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Highly accurate sigmoidal fitting of real-time PCR data by introducing a parameter for asymmetry
BACKGROUND: Fitting four-parameter sigmoidal models is one of the methods established in the analysis of quantitative real-time PCR (qPCR) data. We had observed that these models are not optimal in the fitting outcome due to the inherent constraint of symmetry around the point of inflection. Thus, w...
Autores principales: | , , |
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Formato: | Texto |
Lenguaje: | English |
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BioMed Central
2008
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Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2386824/ https://www.ncbi.nlm.nih.gov/pubmed/18445269 http://dx.doi.org/10.1186/1471-2105-9-221 |
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author | Spiess, Andrej-Nikolai Feig, Caroline Ritz, Christian |
author_facet | Spiess, Andrej-Nikolai Feig, Caroline Ritz, Christian |
author_sort | Spiess, Andrej-Nikolai |
collection | PubMed |
description | BACKGROUND: Fitting four-parameter sigmoidal models is one of the methods established in the analysis of quantitative real-time PCR (qPCR) data. We had observed that these models are not optimal in the fitting outcome due to the inherent constraint of symmetry around the point of inflection. Thus, we found it necessary to employ a mathematical algorithm that circumvents this problem and which utilizes an additional parameter for accommodating asymmetrical structures in sigmoidal qPCR data. RESULTS: The four-parameter models were compared to their five-parameter counterparts by means of nested F-tests based on the residual variance, thus acquiring a statistical measure for higher performance. For nearly all qPCR data we examined, five-parameter models resulted in a significantly better fit. Furthermore, accuracy and precision for the estimation of efficiencies and calculation of quantitative ratios were assessed with four independent dilution datasets and compared to the most commonly used quantification methods. It could be shown that the five-parameter model exhibits an accuracy and precision more similar to the non-sigmoidal quantification methods. CONCLUSION: The five-parameter sigmoidal models outperform the established four-parameter model with high statistical significance. The estimation of essential PCR parameters such as PCR efficiency, threshold cycles and initial template fluorescence is more robust and has smaller variance. The model is implemented in the qpcR package for the freely available statistical R environment. The package can be downloaded from the author's homepage. |
format | Text |
id | pubmed-2386824 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2008 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-23868242008-05-19 Highly accurate sigmoidal fitting of real-time PCR data by introducing a parameter for asymmetry Spiess, Andrej-Nikolai Feig, Caroline Ritz, Christian BMC Bioinformatics Methodology Article BACKGROUND: Fitting four-parameter sigmoidal models is one of the methods established in the analysis of quantitative real-time PCR (qPCR) data. We had observed that these models are not optimal in the fitting outcome due to the inherent constraint of symmetry around the point of inflection. Thus, we found it necessary to employ a mathematical algorithm that circumvents this problem and which utilizes an additional parameter for accommodating asymmetrical structures in sigmoidal qPCR data. RESULTS: The four-parameter models were compared to their five-parameter counterparts by means of nested F-tests based on the residual variance, thus acquiring a statistical measure for higher performance. For nearly all qPCR data we examined, five-parameter models resulted in a significantly better fit. Furthermore, accuracy and precision for the estimation of efficiencies and calculation of quantitative ratios were assessed with four independent dilution datasets and compared to the most commonly used quantification methods. It could be shown that the five-parameter model exhibits an accuracy and precision more similar to the non-sigmoidal quantification methods. CONCLUSION: The five-parameter sigmoidal models outperform the established four-parameter model with high statistical significance. The estimation of essential PCR parameters such as PCR efficiency, threshold cycles and initial template fluorescence is more robust and has smaller variance. The model is implemented in the qpcR package for the freely available statistical R environment. The package can be downloaded from the author's homepage. BioMed Central 2008-04-29 /pmc/articles/PMC2386824/ /pubmed/18445269 http://dx.doi.org/10.1186/1471-2105-9-221 Text en Copyright © 2008 Spiess et al; licensee BioMed Central Ltd. http://creativecommons.org/licenses/by/2.0 This is an Open Access article distributed under the terms of the Creative Commons Attribution License ( (http://creativecommons.org/licenses/by/2.0) ), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Methodology Article Spiess, Andrej-Nikolai Feig, Caroline Ritz, Christian Highly accurate sigmoidal fitting of real-time PCR data by introducing a parameter for asymmetry |
title | Highly accurate sigmoidal fitting of real-time PCR data by introducing a parameter for asymmetry |
title_full | Highly accurate sigmoidal fitting of real-time PCR data by introducing a parameter for asymmetry |
title_fullStr | Highly accurate sigmoidal fitting of real-time PCR data by introducing a parameter for asymmetry |
title_full_unstemmed | Highly accurate sigmoidal fitting of real-time PCR data by introducing a parameter for asymmetry |
title_short | Highly accurate sigmoidal fitting of real-time PCR data by introducing a parameter for asymmetry |
title_sort | highly accurate sigmoidal fitting of real-time pcr data by introducing a parameter for asymmetry |
topic | Methodology Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2386824/ https://www.ncbi.nlm.nih.gov/pubmed/18445269 http://dx.doi.org/10.1186/1471-2105-9-221 |
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