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Journal of Biomedicine and Biotechnology
Volume 2010, Article ID 616358, 9 pages
http://dx.doi.org/10.1155/2010/616358
Research Article

Stability of Ranked Gene Lists in Large Microarray Analysis Studies

1Faculty of Health Sciences, Research Institute, University of Maribor, Zitna ulica 15, 2000 Maribor, Slovenia
2Laboratory for System Design, Faculty of Electrical Engineering and Computer Science, University of Maribor, Smetanova ulica 17, 2000 Maribor, Slovenia

Received 28 January 2010; Accepted 17 May 2010

Academic Editor: Nick Grishin

Copyright © 2010 Gregor Stiglic and Peter Kokol. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Abstract

This paper presents an empirical study that aims to explain the relationship between the number of samples and stability of different gene selection techniques for microarray datasets. Unlike other similar studies where number of genes in a ranked gene list is variable, this study uses an alternative approach where stability is observed at different number of samples that are used for gene selection. Three different metrics of stability, including a novel metric in bioinformatics, were used to estimate the stability of the ranked gene lists. Results of this study demonstrate that the univariate selection methods produce significantly more stable ranked gene lists than the multivariate selection methods used in this study. More specifically, thousands of samples are needed for these multivariate selection methods to achieve the same level of stability any given univariate selection method can achieve with only hundreds.