Robust Quantification of Polymerase Chain Reactions Using Global Fitting

Abstract

BackgroundQuantitative polymerase chain reactions (qPCR) are used to monitor relative changes in very small amounts of DNA. One drawback to qPCR is reproducibility: measuring the same sample multiple times can yield data that is so noisy that important differences can be dismissed. Numerous analytical methods have been employed that can extract the relative template abundance between samples. However, each method is sensitive to baseline assignment and to the unique shape profiles of individual reactions, which gives rise to increased variance stemming from the analytical procedure itself.Principal FindingsWe developed a simple mathematical model that accurately describes the entire PCR reaction profile using only two reaction variables that depict the maximum capacity of the reaction and feedback inhibition. This model allows quantification that is more accurate than existing methods and takes advantage of the brighter fluorescence signals from later cycles. Because the model describes the entire reaction, the influences of baseline adjustment errors, reaction efficiencies, template abundance, and signal loss per cycle could be formalized. We determined that the common cycle-threshold method of data analysis introduces unnecessary variance because of inappropriate baseline adjustments, a dynamic reaction efficiency, and also a reliance on data with a low signal-to-noise ratio.SignificanceUsing our model, fits to raw data can be used to determine template abundance with high precision, even when the data contains baseline and signal loss defects. This improvement reduces the time and cost associated with qPCR and should be applicable in a variety of academic, clinical, and biotechnological settings.

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Bias and Imprecision in Analysis of Real-Time Quantitative Polymerase Chain Reaction Data

“…[3][4][5][6][7][8] These have typically been demonstrated on specific datasets, sometimes with comparisons against other methods. However, there has been virtually no purely statistical testing to address questions of inherent bias and imprecision.…”

History, Virulence Genes, Identification and Antimicrobial Resistance of Enterococcus faecalis Isolated from Diabetic Foot Patients

“…By way of the heat, degree in the tube passes into the T m range and settles at the Ta temperature, the greatest probable number of primer molecules relative to the number of obtainable targets will have found those targets and will lay down in stable duplexes (Carr and Moore, 2012). Agarose gel electrophoresis is employed for size parting of the PCR output.…”