Identification of differentially expressed spatial clusters using humoral response microarray data

Jincao Wu, Tasneem H. Patwa, David M. Lubman and Debashis Ghosh

Computational Statistics & Data Analysis, 2009, vol. 53, issue 8, 3094-3102

Abstract: The protein microarray is a powerful chip-based technology for profiling hundreds of proteins simultaneously and is being increasingly used. To study humoral response in pancreatic cancers, scientists have developed a two-dimensional liquid separation technique and built a two-dimensional protein microarray. However, identifying regions of differential expression on the protein microarray requires the use of appropriate statistical methods to assess the large amounts of data generated. A permutation-based test is proposed that incorporates spatial information of the two-dimensional antibody microarray. By borrowing strength from neighboring differentially expressed spots, the procedure is able to detect differentially expressed regions with high power while controlling the familywise type I error at 0.05 in simulation studies. The proposed methodology is also applied to a real microarray dataset.

Date: 2009
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