Journal
BIOINFORMATICS
Volume 24, Issue 9, Pages 1154-1160Publisher
OXFORD UNIV PRESS
DOI: 10.1093/bioinformatics/btn083
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Funding
- NCI NIH HHS [P50-CA58223-09A1, R01-CA-101227-01] Funding Source: Medline
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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@email.unc.edu Supplementary information: Supplementary data are available at Bioinformatics online.
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