Relative Expression Software Tool  =  REST
Today the "relative gene expression approach" is increasingly used in gene expression studies, where the expression of a target gene is standardised by a non-regulated reference-gene or by an index, containing more reference-genes. Several mathematical algorithm have been developed to compute the expression ratio, based on real-time PCR efficiency and the crossing point (Ct or CP) deviation (=> delta CP) of an unknown sample versus a control. But all published equations and available models for the calculation of relative expression ratio allow only for the determination of a single transcription difference between one control and one sample.
Therefore new software tools were established, named REST © (Relative Expression Software Tool), which compare two or more treatments groups or conditions (in REST-MCS), with up to 100 data points in sample or control group (in REST-XL), for multiple reference genes and up to 15 target genes (in REST-384) . The mathematical model used is based on the correction for exact PCR efficiencies and the mean crossing point deviation between sample group(s) and control group(s). Subsequently the expression ratio results of the investigated transcripts are tested for significance by a Pair Wise Fixed Reallocation Randomisation Test © and plotted using standard error (SE) estimation via a complex Taylor algorithm (=> see below).

REST software versions (REST-384, REST-RG and REST-MCS) were established in collaboration with:
  • Y. Vainshtein, EMBL, Gene Expression Unit, M. Hentze Group, Germany;  
  • P. Avery, School of Mathematics and Statistics, University of Newcastle, UK; 
  • G. Horgan, Biomathematics and Statistics Scotland, Rowett Research Institute, Scotland;
  • M. W. Pfaffl, Physiology Weihenstephan, Technical University of Munich, Germany;
Stand-alone software versions  REST-2005  &  REST-2008 were programmed and designed by:
  • M. Herrmann, D. Chiew, B. Speller Corbett Research, Sydney, Australia
  • M. W. Pfaffl, Physiology Weihenstephan, Technical University of Munich, Germany
Stand-alone software versions  REST-2009  was programmed and designed by:   
  • Qiagen, Hilden, Germany => http://www.REST.de.com
  • M. W. Pfaffl, Physiology Weihenstephan, Technical University of Munich, Germany
Many thanks to all co-workers !

New REST software applications are available:

  Relative Expression Software Tool  (REST©) for group wise comparison
and statistical analysis
of relative expression results in real-time PCR.

Michael W. Pfaffl   Graham W. Horgan & Leo Dempfle
Nucleic Acids Research 2002 May 1; 30(9): E36


Real-time reverse transcription followed by polymerase chain reaction (RT-PCR) is the most suitable method for the detection and quantification of mRNA. It offers high sensitivity, good reproducibility, and a wide quantification range. Today relative expression is increasingly used, where the expression of a target gene is standardised by a non regulated reference gene. Several mathematical algorithm have been developed to compute an expression ratio, based on real-time PCR efficiency and the crossing point deviation of an unknown sample versus a control. But all published equations and available models for the calculation of relative expression ratio allow only for the determination of a single transcription difference between one control and one sample. Therefore a new software tool was established, named REST © (Relative Expression Software Tool), which compares two groups, with up to 16 data points in sample and  16 in control group, for reference and up to four target genes. The mathematical model used is based on the PCR efficiencies and the mean crossing point deviation between sample and control group. Subsequently the expression ratio results of the four investigated transcripts are tested for significances by a randomisation test. Herein development and application of REST is explained and the usefulness of relative expression in real-time PCR using REST is discussed.


REST ratio error estimation
using Taylor series
implemented in the REST application software versions  REST 384

Real Time PCR:  A useful new approach?  Statistical Problems?

by Peter Avery,
School of Mathematics and Statistics, University of Newcastle, UK



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