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Volume 11 (2011), Pages 1383-1393
Review Article

Linear Methods for Analysis and Quality Control of Relative Expression Ratios from Quantitative Real-Time Polymerase Chain Reaction Experiments

1Department of Biology, Auburn University, Montgomery, Alabama, USA
2Department of Statistics, University of Kentucky, Lexington, USA

Received 3 March 2011; Revised 8 June 2011; Accepted 11 June 2011

Academic Editor: Eric Blalock

Copyright © 2011 Robert B. Page and Arnold J. Stromberg.


Relative expression quantitative real-time polymerase chain reaction (RT-qPCR) experiments are a common means of estimating transcript abundances across biological groups and experimental treatments. One of the most frequently used expression measures that results from such experiments is the relative expression ratio (RE), which describes expression in experimental samples (i.e., RNA isolated from organisms, tissues, and/or cells that were exposed to one or more experimental or nonbaseline condition) in terms of fold change relative to calibrator samples (i.e., RNA isolated from organisms, tissues, and/or cells that were exposed to a control or baseline condition). Over the past decade, several models of RE have been proposed, and it is now clear that endogenous reference gene stability and amplification efficiency must be assessed in order to ensure that estimates of RE are valid. In this review, we summarize key issues associated with estimating RE from cycle threshold data. In addition, we describe several methods based on linear modeling that enable researchers to estimate model parameters and conduct quality control procedures that assess whether model assumptions have been violated.