Data Normalization Strategies for MicroRNA Quantification

Different technologies, such as quantitative real-time PCR or microarrays, have been developed to measure microRNA (miRNA) expression levels. Quantification of miRNA transcripts implicates data normalization using endogenous and exogenous reference genes for data correction. However, there is no con...

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Bibliographic Details
Published in:Clinical chemistry (Baltimore, Md.) Vol. 61; no. 11; pp. 1333 - 1342
Main Authors: Schwarzenbach, Heidi, da Silva, Andreia Machado, Calin, George, Pantel, Klaus
Format: Journal Article
Language:English
Published: England Oxford University Press 01.11.2015
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ISSN:0009-9147, 1530-8561
Online Access:Get full text
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Summary:Different technologies, such as quantitative real-time PCR or microarrays, have been developed to measure microRNA (miRNA) expression levels. Quantification of miRNA transcripts implicates data normalization using endogenous and exogenous reference genes for data correction. However, there is no consensus about an optimal normalization strategy. The choice of a reference gene remains problematic and can have a serious impact on the actual available transcript levels and, consequently, on the biological interpretation of data. In this review article we discuss the reliability of the use of small RNAs, commonly reported in the literature as miRNA expression normalizers, and compare different strategies used for data normalization. A workflow strategy is proposed for normalization of miRNA expression data in an attempt to provide a basis for the establishment of a global standard procedure that will allow comparison across studies.
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ISSN:0009-9147
1530-8561
DOI:10.1373/clinchem.2015.239459