Real-time PCR is becoming the method of choice for precise quanti®cation of minute amounts of nucleic acids. For proper comparison of samples, almost all quanti®cation methods assume similar PCR ef®ciencies in the exponential phase of the reaction. However, inhibition of PCR is common when working with biological samples and may invalidate the assumed similarity of PCR ef®ciencies. Here we present a statistical method, Kinetic Outlier Detection (KOD), to detect samples with dissimilar ef®ciencies. KOD is based on a comparison of PCR ef®ciency, estimated from the ampli®cation curve of a test sample, with the mean PCR ef®ciency of samples in a training set. KOD is demonstrated and validated on samples with the same initial number of template molecules, where PCR is inhibited to various degrees by elevated concentrations of dNTP; and in detection of cDNA samples with an aberrant ratio of two genes. Translating the dissimilarity in ef®ciency to quantity, KOD identi®es outliers that differ by 1.3±1.9-fold in their quantity from normal samples with a P-value of 0.05. This precision is higher than the minimal 2-fold difference in number of DNA molecules that real-time PCR usually aims to detect. Thus, KOD may be a useful tool for outlier detection in real-time PCR
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