Introducing the f0% method: a reliable and accurate approach for qPCR analysis

qPCR is a widely used technique in scientific research as a basic tool in gene expression analysis. Classically, the quantitative endpoint of qPCR is the threshold cycle (C.sub.T) that ignores differences in amplification efficiency among many other drawbacks. While other methods have been developed to analyze qPCR results, none has statistically proven to perform better than the C.sub.T method. Therefore, we aimed to develop a new qPCR analysis method that overcomes the limitations of the C.sub.T method. Our f.sub.0% [eff naught percent] method depends on a modified flexible sigmoid function to fit the amplification curve with a linear part to subtract the background noise. Then, the initial fluorescence is estimated and reported as a percentage of the predicted maximum fluorescence (f.sub.0%). The performance of the new f.sub.0% method was compared against the C.sub.T method along with another two outstanding methods--LinRegPCR and Cy.sub.0. The comparison regarded absolute and relative quantifications and used 20 dilution curves obtained from 7 different datasets that utilize different DNA-binding dyes. In the case of absolute quantification, f.sub.0% reduced CV%, variance, and absolute relative error by 1.66, 2.78, and 1.8 folds relative to C.sub.T; and by 1.65, 2.61, and 1.71 folds relative to LinRegPCR, respectively. While, regarding relative quantification, f.sub.0% reduced CV% by 1.76, 1.55, and 1.25 folds and variance by 3.13, 2.31, and 1.57 folds regarding C.sub.T, LinRegPCR, and Cy.sub.0, respectively. Finally, f.sub.0% reduced the absolute relative error caused by LinRegPCR by 1.83 folds. We recommend using the f.sub.0% method to analyze and report qPCR results based on its reported advantages. Finally, to simplify the usage of the f.sub.0% method, it was implemented in a macro-enabled Excel file with a user manual located on https://github.com/Mahmoud0Gamal/F0-perc/releases.