point”. Depending on the platformand on the analysis software used, this point may be named as cycle threshold (Ct),crossing point or take-off-point. The importance of the model and algorithm used to getthe right “quantification point” or Ct is often underestimated (Pfaffl et al., 2004). All thesubsequent data analysis depends on validity of the selected Ct point. There are variousapproaches to define Ct. Most widely used are two methods: cycle threshold method (Ctmethod), second derivative maximum method (SDM).In Ct method threshold fluorescence is calculated from the initial cycles, and in eachreaction the Ct value is defined by the fractional cycle at which the fluorescenceintensity equals the prior set threshold fluorescence value. This threshold value is notdependent of sample specific efficiency and kinetics, which may lead to declinedaccuracy when samples have different efficiencies (Logan et al., 2009).