FCI: an R-based algorithm for evaluating uncertainty of absolute real-time PCR quantification

Area of Science:

• Molecular Biology
• Bioinformatics

Background:

• Real-time PCR (polymerase chain reaction) is a key technique for nucleic acid quantification.
• Accurate analysis of real-time PCR data is crucial for reliable experimental results.

Purpose of the Study:

• To introduce FCI, an R code designed for analyzing real-time PCR experimental data.
• To enhance the information content and accuracy of real-time PCR assays.

Main Methods:

• FCI algorithm estimates standard curve features, nucleic acid concentrations, and confidence intervals using Fieller's theorem.
• The code was tested using real data from an international external quality assessment program for quantitative assays.

Main Results:

• FCI provides accurate estimation of standard curve parameters and nucleic acid concentrations.
• The diagnostic figure generated by FCI aids in assessing the quality of the quantification process.

Conclusions:

• FCI is a freeware program that improves the analytical capabilities for real-time PCR.
• The tool increases the information content derived from real-time PCR experiments.