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Quantitative polymerase chain reaction analysis by deconvolution of internal standard.


ABSTRACT:

Background

Quantitative Polymerase Chain Reaction (qPCR) is a collection of methods for estimating the number of copies of a specific DNA template in a sample, but one that is not universally accepted because it can lead to highly inaccurate (albeit precise) results. The fundamental problem is that qPCR methods use mathematical models that explicitly or implicitly apply an estimate of amplification efficiency, the error of which is compounded in the analysis to unacceptable levels.

Results

We present a new method of qPCR analysis that is efficiency-independent and yields accurate and precise results in controlled experiments. The method depends on a computer-assisted deconvolution that finds the point of concordant amplification behavior between the "unknown" template and an admixed amplicon standard. We apply the method to demonstrate dexamethasone-induced changes in gene expression in lymphoblastic leukemia cell lines.

Conclusions

This method of qPCR analysis does not use any explicit or implicit measure of efficiency, and may therefore be immune to problems inherent in other qPCR approaches. It yields an estimate of absolute initial copy number of template, and controlled tests show it generates accurate results.

SUBMITTER: Hirakawa Y 

PROVIDER: S-EPMC2877679 | biostudies-literature | 2010 Apr

REPOSITORIES: biostudies-literature

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Quantitative polymerase chain reaction analysis by deconvolution of internal standard.

Hirakawa Yasuko Y   Medh Rheem D RD   Metzenberg Stan S  

BMC molecular biology 20100429


<h4>Background</h4>Quantitative Polymerase Chain Reaction (qPCR) is a collection of methods for estimating the number of copies of a specific DNA template in a sample, but one that is not universally accepted because it can lead to highly inaccurate (albeit precise) results. The fundamental problem is that qPCR methods use mathematical models that explicitly or implicitly apply an estimate of amplification efficiency, the error of which is compounded in the analysis to unacceptable levels.<h4>Re  ...[more]

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