Pairwise efficiency: a new mathematical approach to qPCR data analysis increases the precision of the calibration curve assay

Abstract

Background The real-time quantitative polymerase chain reaction (qPCR) is routinely used for quantification of nucleic acids and is considered the gold standard in the field of relative nucleic acid measurements. The efficiency of the qPCR reaction is one of the most important parameters in data analysis in qPCR experiments. The Minimum Information for publication of Quantitative real-time PCR Experiments (MIQE) guidelines recommends the calibration curve as the method of choice for estimation of qPCR efficiency. The precision of this method has been reported to be between SD = 0.007 (three replicates) and SD = 0.022 (no replicates). Results In this article, we present a novel approach to the analysis of qPCR data which has been obtained by running a dilution series. Unlike previously developed methods, our method, Pairwise Efficiency, involves a new formula that describes pairwise relationships between data points on separate amplification curves and thus enables extensive statistics. The comparison of Pairwise Efficiency with the calibration curve by Monte Carlo simulation shows the two-folds improvement in the precision of estimations of efficiency and gene expression ratios on the same dataset. Conclusions The Pairwise Efficiency nearly doubles the precision in qPCR efficiency determinations compared to standard calibration curve method. This paper demonstrates that applications of combinatorial treatment of data provide the improvement of the determination. Electronic supplementary material The online version of this article (10.1186/s12859-019-2911-5) contains supplementary material, which is available to authorized users.

Critique of the pairwise method for estimating qPCR amplification efficiency: beware of correlated data!

“…Comparison of my E estimates with those in Table S7 from [11] shows general agreement, except for the additional values from my routine. Thus, the statistical properties of my estimates must be essentially the same as those of PGDW.…”

“…Viewed collectively, the 7 sets I have analyzed are not convincingly normal, which is not surprising, considering the correlated nature of the data. Still, they are not radically [11] and those obtained for 4 different C q markers using the methods of ref. [7].…”

“…A detailed examination of the pairwise method of estimating AE from Panina, et al [11] shows that the appearance of improved precision for the method is a spurious result of the inherent correlation of the data. When implemented in a statistically correct way, by direct fitting of the fluorescence data to Eq.…”

“…The dilution factor here is 2, so the 9 points to be analyzed can be fitted to the two parameters y 0 and E using. [11]. The dilution factor is 2 for these curves, which represent the lowest 3 concentrations in the first C series.…”

“…Recently Panina, et al (PGDW) have proposed a method for estimating E that might be considered an intermediate to the traditional C q calibration method and the SR methods [ 11 ]. In it, signal values deemed to lie in the early growth phase on all the amplification curves in a dilution series are analyzed simultaneously to yield a single estimate of E .…”