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Probabilistic Model Based Hough Transform for Detection of Co-expression Patterns in Three-Color cDNA Microarray Data

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3 Author(s)
Tino, P. ; Sch. of Comput. Sci., Univ. of Birmingham Birmingham, Birmingham, UK ; Hongya Zhao ; Hong Yan

Three-color cDNA microarrays built on normal-disease-drug samples can be used to assess the effects of a drug on the genomic scale. We have recently shown that the Hough transform (HT) applied to a two-dimensional representation of the three color intensities can be used to detect groups of co-expressed genes. However, the standard HT is not well suited for the purpose because: (1) the essayed genes need first to be hard-partitioned into equally and differentially expressed genes, causing the HT to ignore possible information in the former group; (2) the two-dimensional gene representations are negatively correlated and there is no direct way of expressing this in the standard HT; (3) it is not clear how to quantify the association of co-expressed genes with the line along which they cluster. We address these deficiencies by formulating a dedicated probabilistic model based HT. The approach is applied to assess the effects of the drug Rg1 on homocysteine-treated human umbilical vein endothetial cells. Compared with our previous study we robustly detect stronger natural groupings of co-expressed genes. Moreover, the gene groups show coherent biological functions with high significance, as detected by the Gene ontology analysis.

Published in:

Bioinformatics, Systems Biology and Intelligent Computing, 2009. IJCBS '09. International Joint Conference on

Date of Conference:

3-5 Aug. 2009

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