Experimental validation of novel and conventional approaches to quantitative real-time PCR data analysis.

By S. Peirson, J. N. Butler, R. Foster. Nucleic Acids Research, 2003

897 citations recorded by the source corpus.

View Paper: https://www.semanticscholar.org/paper/f0c17fd829d0c3c5a540f4f578ce45f4170ffab0

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Citations in the corpus

qpcR: an R package for sigmoidal model selection in quantitative real-time polymerase chain reaction analysis (2008, methodology): “…slope of a calibration curve (Pfaffl et al ., 2001) 2) based directly on the threshold values (Pfaffl, 2001) 3) by mid-value-point regression (Peirson et al ., 2003) 4) with the window-of-linearity method (Ramakers et al ., 2003) Nonlinear methods: 1) fitting four-parameter sigmoidal models…”
Anatomical profiling of G protein-coupled receptor expression (2008, neutral): “PCR efficiencies were calculated as described (Peirson et al., 2003).”
Amplification efficiency: linking baseline and bias in the analysis of quantitative PCR data (2009, methodology): “Data analysis methods that are based on the application of linear regression algorithms (10,15) require baseline subtraction before the logarithmic transformation because of the fit of the logarithm of Equation 1 to a subset of data in the exponential phase.”
A review of the biology and genetics of sea lice (2006, methodology): “When the DART method (Peirson et al., 2003) was employed, the LsTryp1 transcript levels decreased by a factor of two or three when the lice were starved and remained low even on access to food.”
Quantitative real-time RT-PCR data analysis: current concepts and the novel “gene expression’s CT difference” formula (2006, methodology): “Given identical initial copy numbers (R0), the PCR efficiency E defines the CT value and the resulting gene expression ratios, as these are calculated on the basis of the CT values [8].”
Statistical analysis of real-time PCR data (2006, positive): “We considered the data in the third scenario as unacceptable as many others have reported [10,18].”