Significance Analysis and Improved Discovery of Differentially Co-expressed Gene Sets in Microarray Data

Authors:
Haixia Li;R. Krishna Murthy Karuturi
Affiliations:
Genome Institute of Singapore;Genome Institute of Singapore
Venue:
ICDMW '06 Proceedings of the Sixth IEEE International Conference on Data Mining - Workshops
Year:
2006

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ICIC '08 Proceedings of the 4th international conference on Intelligent Computing: Advanced Intelligent Computing Theories and Applications - with Aspects of Theoretical and Methodological Issues

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Abstract

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.