Simultaneous fitting of real-time PCR data with efficiency of amplification modeled as Gaussian function of target fluorescence

Here we introduce simultaneous non-linear fitting to determine – without standard curves – an optimal common EA for all samples of a group. In order to adjust EA as a function of target fluorescence, and still to describe fluorescence as a function of cycle number, we use an iterative algorithm that increases fluorescence cycle by cycle and thus simulates the PCR process. A Gauss peak function is used to model the decrease of EA with increasing amplicon accumulation. Our approach was validated experimentally with hydrolysis probe or SYBR green detection with dilution series of 5 different targets. It performed distinctly better in terms of accuracy than standard curve, DART-PCR, and LinRegPCR approaches. Based on reliable EAs, it was possible to detect that for some amplicons, extraordinary fluorescence (EA > 2.00) was generated with locked nucleic acid hydrolysis probes, but not with SYBR green.In comparison to previously reported approaches that are based on the separate analysis of each curve and on modelling EA as a function of cycle number, our approach yields more accurate and precise estimates of relative initial target levels.In real-time PCR, fluorescence is recorded at each cycle to monitor the generation of product [1]. Typically, after several cycles with no or minor changes in background fluorescence, there is a short phase with vigorous exponential increase of fluorescence, which then gradually slows down to a plateau phase. In conventional data analysis, for each fluorescence curve a crossing point (Cp) alias threshold cycle (Ct) is determined from the visible exponential amplification phase using either the fit point method or the second-derivative method [2]. It is clear that for proper calculation of initial target levels, differences in efficiency of amplification (EA) must be taken into account [3]. Even small EA differences amplify to large apparent differences in mRNA levels [4]. The above methods require the set-up of standard curves from whic