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An improvement of the 2ˆ(-delta delta CT) method for quantitative real-time polymerase chain reaction data analysis.

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TLDR
The improved method, the individual efficiency corrected calculation, produces more accurate estimates inrelative gene expression than the 2-ΔΔCT method and is thus a better way to calculate relative gene expression.
Abstract
Background The 2-ΔΔCT method has been extensively used as a relative quantification strategy for quantitative real-time polymerase chain reaction (qPCR) data analysis. This method is a convenient way to calculate relative gene expression levels between different samples in that it directly uses the threshold cycles (CTs) generated by the qPCR system for calculation. However, this approach relies heavily on an invalid assumption of 100% PCR amplification efficiency across all samples. In addition, the 2-ΔΔCT method is applied to data with automatic removal of background fluorescence by the qPCR software. Since the background fluorescence is unknown, subtracting an inaccurate background can lead to distortion of the results. To address these problems, we present an improved method, the individual efficiency corrected calculation.

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References
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Journal ArticleDOI

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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Analyzing real-time PCR data by the comparative C(T) method.

TL;DR: This protocol provides an overview of the comparative CT method for quantitative gene expression studies and various examples to present quantitative gene Expression data using this method.
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Determination of stable housekeeping genes, differentially regulated target genes and sample integrity: BestKeeper--Excel-based tool using pair-wise correlations.

TL;DR: The developed, and herein presented, software called BestKeeper determines the best suited standards, out of ten candidates, and combines them into an index, which can be compared with further target genes to decide, whether they are differentially expressed under an applied treatment.
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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.
Journal ArticleDOI

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

TL;DR: This article showed 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.
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