title: Data Normalization Strategies for MicroRNA Quantification.
abstract: BACKGROUND
  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.
  
  
  BACKGROUND
  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.
  
  
  CONCLUSIONS
  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.
authors.affiliation: Department of Tumour Biology, Center of Experimental Medicine, University Cancer Center Hamburg, University Medical Center Hamburg-Eppendorf, Hamburg, Germany;
authors.forename: Heidi
authors.initials: H
authors.lastname: Schwarzenbach
authors.affiliation: Department of Experimental Therapeutics and The Center for RNA Interference and Non-Coding RNAs, The University of Texas MD Anderson Cancer Center, Houston, TX; Instituto de Investigação em Saúde, Universidade do Porto, Porto, Portugal; INEB, Institute of Biomedical Engineering, Universidade do Porto, Porto, Portugal.
authors.forename: Andreia Machado
authors.initials: AM
authors.lastname: da Silva
authors.affiliation: Department of Experimental Therapeutics and The Center for RNA Interference and Non-Coding RNAs, The University of Texas MD Anderson Cancer Center, Houston, TX;
authors.forename: George
authors.initials: G
authors.lastname: Calin
authors.affiliation: Department of Tumour Biology, Center of Experimental Medicine, University Cancer Center Hamburg, University Medical Center Hamburg-Eppendorf, Hamburg, Germany; pantel@uke.de.
authors.forename: Klaus
authors.initials: K
authors.lastname: Pantel
mesh_terms: D000818:Animals; D020869:Gene Expression Profiling / Q000379:methods* / Q000592:standards; D006801:Humans; D035683:MicroRNAs / Q000235:genetics*; D020411:Oligonucleotide Array Sequence Analysis / Q000379:methods / Q000592:standards; D060888:Real-Time Polymerase Chain Reaction / Q000379:methods* / Q000592:standards; D012015:Reference Standards; D015203:Reproducibility of Results; D057188:Workflow
chemical_list: D035683:MicroRNAs