A method for visual identification of small sample subgroups and potential biomarkers

Details A method for visual identification of small sample subgroups and potential biomarkers A method for visual identification of small sample subgroups and potential biomarkers

2011-11-30

arxiv.org/abs/1111.7125v1

Annals of Applied Statistics 2011, Vol. 5, No. 3, 2131-2149

Statistics

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Published in at http://dx.doi.org/10.1214/11-AOAS460 the Annals of Applied Statistics (http://www.imstat.org/aoas/) by the Ins

Scientific paper

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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