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Ensemble clustering method based on the resampling similarity measure for gene expression data

Research Institute for Basic Science, Chonnam National University

Jae Won Lee

Department of Statistics, Korea University, Seoul, Korea, jael{at}korea.ac.kr

The rapid development of microarray technologies enabled the monitoring of expression levels of thousands of genes simultaneously. Microarray technology has great potential for creating an enormous amount of data in a short time, and now becomes a new tool for studying such broad problems as classification of tumors in biology and medical science. Many statistical methods are available for analysing and systematizing these complex data into meaningful information, and one of the main goals in analysing gene expression data is the detection of samples or genes with similar expression patterns. In this paper, we developed a new clustering method of class discovery in a dataset. The performances of the new and existing methods were compared using both simulated data and real gene expression data. The proposed method was generally found to give more accurate cluster numbers and cluster assignments for individual objects than the three well-known general clustering methods such as agglomerative and divisive hierarchical clustering (HC) and self-organizing map (SOM). It also gave better results than the three consensus clustering methods based on agglomerative and divisive HC and SOM.

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This version was published on December 1, 2007

Statistical Methods in Medical Research, Vol. 16, No. 6, 539-564 (2007)
DOI: 10.1177/0962280206071842


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This Article Abstract Free Full Text (Free PDF) Free Alert me when this article is cited Alert me if a correction is posted Citation Map Services Email this article to a friend Similar articles in this journal Similar articles in PubMed Alert me to new issues of the journal Add to Saved Citations Download to citation manager Request Permissions Request Reprints Add to My Marked Citations Citing Articles Citing Articles via Google Scholar Citing Articles via Scopus Google Scholar Articles by Seo Young Kim Articles by Won Lee, J. Search for Related Content PubMed PubMed Citation Articles by Seo Young Kim, Articles by Won Lee, J. Social Bookmarking                         What's this?