ArrayCluster: an analytic tool for clustering, data visualization and module finder on gene expression profiles
ArrayCluster: an analytic tool for clustering, data visualization and module finder on gene expression profiles
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DOI：
10.1093/bioinformatics/btl129
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发表时间：
2006-06
期刊：
影响因子：
5.8
通讯作者：
Ryo Yoshida;T. Higuchi;S. Imoto;Satoru Miyano
中科院分区：
文献类型：
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作者：
Ryo Yoshida;T. Higuchi;S. Imoto;Satoru Miyano
基因表达分析的一个重大挑战是在分子水平上发现几种疾病的未知亚型。该任务可以通过基于大量基因对收集的样品的基因表达模式进行分组来解决。然而，将常用的聚类方法应用于这样的数据集可能会由于过度学习而失败，因为要分组的样本的数量远小于等于数据集中涉及的基因数量的数据维度。为了克服这个困难，我们开发了一种新的基于模型的聚类方法，称为混合因子分析。ArrayCluster是一个免费的软件来执行混合因子分析。它为DNA微阵列实验的聚类分析、数据可视化以及与标定的分子亚型相关的基因模块转录的自动检测等提供了分析工具。
SUMMARY One of the significant challenges in gene expression analysis is to find unknown subtypes of several diseases at the molecular levels. This task can be addressed by grouping gene expression patterns of the collected samples on the basis of a large number of genes. Application of commonly used clustering methods to such a dataset however are likely to fail owing to over-learning, because the number of samples to be grouped is much smaller than the data dimension which is equal to the number of genes involved in the dataset. To overcome such difficulty, we developed a novel model-based clustering method, referred to as the mixed factors analysis. The ArrayCluster is a freely available software to perform the mixed factors analysis. It provides us some analytic tools for clustering DNA microarray experiments, data visualization and an automatic detector for module transcriptional of genes that are relevant to the calibrated molecular subtypes and so on.