A data processing method applied to a real-time fluorescence quantitative PCR instrument

Since the outbreak of the novel coronavirus (SARS-CoV-2) in 2019, nucleic acid test results have become a crucial basis for identifying and isolating infected individuals, thereby limiting the further spread of the pandemic. To achieve accurate quantitative analysis of nucleic acid test results, this paper proposes an enhanced fluorescence signal processing method. First, Gaussian fitting [11] is employed to extract the peak values of the fluorescence signals. Subsequently, the signals are further optimized through a combination of polynomial interpolation, smoothing techniques, and a five-point moving average filter. Finally, the PCR amplification curve is modeled using a four-parameter logistic fitting [12], and the Ct value is precisely calculated by determining the intersection between the threshold line and the fitted curve. This approach demonstrates superior effectiveness in processing raw data, significantly improving the detection performance of the optical system, and providing valuable insights for the data processing methods of rotary-based real-time quantitative PCR instruments.