title: A statistical model providing comprehensive predictions for the mRNA differential display.
abstract: BACKGROUND
  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.
  
  
  BACKGROUND
  The algorithms were implemented in Matlab (The Mathworks, Inc., Natick, MA) environment and are available at www.physiologie.uni-freiburg.de/download.html
  
  
  BACKGROUND
  ellen.reisinger@physiologie.uni-freiburg.de.
authors.affiliation: Institut EIT 1, Universitaet der Bundeswehr Muenchen, Neubiberg, Germany.
authors.forename: David
authors.initials: D
authors.lastname: Meintrup
authors.forename: Ellen
authors.initials: E
authors.lastname: Reisinger
mesh_terms: D003198:Computer Simulation; D003627:Data Interpretation, Statistical; D020869:Gene Expression Profiling / Q000379:methods*; D005786:Gene Expression Regulation / Q000235:genetics*; D008957:Models, Genetic; D015233:Models, Statistical; D020411:Oligonucleotide Array Sequence Analysis / Q000379:methods*