The article discusses the impact of baseline estimation errors on PCR efficiency in quantitative PCR (qPCR) data analysis. It highlights that errors in baseline estimation directly affect the observed PCR efficiency values, leading to exponential propagation of errors in the estimated starting concentrations and fold-difference results. The authors developed an algorithm to estimate the baseline by reconstructing the log-linear phase downward from the early plateau phase of the PCR reaction, resulting in very reproducible PCR efficiency values. PCR efficiency values were determined by fitting a regression line to data points in the log-linear phase. Using the mean of these PCR efficiencies per amplicon significantly reduced variability and bias in qPCR results. The study emphasizes the importance of accurate baseline estimation for reliable qPCR analysis, as errors in baseline can lead to biased efficiency values and incorrect gene expression ratios. The proposed algorithm, which estimates the baseline without relying on early cycles, improves the accuracy of PCR efficiency and starting concentration calculations. The article also discusses the implications of using different PCR efficiency values in qPCR data analysis, showing that using amplicon-specific efficiencies reduces bias compared to using a common efficiency. The study concludes that accurate baseline estimation is crucial for reliable qPCR data analysis and that the proposed algorithm provides a robust solution for this challenge.The article discusses the impact of baseline estimation errors on PCR efficiency in quantitative PCR (qPCR) data analysis. It highlights that errors in baseline estimation directly affect the observed PCR efficiency values, leading to exponential propagation of errors in the estimated starting concentrations and fold-difference results. The authors developed an algorithm to estimate the baseline by reconstructing the log-linear phase downward from the early plateau phase of the PCR reaction, resulting in very reproducible PCR efficiency values. PCR efficiency values were determined by fitting a regression line to data points in the log-linear phase. Using the mean of these PCR efficiencies per amplicon significantly reduced variability and bias in qPCR results. The study emphasizes the importance of accurate baseline estimation for reliable qPCR analysis, as errors in baseline can lead to biased efficiency values and incorrect gene expression ratios. The proposed algorithm, which estimates the baseline without relying on early cycles, improves the accuracy of PCR efficiency and starting concentration calculations. The article also discusses the implications of using different PCR efficiency values in qPCR data analysis, showing that using amplicon-specific efficiencies reduces bias compared to using a common efficiency. The study concludes that accurate baseline estimation is crucial for reliable qPCR data analysis and that the proposed algorithm provides a robust solution for this challenge.