Bioinformatics Advance Access originally published online on March 5, 2008
Bioinformatics 2008 24(9):1154-1160; doi:10.1093/bioinformatics/btn083
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Merging two gene-expression studies via cross-platform normalization
1Department of Statistics and Operations Research, University of North Carolina at Chapel Hill, Chapel Hill, USA, 2Department of Mathematical Sciences, Norwegian University of Science and Technology, Trondheim, Norway, 3Lineberger Comprehensive Cancer Center, University of North Carolina at Chapel Hill, 4Department of Pathology and Laboratory Medicine, University of North Carolina at Chapel Hill and 5Department of Genetics, University of North Carolina at Chapel Hill, Chapel Hill, USA
*To whom correspondence should be addressed.
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Abstract |
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Motivation: Gene-expression microarrays are currently being applied in a variety of biomedical applications. This article considers the problem of how to merge datasets arising from different gene-expression studies of a common organism and phenotype. Of particular interest is how to merge data from different technological platforms.
Results: The article makes two contributions to the problem. The first is a simple cross-study normalization method, which is based on linked gene/sample clustering of the given datasets. The second is the introduction and description of several general validation measures that can be used to assess and compare cross-study normalization methods. The proposed normalization method is applied to three existing breast cancer datasets, and is compared to several competing normalization methods using the proposed validation measures.
Availability: The supplementary materials and XPN Matlab code are publicly available at website: https://genome.unc.edu/xpn
Contact: shabalin{at}email.unc.edu
Supplementary information: Supplementary data are available at Bioinformatics online.
Received on November 28, 2007; revised on February 7, 2008; accepted on March 1, 2008
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