Finding disease specific alterations in the co-expression of genes.
BACKGROUND
Standard analysis routines for microarray data aim at differentially expressed genes. In this paper, we address the complementary problem of detecting sets of differentially co-expressed genes in two phenotypically distinct sets of expression profiles.


RESULTS
We introduce a score for differential co-expression and suggest a computationally efficient algorithm for finding high scoring sets of genes. The use of our novel method is demonstrated in the context of simulations and on real expression data from a clinical study.
Kostka
Dennis
D
Max Planck Institute for Molecular Genetics, Berlin, Germany. dennis.kostka@molgen.mpg.de
Spang
Rainer
R
D000465:Algorithms; D014408:Biomarkers, Tumor / Q000032:analysis*; D003936:Diagnosis, Computer-Assisted / Q000379:methods*; D020869:Gene Expression Profiling / Q000379:methods*; D006801:Humans; D007938:Leukemia / Q000175:diagnosis* / Q000378:metabolism*; D005810:Multigene Family; D009363:Neoplasm Proteins / Q000032:analysis*; D015203:Reproducibility of Results; D012680:Sensitivity and Specificity
D014408:Biomarkers, Tumor; D009363:Neoplasm Proteins