Comprehensive Algorithm for Quantitative Real-Time Polymerase Chain Reaction
Sheng Zhao,Russell D. Fernald +1 more
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TLDR
This algorithm provides an objective and noise-resistant method for quantification of qRT-PCR results that is independent of the specific equipment used to perform PCR reactions.Abstract:
Quantitative real-time polymerase chain reactions (qRT-PCR) have become the method of choice for rapid, sensitive, quantitative comparison of RNA transcript abundance. Useful data from this method depend on fitting data to theoretical curves that allow computation of mRNA levels. Calculating accurate mRNA levels requires important parameters such as reaction efficiency and the fractional cycle number at threshold (CT) to be used; however, many algorithms currently in use estimate these important parameters. Here we describe an objective method for quantifying qRT-PCR results using calculations based on the kinetics of individual PCR reactions without the need of the standard curve, independent of any assumptions or subjective judgments which allow direct calculation of efficiency and CT. We use a four-parameter logistic model to fit the raw fluorescence data as a function of PCR cycles to identify the exponential phase of the reaction. Next, we use a three-parameter simple exponent model to fit the exponential phase using an iterative nonlinear regression algorithm. Within the exponential portion of the curve, our technique automatically identifies candidate regression values using the P-value of regression and then uses a weighted average to compute a final efficiency for quantification. For CT determination, we chose the first positive second derivative maximum from the logistic model. This algorithm provides an objective and noise-resistant method for quantification of qRT-PCR results that is independent of the specific equipment used to perform PCR reactions.read more
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References
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Analysis of relative gene expression data using real-time quantitative pcr and the 2(-delta delta c(t)) method
TL;DR: The 2-Delta Delta C(T) method as mentioned in this paper was proposed to analyze the relative changes in gene expression from real-time quantitative PCR experiments, and it has been shown to be useful in the analysis of realtime, quantitative PCR data.
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Jo Vandesompele,Katleen De Preter,Filip Pattyn,Bruce Poppe,Nadine Van Roy,Anne De Paepe,Franki Speleman +6 more
TL;DR: The normalization strategy presented here is a prerequisite for accurate RT-PCR expression profiling, which opens up the possibility of studying the biological relevance of small expression differences.
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Absolute quantification of mRNA using real-time reverse transcription polymerase chain reaction assays.
TL;DR: The technical aspects involved are discussed, conventional and kinetic RT-PCR methods for quantitating gene expression are contrasted, and the usefulness of these assays are illustrated by demonstrating the significantly different levels of transcription between individuals of the housekeeping gene family, glyceraldehyde-3-phosphate-dehydrogenase (GAPDH).
Journal ArticleDOI
Assumption-free analysis of quantitative real-time polymerase chain reaction (PCR) data.
TL;DR: It is shown that the first approach can lead to PCR efficiencies that vary over a 0.2 range, whereas the second approach may be off by 0.26, and proposed linear regression on the Log(fluorescence) per cycle number data as an assumption-free method to calculate starting concentrations of mRNAs and PCRefficiencies for each sample.