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Bioinformatics Advance Access originally published online on August 18, 2005
Bioinformatics 2005 21(20):3880-3886; doi:10.1093/bioinformatics/bti636
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© The Author 2005. Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions{at}oxfordjournals.org

A statistical model providing comprehensive predictions for the mRNA differential display

David Meintrup 1 and Ellen Reisinger 2,*

1Institut EIT 1, Universitaet der Bundeswehr Muenchen 85577 Neubiberg, Germany
2Department of Physiology II, Universitaet Freiburg 79104 Freiburg, Germany

*To whom correspondence should be addressed.

Motivation: Differential display (DD) or arbitrarily primed fingerprinting serves to identify differentially expressed genes, but these techniques cannot determine how many of the theoretically available genes have been uncovered. Previous mathematical models are unsatisfying as they are not suitable to analyze experimental data.

Results: In the present study, we provide a statistical model based on the redundancy of cDNA fragments amplified during DD experiments. This model is applicable to any DD and predicts (1) the total number of genes expressed in a sample cell type or tissue, (2) the number of differentially expressed genes, (3) the coverage obtained with any given number of primer combinations. In a DD experiment comparing two developmental stages of the post natal rat inner ear, we estimated the total number of differentially expressed genes accessible by DD to be 445, and the number of primer combinations required to uncover 90% of these to be 127.

Availability: The algorithms were implemented in MatlabTM (The Mathworks, Inc., Natick, MA) environment and are available at www.physiologie.uni-freiburg.de/download.html

Contact: ellen.reisinger{at}physiologie.uni-freiburg.de

Received on June 30, 2005; revised on August 9, 2005; accepted on August 16, 2005

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