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System-specific periodicity in quantitative real-time polymerase chain reaction data questions threshold-based quantitation
Real-time quantitative polymerase chain reaction (qPCR) data are found to display periodic patterns in the fluorescence intensity as a function of sample number for fixed cycle number. This behavior is seen for technical replicate datasets recorded on several different commercial instruments; it occ...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group
2016
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5154181/ https://www.ncbi.nlm.nih.gov/pubmed/27958340 http://dx.doi.org/10.1038/srep38951 |
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author | Spiess, Andrej-Nikolai Rödiger, Stefan Burdukiewicz, Michał Volksdorf, Thomas Tellinghuisen, Joel |
author_facet | Spiess, Andrej-Nikolai Rödiger, Stefan Burdukiewicz, Michał Volksdorf, Thomas Tellinghuisen, Joel |
author_sort | Spiess, Andrej-Nikolai |
collection | PubMed |
description | Real-time quantitative polymerase chain reaction (qPCR) data are found to display periodic patterns in the fluorescence intensity as a function of sample number for fixed cycle number. This behavior is seen for technical replicate datasets recorded on several different commercial instruments; it occurs in the baseline region and typically increases with increasing cycle number in the growth and plateau regions. Autocorrelation analysis reveals periodicities of 12 for 96-well systems and 24 for a 384-well system, indicating a correlation with block architecture. Passive dye experiments show that the effect may be from optical detector bias. Importantly, the signal periodicity manifests as periodicity in quantification cycle (C(q)) values when these are estimated by the widely applied fixed threshold approach, but not when scale-insensitive markers like first- and second-derivative maxima are used. Accordingly, any scale variability in the growth curves will lead to bias in constant-threshold-based C(q)s, making it mandatory that workers should either use scale-insensitive C(q)s or normalize their growth curves to constant amplitude before applying the constant threshold method. |
format | Online Article Text |
id | pubmed-5154181 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2016 |
publisher | Nature Publishing Group |
record_format | MEDLINE/PubMed |
spelling | pubmed-51541812016-12-28 System-specific periodicity in quantitative real-time polymerase chain reaction data questions threshold-based quantitation Spiess, Andrej-Nikolai Rödiger, Stefan Burdukiewicz, Michał Volksdorf, Thomas Tellinghuisen, Joel Sci Rep Article Real-time quantitative polymerase chain reaction (qPCR) data are found to display periodic patterns in the fluorescence intensity as a function of sample number for fixed cycle number. This behavior is seen for technical replicate datasets recorded on several different commercial instruments; it occurs in the baseline region and typically increases with increasing cycle number in the growth and plateau regions. Autocorrelation analysis reveals periodicities of 12 for 96-well systems and 24 for a 384-well system, indicating a correlation with block architecture. Passive dye experiments show that the effect may be from optical detector bias. Importantly, the signal periodicity manifests as periodicity in quantification cycle (C(q)) values when these are estimated by the widely applied fixed threshold approach, but not when scale-insensitive markers like first- and second-derivative maxima are used. Accordingly, any scale variability in the growth curves will lead to bias in constant-threshold-based C(q)s, making it mandatory that workers should either use scale-insensitive C(q)s or normalize their growth curves to constant amplitude before applying the constant threshold method. Nature Publishing Group 2016-12-13 /pmc/articles/PMC5154181/ /pubmed/27958340 http://dx.doi.org/10.1038/srep38951 Text en Copyright © 2016, The Author(s) http://creativecommons.org/licenses/by/4.0/ This work is licensed under a Creative Commons Attribution 4.0 International License. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in the credit line; if the material is not included under the Creative Commons license, users will need to obtain permission from the license holder to reproduce the material. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/ |
spellingShingle | Article Spiess, Andrej-Nikolai Rödiger, Stefan Burdukiewicz, Michał Volksdorf, Thomas Tellinghuisen, Joel System-specific periodicity in quantitative real-time polymerase chain reaction data questions threshold-based quantitation |
title | System-specific periodicity in quantitative real-time polymerase chain reaction data questions threshold-based quantitation |
title_full | System-specific periodicity in quantitative real-time polymerase chain reaction data questions threshold-based quantitation |
title_fullStr | System-specific periodicity in quantitative real-time polymerase chain reaction data questions threshold-based quantitation |
title_full_unstemmed | System-specific periodicity in quantitative real-time polymerase chain reaction data questions threshold-based quantitation |
title_short | System-specific periodicity in quantitative real-time polymerase chain reaction data questions threshold-based quantitation |
title_sort | system-specific periodicity in quantitative real-time polymerase chain reaction data questions threshold-based quantitation |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5154181/ https://www.ncbi.nlm.nih.gov/pubmed/27958340 http://dx.doi.org/10.1038/srep38951 |
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