On a resampling approach for tests on the number of clusters with mixture model-based clustering of tissue samples


Autoria(s): McLachlan, GJ; Khan, N
Contribuinte(s)

B. Arnold

J de Leeuw

Data(s)

01/01/2004

Resumo

We consider the problem of assessing the number of clusters in a limited number of tissue samples containing gene expressions for possibly several thousands of genes. It is proposed to use a normal mixture model-based approach to the clustering of the tissue samples. One advantage of this approach is that the question on the number of clusters in the data can be formulated in terms of a test on the smallest number of components in the mixture model compatible with the data. This test can be carried out on the basis of the likelihood ratio test statistic, using resampling to assess its null distribution. The effectiveness of this approach is demonstrated on simulated data and on some microarray datasets, as considered previously in the bioinformatics literature. (C) 2004 Elsevier Inc. All rights reserved.

Identificador

http://espace.library.uq.edu.au/view/UQ:68132

Idioma(s)

eng

Publicador

Academic Press

Palavras-Chave #Statistics & Probability #Microarray Gene Expression Data #Mixture Models #Clustering Of Tissue Samples #Tests On Number Of Clusters #Likelihood Ratio Statistic #Resampling Approach #Gene-expression Data #Molecular Classification #Patterns #Transformations #Prediction #C1 #230204 Applied Statistics #780101 Mathematical sciences
Tipo

Journal Article