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Statistical Applications in Genetics and Molecular Biology

Editor-in-Chief: Sanguinetti, Guido


IMPACT FACTOR 2018: 0.536
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1544-6115
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Volume 7, Issue 1

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Volume 1 (2002)

Estimating Number of Clusters Based on a General Similarity Matrix with Application to Microarray Data

Shafagh Fallah / David Tritchler / Joseph Beyene
Published Online: 2008-08-02 | DOI: https://doi.org/10.2202/1544-6115.1261

Many clustering methods require that the number of clusters believed present in a given data set be specified a priori, and a number of methods for estimating the number of clusters have been developed. However, the selection of the number of clusters is well recognized as a difficult and open problem and there is a need for methods which can shed light on specific aspects of the data. This paper adopts a model for clustering based on a specific structure for a similarity matrix. Publicly available gene expression data sets are analyzed to illustrate the method and the performance of our method is assessed by simulation.

Keywords: cluster analysis; eigenanalysis; microarray; segmented regression; scree plot

About the article

Published Online: 2008-08-02


Citation Information: Statistical Applications in Genetics and Molecular Biology, Volume 7, Issue 1, ISSN (Online) 1544-6115, DOI: https://doi.org/10.2202/1544-6115.1261.

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