Significance Analysis and Improved Discovery of Differentially Co-expressed Gene Sets in Microarray Data
Sixth IEEE International Conference on Data Mining - Workshops (ICDMW'06) (2006)
Hong Kong, China
Dec. 18, 2006 to Dec. 22, 2006
Haixia Li , Genome Institute of Singapore
R. Krishna Murthy Karuturi , Genome Institute of Singapore
Differential co-expression signifies the deregulated pathways as opposed to differential expression that signifies change of gene expression. Kostka and Spang proposed a score and an algorithm to elicit differentially co-expressed gene-sets. We analyze the statistical properties of their score in two different data processing settings and obtain respective null-distributions to provide the statistical significance of a gene-set through the p-value of its score. We propose to use these p-values to automate their algorithm. In addition, we propose a two stage algorithm, based on Friendly Neighbors (FNs) algorithm, called FNs-KS algorithm for improved discovery of such gene set i.e. improves both sensitivity and specificity of the discovery.
H. Li and R. K. Karuturi, "Significance Analysis and Improved Discovery of Differentially Co-expressed Gene Sets in Microarray Data," Sixth IEEE International Conference on Data Mining - Workshops (ICDMW'06)(ICDMW), Hong Kong, China, 2006, pp. 196-201.