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September 2011 A method for visual identification of small sample subgroups and potential biomarkers
Charlotte Soneson, Magnus Fontes
Ann. Appl. Stat. 5(3): 2131-2149 (September 2011). DOI: 10.1214/11-AOAS460


In order to find previously unknown subgroups in biomedical data and generate testable hypotheses, visually guided exploratory analysis can be of tremendous importance. In this paper we propose a new dissimilarity measure that can be used within the Multidimensional Scaling framework to obtain a joint low-dimensional representation of both the samples and variables of a multivariate data set, thereby providing an alternative to conventional biplots. In comparison with biplots, the representations obtained by our approach are particularly useful for exploratory analysis of data sets where there are small groups of variables sharing unusually high or low values for a small group of samples.


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Charlotte Soneson. Magnus Fontes. "A method for visual identification of small sample subgroups and potential biomarkers." Ann. Appl. Stat. 5 (3) 2131 - 2149, September 2011.


Published: September 2011
First available in Project Euclid: 13 October 2011

zbMATH: 1228.62149
MathSciNet: MR2884934
Digital Object Identifier: 10.1214/11-AOAS460

Keywords: biplot , Dimension reduction , multidimensional scaling , principal components analysis , visualization

Rights: Copyright © 2011 Institute of Mathematical Statistics


Vol.5 • No. 3 • September 2011
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