Merging Two Gene Expression Studies via Cross Platform Normalization

@article{citeulike:2479514, 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@email.unc.edu 10.1093/bioinformatics/btn083}, author = {Shabalin, Andrey A. and Tjelmeland, Hakon and Fan, Cheng and Perou, Charles M. and Nobel, Andrew B. }, citeulike-article-id = {2479514}, doi = {http://dx.doi.org/10.1093/bioinformatics/btn083}, journal = {Bioinformatics}, keywords = {cross-platform, microarray}, month = {March}, pages = {btn083+}, posted-at = {2008-05-06 16:29:27}, priority = {2}, title = {Merging Two Gene Expression Studies via Cross Platform Normalization}, url = {http://dx.doi.org/10.1093/bioinformatics/btn083}, year = {2008} }

TY - JOUR ID - citeulike:2479514 L3 - citeulike-article-id:2479514 TI - Merging Two Gene Expression Studies via Cross Platform Normalization JF - Bioinformatics SP - btn083 N2 - 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@email.unc.edu 10.1093/bioinformatics/btn083 KW - cross-platform KW - microarray AU - Shabalin, Andrey AU - Tjelmeland, Hakon AU - Fan, Cheng AU - Perou, Charles AU - Nobel, Andrew PY - 2008/03/05/ UR - http://dx.doi.org/10.1093/bioinformatics/btn083 ER -