Amplification efficiency: linking baseline and bias in the analysis of quantitative PCR data

By Jan Ruijter, C. Ramakers, W. Hoogaars, Y. Karlen, O. Bakker, Maurice J. B. van den Hoff, A. Moorman. Nucleic Acids Research, 2009

3,056 citations recorded by the source corpus.

Despite the central role of quantitative PCR (qPCR) in the quantification of mRNA transcripts, most analyses of qPCR data are still delegated to the software that comes with the qPCR apparatus. This is especially true for the handling of the fluorescence baseline. This article shows that baseline estimation errors are directly reflected in the observed PCR efficiency values and are thus propagated exponentially in the estimated starting concentrations as well as ‘fold-difference’ results. Because of the unknown origin and kinetics of the baseline fluorescence, the fluorescence values monitored in the initial cycles of the PCR reaction cannot be used to estimate a useful baseline value. An algorithm that estimates the baseline by reconstructing the log-linear phase downward from the early plateau phase of the PCR reaction was developed and shown to lead to very reproducible PCR efficiency values. PCR efficiency values were determined per sample by fitting a regression line to a subset of data points in the log-linear phase. The variability, as well as the bias, in qPCR results was significantly reduced when the mean of these PCR efficiencies per amplicon was used in the calculation of an estimate of the starting concentration per sample.

Subfields: Molecular Biology

View Paper: https://www.semanticscholar.org/paper/de9e7c7135b10592f434743d3f77f26239c80e59

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Citations in the corpus

• Characterization of bacterial communities in soil and sediment of a created riverine wetland complex using high-throughput 16S rRNA amplicon sequencing (2014, methodology): “Functional genes were normalzed against 16S rRNA gene using amplification efficiencies and ycle threshold values, as proposed by Ruijter et al. (2009), and the esults were presented as percentages of detected gene copies in he total bacterial community.”
• An improvement of the 2ˆ(-delta delta CT) method for quantitative real-time polymerase chain reaction data analysis. (2013, background): “Background fluorescence may originate from unbound SYBR Green dye or from fluorochrome bound to the template cDNA or primers with nontarget DNA binding (16).”
• A Basic Guide to Real Time PCR in Microbial Diagnostics: Definitions, Parameters, and Everything (2017, background): “However, this approach is not flawless as it does not take into account all possible variables that can affect the analysis (Ruijter et al., 2009).”