title: A novel method of differential gene expression analysis using multiple cDNA libraries applied to the identification of tumour endothelial genes.
abstract: BACKGROUND
  In this study, differential gene expression analysis using complementary DNA (cDNA) libraries has been improved. Firstly by the introduction of an accurate method of assigning Expressed Sequence Tags (ESTs) to genes and secondly, by using a novel likelihood ratio statistical scoring of differential gene expression between two pools of cDNA libraries. These methods were applied to the latest available cell line and bulk tissue cDNA libraries in a two-step screen to predict novel tumour endothelial markers. Initially, endothelial cell lines were in silico subtracted from non-endothelial cell lines to identify endothelial genes. Subsequently, a second bulk tumour versus normal tissue subtraction was employed to predict tumour endothelial markers.
  
  
  RESULTS
  From an endothelial cDNA library analysis, 431 genes were significantly up regulated in endothelial cells with a False Discovery Rate adjusted q-value of 0.01 or less and 104 of these were expressed only in endothelial cells. Combining the cDNA library data with the latest Serial Analysis of Gene Expression (SAGE) library data derived a complete list of 459 genes preferentially expressed in endothelium. 27 genes were predicted tumour endothelial markers in multiple tissues based on the second bulk tissue screen.
  
  
  CONCLUSIONS
  This approach represents a significant advance on earlier work in its ability to accurately assign an EST to a gene, statistically measure differential expression between two pools of cDNA libraries and predict putative tumour endothelial markers before entering the laboratory. These methods are of value and available http://www.compbio.ox.ac.uk/data/diffex.html to researchers that are interested in the analysis of transcriptomic data.
authors.affiliation: Cancer Research UK Angiogenesis Group, Institute for Biomedical Research, University of Birmingham Medical School, Edgbaston, BIRMINGHAM, B15 2TT, UK. j.m.herbert@bham.ac.uk
authors.forename: John M J
authors.initials: JM
authors.lastname: Herbert
authors.forename: Dov
authors.initials: D
authors.lastname: Stekel
authors.forename: Sharon
authors.initials: S
authors.lastname: Sanderson
authors.forename: Victoria L
authors.initials: VL
authors.lastname: Heath
authors.forename: Roy
authors.initials: R
authors.lastname: Bicknell
mesh_terms: D000465:Algorithms; D019295:Computational Biology / Q000379:methods*; D042783:Endothelial Cells / Q000378:metabolism*; D020224:Expressed Sequence Tags; D020869:Gene Expression Profiling / Q000379:methods*; D015972:Gene Expression Regulation, Neoplastic / Q000235:genetics; D015723:Gene Library; D005819:Genetic Markers / Q000235:genetics*; D006801:Humans; D016013:Likelihood Functions; D009369:Neoplasms / Q000235:genetics* / Q000378:metabolism
chemical_list: D005819:Genetic Markers