Cited by 170Molecular Biology Techniques and ApplicationsStochastic processes and statistical mechanicsGene Regulatory Network Analysis

Theoretical uncertainty of measurements using quantitative polymerase chain reaction

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Peccoud, J., Jacob, C.·1996·Biophysical Journal

Abstract

Current quantitative polymerase chain reaction (PCR) protocols are only indicative of the quantity of a target sequence relative to a standard, because no means of estimating the amplification rate is yet available. The variability of PCR performed on isolated cells has already been reported by several authors, but it could not be extensively studied, because of lack of a system for doing kinetic data acquisition and of statistical methods suitable for analyzing this type of data. We used the branching process theory to simulate and analyze quantitative kinetic PCR data. We computed the probability distribution of the offspring of a single molecule. We demonstrated that the rate of amplication has a severe influence on the shape of this distribution. For high values of the amplification rate, the distribution has several maxima of probability. A single amplification trajectory is used to estimate the initial copy number of the target sequence as well as its confidence interval, provided that the amplification is done over more than 20 cycles. The consequence of possible molecular fluctuations in the early stage of amplification is that small copy numbers result in relatively larger intervals than large initial copy numbers. The confidence interval amplitude is the theoretical uncertainty of measurements using quantitative PCR. We expect these results to be applicable to the data produced by the next generation of thermocyclers for quantitative applications.

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Crossref · 10.1016/s0006-3495(96)79205-6

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  • PCR is an exponential process, so small random variations early on in amplification can have a large impact on distribution.

    “PCR is an exponential process, so small random variations early on in amplification can have a large impact on distribution18–24.”

    From Quantifying Molecular Bias in DNA Data Storage (2019) · cites this paper as [23]

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Authors
Peccoud, J., & Jacob, C.
Affiliations
Translational Innovation in Medicine and Complexity (FR)
Venue
Biophysical Journal
Publisher
Elsevier BV
Published
1996-07
Volume
71
Issue
1
Pages
101-108
ISSN
0006-3495 (ISSN-L)
OpenAlex
W2019766856
Cited by
170
References
23
Citations by year
2026: 4 · 2025: 1 · 2024: 2 · 2023: 5 · 2022: 1 · 2021: 3 · 2020: 2 · 2019: 8 · 2018: 3 · 2017: 2 · 2016: 2 · 2015: 11 · 2014: 2 · 2013: 6 · 2012: 8
FWCI
1.52
Type
journal article
Language
en
Open access
Locations
  • Biophysical Journal (publishedVersion)
  • PubMed Central (publishedVersion)
  • PubMed (publishedVersion)
  • HAL (submittedVersion)
Topics
  • Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Molecular Biology Techniques and Applications
  • Physical Sciences › Mathematics › Mathematical Physics › Stochastic processes and statistical mechanics
  • Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Gene Regulatory Network Analysis
Keywords
real-time PCR, measurement uncertainty, amplification rate, confidence intervals, molecular fluctuations, thermocycler
MeSH terms
Biometry, Biophysics, Computer Simulation, Data Interpretation, Statistical, Models, Theoretical, Monte Carlo Method, Stochastic Processes, Polymerase Chain Reaction, Biophysical Phenomena

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