Abstract
Digital PCR, a state-of-the-art nucleic acid quantification technique, works by spreading the target material across a large number of partitions. The average number of molecules per partition is estimated using Poisson statistics, and then converted into concentration by dividing by partition volume. In this standard approach, identical partition sizing is assumed. Violations of this assumption result in underestimation of target quantity, when using Poisson modeling, especially at higher concentrations. The Poisson-Plus Model accommodates for this underestimation, if statistics of the volume variation are well characterized. The volume variation was measured on the chip array based QuantStudio 3D Digital PCR System using the ROX fluorescence level as a proxy for effective load volume per through-hole. Monte Carlo simulations demonstrate the efficacy of the proposed correction. Empirical measurement of model parameters characterizing the effective load volume on QuantStudio 3D Digital PCR chips is presented. The model was used to analyze digital PCR experiments and showed improved accuracy in quantification. At the higher concentrations, the modeling must take effective fill volume variation into account to produce accurate estimates. The extent of the difference from the standard to the new modeling is positively correlated to the extent of fill volume variation in the effective load of your reactions.
Highlights
Digital PCR is a state-of-the-art technique for measuring nucleic acid concentrations with high precision and accuracy
A normal distribution of partition sizes is assumed with the standard deviation taken as a percentage of the mean partition size
Monte Carlo simulations were run to demonstrate the remedial effects of quantification using alternate modeling that accounts for non-uniform partition size in Poisson processes
Summary
Digital PCR is a state-of-the-art technique for measuring nucleic acid concentrations with high precision and accuracy. The estimate is divided by partition volume to obtain a measure of the concentration In this case, for the purposes of computation, an ensemble of identically sized partitions is assumed where the occurrence of a molecule in each partition follows a Poisson process. For the purposes of computation, an ensemble of identically sized partitions is assumed where the occurrence of a molecule in each partition follows a Poisson process This technique is adversely affected, at higher concentration, when partitions are not identically sized. In this simulation, the concentration of the target molecules is kept constant. This paper demonstrates how Poisson modeling can be extended to better estimate concentration when effective loads are not identically distributed. Characterized, adoption of the model proposed in this paper will enable precise measurements of target molecules despite load volume dissimilarities
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