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The choice of reference gene affects statistical efficiency in quantitative PCR data analysis.


ABSTRACT: Quantitative polymerase chain reaction (qPCR), a highly sensitive method of measuring gene expression, is widely used in biomedical research. To produce reliable results, it is essential to use stably expressed reference genes (RGs) for data normalization so that sample-to-sample variation can be controlled. In this study, we examine the effect of different RGs on statistical efficiency by analyzing a qPCR data set that contains 12 target genes and 3 RGs. Our results show that choosing the most stably expressed RG for data normalization does not guarantee reduced variance or improved statistical efficiency. We also provide a formula for determining when data normalization will improve statistical efficiency and hence increase the power of statistical tests in data analysis.

SUBMITTER: Guo Y 

PROVIDER: S-EPMC4102495 | biostudies-literature | 2013 Oct

REPOSITORIES: biostudies-literature

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The choice of reference gene affects statistical efficiency in quantitative PCR data analysis.

Guo Yi Y   Pennell Michael L ML   Pearl Dennis K DK   Knobloch Thomas J TJ   Fernandez Soledad S   Weghorst Christopher M CM  

BioTechniques 20131001 4


Quantitative polymerase chain reaction (qPCR), a highly sensitive method of measuring gene expression, is widely used in biomedical research. To produce reliable results, it is essential to use stably expressed reference genes (RGs) for data normalization so that sample-to-sample variation can be controlled. In this study, we examine the effect of different RGs on statistical efficiency by analyzing a qPCR data set that contains 12 target genes and 3 RGs. Our results show that choosing the most  ...[more]

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