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NORMA-Gene: A simple and robust method for qPCR normalization based on target gene data

BACKGROUND: Normalization of target gene expression, measured by real-time quantitative PCR (qPCR), is a requirement for reducing experimental bias and thereby improving data quality. The currently used normalization approach is based on using one or more reference genes. Yet, this approach extends...

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Autores principales: Heckmann, Lars-Henrik, Sørensen, Peter B, Krogh, Paul Henning, Sørensen, Jesper G
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2011
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3223928/
https://www.ncbi.nlm.nih.gov/pubmed/21693017
http://dx.doi.org/10.1186/1471-2105-12-250
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author Heckmann, Lars-Henrik
Sørensen, Peter B
Krogh, Paul Henning
Sørensen, Jesper G
author_facet Heckmann, Lars-Henrik
Sørensen, Peter B
Krogh, Paul Henning
Sørensen, Jesper G
author_sort Heckmann, Lars-Henrik
collection PubMed
description BACKGROUND: Normalization of target gene expression, measured by real-time quantitative PCR (qPCR), is a requirement for reducing experimental bias and thereby improving data quality. The currently used normalization approach is based on using one or more reference genes. Yet, this approach extends the experimental work load and suffers from assumptions that may be difficult to meet and to validate. RESULTS: We developed a data driven normalization algorithm (NORMA-Gene). An analysis of the performance of NORMA-Gene compared to reference gene normalization on artificially generated data-sets showed that the NORMA-Gene normalization yielded more precise results under a large range of parameters tested. Furthermore, when tested on three very different real qPCR data-sets NORMA-Gene was shown to be best at reducing variance due to experimental bias in all three data-sets compared to normalization based on the use of reference gene(s). CONCLUSIONS: Here we present the NORMA-Gene algorithm that is applicable to all biological and biomedical qPCR studies, especially those that are based on a limited number of assayed genes. The method is based on a data-driven normalization and is useful for as little as five target genes comprising the data-set. NORMA-Gene does not require the identification and validation of reference genes allowing researchers to focus their efforts on studying target genes of biological relevance.
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spelling pubmed-32239282011-11-26 NORMA-Gene: A simple and robust method for qPCR normalization based on target gene data Heckmann, Lars-Henrik Sørensen, Peter B Krogh, Paul Henning Sørensen, Jesper G BMC Bioinformatics Research Article BACKGROUND: Normalization of target gene expression, measured by real-time quantitative PCR (qPCR), is a requirement for reducing experimental bias and thereby improving data quality. The currently used normalization approach is based on using one or more reference genes. Yet, this approach extends the experimental work load and suffers from assumptions that may be difficult to meet and to validate. RESULTS: We developed a data driven normalization algorithm (NORMA-Gene). An analysis of the performance of NORMA-Gene compared to reference gene normalization on artificially generated data-sets showed that the NORMA-Gene normalization yielded more precise results under a large range of parameters tested. Furthermore, when tested on three very different real qPCR data-sets NORMA-Gene was shown to be best at reducing variance due to experimental bias in all three data-sets compared to normalization based on the use of reference gene(s). CONCLUSIONS: Here we present the NORMA-Gene algorithm that is applicable to all biological and biomedical qPCR studies, especially those that are based on a limited number of assayed genes. The method is based on a data-driven normalization and is useful for as little as five target genes comprising the data-set. NORMA-Gene does not require the identification and validation of reference genes allowing researchers to focus their efforts on studying target genes of biological relevance. BioMed Central 2011-06-21 /pmc/articles/PMC3223928/ /pubmed/21693017 http://dx.doi.org/10.1186/1471-2105-12-250 Text en Copyright ©2011 Heckmann 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 Research Article
Heckmann, Lars-Henrik
Sørensen, Peter B
Krogh, Paul Henning
Sørensen, Jesper G
NORMA-Gene: A simple and robust method for qPCR normalization based on target gene data
title NORMA-Gene: A simple and robust method for qPCR normalization based on target gene data
title_full NORMA-Gene: A simple and robust method for qPCR normalization based on target gene data
title_fullStr NORMA-Gene: A simple and robust method for qPCR normalization based on target gene data
title_full_unstemmed NORMA-Gene: A simple and robust method for qPCR normalization based on target gene data
title_short NORMA-Gene: A simple and robust method for qPCR normalization based on target gene data
title_sort norma-gene: a simple and robust method for qpcr normalization based on target gene data
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3223928/
https://www.ncbi.nlm.nih.gov/pubmed/21693017
http://dx.doi.org/10.1186/1471-2105-12-250
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