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PLoS One. 2016 May 5;11(5):e0153317. doi: 10.1371/journal.pone.0153317. eCollection 2016.

Measuring Digital PCR Quality: Performance Parameters and Their Optimization.

Author information

1
Molecular Biology and Genomics Unit, European Commission - Joint Research Centre, Institute for Health and Consumer Protection, 21027 Ispra (VA), Italy.

Abstract

Digital PCR is rapidly being adopted in the field of DNA-based food analysis. The direct, absolute quantification it offers makes it an attractive technology for routine analysis of food and feed samples for their composition, possible GMO content, and compliance with labelling requirements. However, assessing the performance of dPCR assays is not yet well established. This article introduces three straightforward parameters based on statistical principles that allow users to evaluate if their assays are robust. In addition, we present post-run evaluation criteria to check if quantification was accurate. Finally, we evaluate the usefulness of Poisson confidence intervals and present an alternative strategy to better capture the variability in the analytical chain.

PMID:
27149415
PMCID:
PMC4858304
DOI:
10.1371/journal.pone.0153317
[Indexed for MEDLINE]
Free PMC Article

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