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A new mathematical model for relative quantification in real-time RT-PCR
Author(s) -
Michael W. Pfaffl
Publication year - 2001
Publication title -
nucleic acids research
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 9.008
H-Index - 537
eISSN - 1362-4954
pISSN - 0305-1048
DOI - 10.1093/nar/29.9.e45
Subject(s) - biology , real time polymerase chain reaction , computational biology , polymerase chain reaction , complementary dna , biological system , melting curve analysis , reproducibility , sample (material) , nucleic acid , digital polymerase chain reaction , gene expression , gene , genetics , statistics , mathematics , chromatography , chemistry
Use of the real-time polymerase chain reaction (PCR) to amplify cDNA products reverse transcribed from mRNA is on the way to becoming a routine tool in molecular biology to study low abundance gene expression. Real-time PCR is easy to perform, provides the necessary accuracy and produces reli- able as well as rapid quantification results. But accu- rate quantification of nucleic acids requires a reproducible methodology and an adequate mathe- matical model for data analysis. This study enters into the particular topics of the relative quantification in real-time RT-PCR of a target gene transcript in comparison to a reference gene transcript. There- fore, a new mathematical model is presented. The relative expression ratio is calculated only from the real-time PCR efficiencies and the crossing point deviation of an unknown sample versus a control. This model needs no calibration curve. Control levels were included in the model to standardise each reac- tion run with respect to RNA integrity, sample loading and inter-PCR variations. High accuracy and reproducibility (<2.5% variation) were reached in LightCycler PCR using the established mathematical model.

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