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

Area of Science:

• Molecular Biology
• Biotechnology
• Genomics

Background:

• Quantitative Polymerase Chain Reaction (qPCR) is a cornerstone technique for gene expression analysis.
• The classical threshold cycle (C_T) method in qPCR has inherent limitations, including ignoring amplification efficiency.
• Existing alternative methods for qPCR analysis have not statistically outperformed the C_T method.

Purpose of the Study:

• To develop a novel qPCR analysis method that addresses the shortcomings of the traditional C_T method.
• To introduce the f₀% method, which estimates initial fluorescence as a percentage of predicted maximum fluorescence.

Main Methods:

• Developed the f₀% method utilizing a modified sigmoid function to fit amplification curves.
• Incorporated a linear component for background noise subtraction.
• Estimated initial fluorescence as a percentage of predicted maximum fluorescence (f₀%).

Main Results:

• The f₀% method demonstrated superior performance compared to C_T, LinRegPCR, and Cy₀ methods in both absolute and relative quantification.
• f₀% significantly reduced coefficient of variation (CV%), variance, and absolute relative error across multiple datasets and DNA-binding dyes.
• Specifically, f₀% reduced errors by up to 1.83-fold compared to existing methods.

Conclusions:

• The f₀% method is recommended for analyzing and reporting qPCR results due to its demonstrated advantages in accuracy and reliability.
• An accessible macro-enabled Excel file implementing the f₀% method is available for user convenience.
• A user manual for the f₀% Excel tool is provided on GitHub for ease of implementation.