Advertisement

Statistical Analysis of Quantitative RT-PCR Results

  • Richard Khan-MalekEmail author
  • Ying Wang
Protocol
Part of the Methods in Molecular Biology book series (MIMB, volume 1641)

Abstract

Quantitative real-time reverse transcription polymerase chain reaction (RT-PCR) represents a benchmark technology in the detection and quantification of mRNA. Yet, accurate results cannot be realized without proper statistical analysis of RT-PCR data. Here we examine some of the issues concerning RT-PCR experiments that would benefit from rigorous statistical treatment including normalization, quantification, efficiency estimation, and sample size calculations. Examples are used to illustrate the methods.

Key words

RT-PCR Relative quantification Statistical analysis 

References

  1. 1.
    Walker NJ (2002) Tech.Sight. A technique whose time has come. Science 296:557–579CrossRefPubMedGoogle Scholar
  2. 2.
    Wang Y, Barbacioru C, Hyland F, Xiao W, Hunkapiller KL, Blake J, Chan F, Gonzalez C, Zhang L, Samaha R (2006) Large scale real-time PCR validation on gene expression measurements from two commercial long-oligonucleotide microarrays. BMC Genomics 7:59CrossRefPubMedPubMedCentralGoogle Scholar
  3. 3.
    Wong ML, Medrano JF (2005) Real-time PCR for mRNA quantitation. BioTechniques 39:75–85CrossRefPubMedGoogle Scholar
  4. 4.
    SAS Institute Inc (2004) SAS/STAT® 9.1 user’s guide. SAS Institute Inc, Cary, NCGoogle Scholar
  5. 5.
    Livak KJ, Schmittgen TD (2001) Analysis of relative gene expression data using real-time quantitative PCR and the 2−∆∆CT method. Methods 25:402–408CrossRefPubMedGoogle Scholar
  6. 6.
    Huggett J, Dheda K, Bustin S, Zumla A (2005) Real-time RT-PCR normalisation; strategies and considerations. Genes Immun 6(4):279–284CrossRefPubMedGoogle Scholar
  7. 7.
    Vandesompele J, De Preter K, Pattyn F, Poppe B, Van Roy N, De Paepe A, Speleman F (2002) Accurate normalization of real-time quantitative RT-PCR data by geometric averaging of multiple internal control genes. Genome Biol 3(7):RESEARCH0034CrossRefPubMedPubMedCentralGoogle Scholar
  8. 8.
    Pfaffl MW, Tichopad A, Prgomet C, Neuvians TP (2004) Determination of stable housekeeping genes, differentially regulated target genes and sample integrity: bestKeeper--Excel-based tool using pair-wise correlations. Biotechnol Lett 26:509–515CrossRefPubMedGoogle Scholar
  9. 9.
    Abruzzo LV, Lee KY, Fuller A, Silverman A, Keating MJ, Medeiros LJ, Coombes KR (2005) Validation of oligonucleotide microarray data using microfluidic low-density arrays: a new statistical method to normalize real-time RT-PCR data. BioTechniques 38:785–792CrossRefPubMedGoogle Scholar
  10. 10.
    Andersen CL, Jensen JL, Orntoft TF (2004) Normalization of real-time quantitative reverse transcription-PCR data: a model-based variance estimation approach to identify genes suited for normalization, applied to bladder and colon cancer data sets. Cancer Res 64:5245–5250CrossRefPubMedGoogle Scholar
  11. 11.
    Szabo A, Perou CM, Karaca M, Perreard L, Quackenbush JF, Bernard PS (2004) Statistical modeling for selecting housekeeper genes. Genome Biol 5:R59CrossRefPubMedPubMedCentralGoogle Scholar
  12. 12.
    Dean A, Voss D (1999) Design and analysis of experiments. Springer, New YorkCrossRefGoogle Scholar
  13. 13.
    Mestdagh P, Van Vlierberghe P, De Weer A, Muth D, Westermann F, Speleman F, Vandesompele J (2009) A novel and universal method for microRNA RT-qPCR data normalization. Genome Biol 10:64–74. doi: 10.1186/gb-2009-10-6-r64 CrossRefGoogle Scholar
  14. 14.
    Pfaffl MW (2001) A new mathematical model for relative quantification in real-time RT-PCR. Nucleic Acids Res 29(9):e45CrossRefPubMedPubMedCentralGoogle Scholar
  15. 15.
    Pfaffl MW, Horgan GW, Dempfle L (2002) Relative expression software tool (REST©) for group-wise comparison and statistical analysis of relative expression results in real-time PCR. Nucleic Acids Res 30:e36CrossRefPubMedPubMedCentralGoogle Scholar
  16. 16.
    Fu WJ, Hu J, Spencer T, Carroll R, Wu G (2006) Statistical models in assessing fold change of gene expression in real-time RT-PCR experiments. Comput Biol Chem 30:21–26CrossRefPubMedGoogle Scholar
  17. 17.
    Yuan JS, Reed A, Chen F, Stewart CN (2006) Statistical analysis of real-time PCR data. BMC Bioinf 7:85CrossRefGoogle Scholar
  18. 18.
    Applied Biosystems (2006) Amplification Efficiency of TaqMan® Gene Expression Assays: Application NoteGoogle Scholar
  19. 19.
    Peirson SN, Butler JN, Foster RG (2003) Experimental validation of novel and conventional approaches to quantitative real-time PCR data analysis. Nucleic Acids Res 31:e73CrossRefPubMedPubMedCentralGoogle Scholar
  20. 20.
    Ramakers C, Ruijter JM, Deprez RH, Moorman AF (2003) Assumption-free analysis of quantitative real-time polymerase chain reaction (PCR) data. Neurosci Lett 339(1):62–66CrossRefPubMedGoogle Scholar
  21. 21.
    Tichopad A, Dilger M, Schwarz G, Pfaffl MW (2003) Standardized determination of real-time PCR efficiency from a single reaction set-up. Nucleic Acids Res 31:e122CrossRefPubMedPubMedCentralGoogle Scholar
  22. 22.
    Zhao S, Fernald D (2005) Comprehensive algorithm for quantitative real-time polymerase chain reaction. J Comput Biol 12(8):1047–1064CrossRefPubMedPubMedCentralGoogle Scholar
  23. 23.
    Liu W, Saint D (2002) Validation of a quantitative method for real time PCR kinetics. Biochem Biophys Res Commun 294(2):347–353CrossRefPubMedGoogle Scholar
  24. 24.
    Tichopad A, Dzidic A, Pfaffl MW (2002) Improving quantitative real-time RT-PCR reproducibility by boosting primer-linked amplification efficiency. Biotechnol Lett 24(24):2053–2056CrossRefGoogle Scholar
  25. 25.
    Rutledge RG (2004) Sigmoidal curve-fitting redefines quantitative real-time PCR with the prospective of developing automated high-throughput applications. Nucleic Acids Res 32(22):e178CrossRefPubMedPubMedCentralGoogle Scholar

Copyright information

© Springer Science+Business Media LLC 2017

Authors and Affiliations

  1. 1.Biostatistics and ProgrammingSanofi US, Inc.BridgewaterUSA
  2. 2.Translational Medicine and Early DevelopmentSanofi US, Inc.BridgewaterUSA

Personalised recommendations