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Cited by 843

The DOI matches its Crossref record; 2 of the 2 references it cites were found in a registry or an index.

Experimental validation of novel and conventional approaches to quantitative real-time PCR data analysis

Open access
Peirson, S. N.·2003·Nucleic Acids Research

Abstract

Real-time PCR is being used increasingly as the method of choice for mRNA quantification, allowing rapid analysis of gene expression from low quantities of starting template. Despite a wide range of approaches, the same principles underlie all data analysis, with standard approaches broadly classified as either absolute or relative. In this study we use a variety of absolute and relative approaches of data analysis to investigate nocturnal c-fos expression in wild-type and retinally degenerate mice. In addition, we apply a simple algorithm to calculate the amplification efficiency of every sample from its amplification profile. We confirm that nocturnal c-fos expression in the rodent eye originates from the photoreceptor layer, with around a 5-fold reduction in nocturnal c-fos expression in mice lacking rods and cones. Furthermore, we illustrate that differences in the results obtained from absolute and relative approaches are underpinned by differences in the calculated PCR efficiency. By calculating the amplification efficiency from the samples under analysis, comparable results may be obtained without the need for standard curves. We have automated this method to provide a means of streamlining the real-time PCR process, enabling analysis of experimental samples based upon their own reaction kinetics rather than those of artificial standards.

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Metadata

Authors
Peirson, S. N.
Venue
Nucleic Acids Research
Published
2003-07-15
Volume
31
Issue
14
Pages
73e-73
ISSN
  • 0305-1048 (ISSN-L)
  • 1362-4962
OpenAlex
W2123247959
Cited by
843
References
2
FWCI
12.33
Type
journal article
Language
en
Open access
bronze

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Peirson, S. N. (2003). Experimental validation of novel and conventional approaches to quantitative real-time PCR data analysis. Nucleic Acids Research. https://doi.org/10.1093/nar/gng073

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