Paper Info
Title
Identification of differentially expressed spatial clusters using humoral response microarray data.
Abstract
The antibody microarray is a powerful chip-based technology for profiling hundreds of proteins simultaneously and is used increasingly nowadays. To study humoral response in pancreatic cancers, Patwa et al. (2007) developed a two-dimensional liquid separation technique and built a two-dimensional antibody microarray. However, identifying differential expression regions on the antibody microarray requires the use of appropriate statistical methods to fairly assess the large amounts of data generated. In this paper, we propose a permutation-based test using spatial information of the two-dimensional antibody microarray. By borrowing strength from the neighboring differentially expressed spots, we are able to detect the differential expression region with very high power controlling type I error at 0.05 in our simulation studies. We also apply the proposed methodology to a real microarray dataset.
Year
DOI
Venue
2009
10.1016/j.csda.2008.04.026
Computational Statistics & Data Analysis
Keywords
Field
DocType
spatial cluster,neighboring differentially,humoral response microarray data,two-dimensional protein microarray,real microarray dataset,two-dimensional liquid separation technique,appropriate statistical method,differential expression,protein microarray,two-dimensional antibody microarray,borrowing strength,proposed methodology,biomedical research,type i error,chip,spatial information,bioinformatics,microarray data
Spatial analysis,Microarray,Antibody microarray,Computer science,Microarray analysis techniques,Gene chip analysis,Type I and type II errors,Statistics,Microarray databases,Protein microarray
Journal
Volume
Issue
ISSN
53
8
0167-9473
Citations 
PageRank 
References 
0
0.34
1
Authors
4
Name
Order
Citations
PageRank
Jincao Wu100.34
Tasneem H Patwa200.34
David M Lubman300.34
Debashis Ghosh449649.16