On a resampling approach for tests on the number of clusters with mixture model-based clustering of tissue samples
On a resampling approach for tests on the number of clusters with mixture model-based clustering of tissue samples
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DOI：
10.1016/j.jmva.2004.02.002
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发表时间：
2004-07-01
影响因子：
1.6
通讯作者：
Khan, N
中科院分区：
文献类型：
--
作者：
McLachlan, GJ;Khan, N
我们认为，在有限数量的组织样本中，可能有几千个基因的基因表达的集群的数量进行评估的问题。建议使用基于正态混合模型的方法对组织样本进行聚类。这种方法的一个优点是，在数据中的集群的数量的问题，可以制定在一个测试的最小数量的组件的混合模型兼容的数据。该检验可以在似然比检验统计量的基础上进行，使用回归来评估其零分布。模拟数据和一些微阵列数据集上证明了这种方法的有效性，如先前在生物信息学文献中所考虑的。(C)2004年爱思唯尔公司All rights reserved.
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.