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Bioinformatics Advance Access published online on August 18, 2005
Bioinformatics, 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@oupjournals.org
Received June 30, 2005
Revised August 9, 2005
Accepted August 16, 2005

Article

A statistical model providing comprehensive predictions for the mRNA differential display

D. Meintrup 1 and E. Reisinger 2*

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

* To whom correspondence should be addressed.
E. Reisinger, E-mail: ellen.reisinger{at}physiologie.uni-freiburg.de


  Abstract

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: Here we present a statistical model basing on the redundancy of cDNA fragments amplified during DD experiments. This model is applicable to any DD and predicts (i) the total number of genes expressed in a sample cell type or tissue, (ii) the number of differentially expressed genes, (iii) the coverage obtained with any given number of primer combinations. In a DD experiment comparing two developmental stages of the postnatal 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.

Supplementary Information: Autoradiography of the DD and Mathematical Appendix are available online at the journal's web site.


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