Data Analysis Methods:
There are two methods, both equally valid, for analyzing data obtained from real time PCR: Relative Standard Curve Method and Comparative CT Method. The first, relative standard curve method, is useful for investigators that have a limited number of cDNA samples and a large number of genes of interest. The comparative CT method is useful for investigators who have a lage number of cDNA samples and a limited number of genes of interest.
Real Time PCR Theory:
The equation that describes the exponential amplification of PCR is:
where Xn is the number of template copies at cycle n, X0 is the initial number of template copies, EX is the efficiency of target amplification, and n is the number of cycles.
The threshold cycle (CT) indicates the fractional cycle number at which the amount of amplified copies reaches a fixed threshold.
where XT is the threshold number of copies and CT,X is the threshold cycle
A similar equation for the endogenous reference (housekeeping gene like GAPDH, b-actin, b2M, or rRNA) is given by equation 3.
where R is denoted as the quantities corresponding to the endogenous reference gene.
For normalization of the gene of interest to the endogenous reference, we can derive the following ratio giving the ratio of copy number of the gene of interest to the endogenous reference gene at the threshold cycle (K).
Assuming the efficiencies of the gene of interest amplification and the endogenous reference are equal (E = EX = ER) we can further derive equation 4 to
where delta CT is equal to CT,X - CT,R
Further rearranging equation 7, we have
Where delta delta CT is the difference in threshold cycles for the target and control samples. For amplicons designed and optimized according to ABI (amplicon size < 150 bp), the efficiency is close to one (E = 1). Therefore the amount of target normalized to an endogenous reference and relative to a control sample is given by
Where CT,X is the threshold cycle of the gene of interest and CT,R is the threshold cycle of the endogeneous reference gene (e.g. GAPDH)