A common base method for analysis of qPCR data and the application of simple blocking in qPCR experiments

BMC Bioinformatics

Methodology Article

Michael T. Ganger¹  Sarah J. Ewing¹  Geoffrey D. Dietz² 

[1] Department of Biology, Gannon University, 109 University Square, 16541, Erie, PA, USA;Department of Mathematics, Gannon University, 109 University Square, 16541, Erie, PA, USA;

关键词: Analysis of variance (ANOVA);    Blocking;    Confidence intervals;    Paired and unpaired tests;    Statistics;    qPCR analysis;   

DOI  :  10.1186/s12859-017-1949-5

 received in 2016-12-20, accepted in 2017-11-22,  发布年份 2017

来源: Springer

【 摘 要 】

BackgroundqPCR has established itself as the technique of choice for the quantification of gene expression. Procedures for conducting qPCR have received significant attention; however, more rigorous approaches to the statistical analysis of qPCR data are needed.ResultsHere we develop a mathematical model, termed the Common Base Method, for analysis of qPCR data based on threshold cycle values (Cq) and efficiencies of reactions (E). The Common Base Method keeps all calculations in the logscale as long as possible by working with log10(E) ∙ Cq, which we call the efficiency-weighted Cq value; subsequent statistical analyses are then applied in the logscale. We show how efficiency-weighted Cq values may be analyzed using a simple paired or unpaired experimental design and develop blocking methods to help reduce unexplained variation.ConclusionsThe Common Base Method has several advantages. It allows for the incorporation of well-specific efficiencies and multiple reference genes. The method does not necessitate the pairing of samples that must be performed using traditional analysis methods in order to calculate relative expression ratios. Our method is also simple enough to be implemented in any spreadsheet or statistical software without additional scripts or proprietary components.

【 授权许可】

CC BY   
© The Author(s). 2017

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