Skip Navigation



Bioinformatics Advance Access published online on March 5, 2008
Bioinformatics, doi:10.1093/bioinformatics/btn083
This Article
Right arrow Advance Access manuscript (PDF)
Right arrow Supplementary Data
Right arrow All Versions of this Article:
24/9/1154    most recent
btn083v1
Right arrow Alert me when this article is cited
Right arrow Alert me if a correction is posted
Services
Right arrow Email this article to a friend
Right arrow Similar articles in this journal
Right arrow Similar articles in PubMed
Right arrow Alert me to new issues of the journal
Right arrow Add to My Personal Archive
Right arrow Download to citation manager
Right arrowRequest Permissions
Google Scholar
Right arrow Articles by Shabalin, A. A
Right arrow Articles by Nobel, A. B
Right arrow Search for Related Content
PubMed
Right arrow PubMed Citation
Right arrow Articles by Shabalin, A. A
Right arrow Articles by Nobel, A. B
Social Bookmarking
Add to CiteULike   Add to Connotea   Add to Del.icio.us  
What's this?

© The Author (2008). Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oxfordjournals.org

Merging Two Gene Expression Studies via Cross Platform Normalization

Andrey A Shabalin 1,*, Håkon Tjelmeland 2, Cheng Fan 3, Charles M Perou 3,4,5 and Andrew B Nobel 1

1Department of Statistics and Operations Research, University of North Carolina at Chapel Hill
2Department of Mathematical Sciences, Norwegian University of Science and Technology
3Lineberger Comprehensive Cancer Center, University of North Carolina at Chapel Hill
4Department of Pathology and Laboratory Medicine, University of North Carolina at Chapel Hill
5Department of Genetics, University of North Carolina at Chapel Hill

*To whom correspondence should be addressed. Andrey A Shabalin, E-mail: shabalin{at}email.unc.edu


  Abstract

Motivation: Gene expression microarrays are currently being applied in a variety of biomedical applications. This paper considers the problem of how to merge data sets arising from different geneexpression studies of a common organism and phenotype. Of particular interest is how to merge data from different technological platforms.

Results: The paper 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 data sets. 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 data sets, 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

Associate Editor: Prof. David Rocke

Received on November 28, 2007; revised on February 7, 2008; accepted on March 1, 2008

Add to CiteULike CiteULike   Add to Connotea Connotea   Add to Del.icio.us Del.icio.us    What's this?




Disclaimer:
Please note that abstracts for content published before 1996 were created through digital scanning and may therefore not exactly replicate the text of the original print issues. All efforts have been made to ensure accuracy, but the Publisher will not be held responsible for any remaining inaccuracies. If you require any further clarification, please contact our Customer Services Department.