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Title: | Use of principal component analysis and the GE-biplot for the graphical exploration of gene expression data - Reply | Authors: | Gohlmann, Hinrich W. Kass, Stefan U. Lewi, Paul J. BIJNENS, Luc Wouters, Luc MOLENBERGHS, Geert |
Issue Date: | 2005 | Publisher: | BLACKWELL PUBLISHING | Source: | BIOMETRICS, 61(2). p. 632-634 | Abstract: | This note is in response to Wouters et al. (2003, Biometrics 59, 1131–1139) who compared three methods for exploring gene expression data. Contrary to their summary that principal component analysis is not very informative, we show that it is possible to determine principal component analyses that are useful for exploratory analysis of microarray data. We also present another biplot representation, the GE-biplot (Gene Expression biplot), that is a useful method for exploring gene expression data with the major advantage of being able to aid interpretation of both the samples and the genes relative to each other. | Notes: | Limburgs Univ Ctr, Ctr Stat, Transnatl Univ Limburg, B-3590 Diepenbeek, Belgium. Barrier Therapeut Nv, B-2440 Geel, Belgium. Johnson & Johson Pharmaceut Res & Dev, Div Janssen Pharmaceut NV, Ctr Mol Design, B-2340 Beerse, Belgium. Johnson & Johson Pharmaceut Res & Dev, Div Janssen Pharmaceut NV, Dept Genom Technol, B-2340 Beerse, Belgium. Johnson & Johson Pharmaceut Res & Dev, Div Janssen Pharmaceut NV, Dept Global Biometr & Reporting, B-2340 Beerse, Belgium.Wouters, L, Limburgs Univ Ctr, Ctr Stat, Transnatl Univ Limburg, Univ Campus,Gebouw D, B-3590 Diepenbeek, Belgium. | Keywords: | bioinformatics; biplot; data visualization; GE biplot; gene expression data; microarray data; multivariate exploratory data analysis; principal component analysis; SVD | Document URI: | http://hdl.handle.net/1942/2035 | ISSN: | 0006-341X | e-ISSN: | 1541-0420 | DOI: | 10.1111/j.1541-0420.2005.00367.x | ISI #: | 000229893900039 | Category: | A1 | Type: | Journal Contribution | Validations: | ecoom 2006 |
Appears in Collections: | Research publications |
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