Department of Computer Science and Department of Physics, Wake Forest University, Winston-Salem, NC 27109, USA.
Bioinformatics. 2011 May 1;27(9):1330-1. doi: 10.1093/bioinformatics/btr115. Epub 2011 Mar 3.
Standard and Consensus Clustering Analysis Tool for Microarray Data (SC²ATmd) is a MATLAB-implemented application specifically designed for the exploration of microarray gene expression data via clustering. Implementation of two versions of the clustering validation method figure of merit allows for performance comparisons between different clustering algorithms, and tailors the cluster analysis process to the varying characteristics of each dataset. Along with standard clustering algorithms this application also offers a consensus clustering method that can generate reproducible clusters across replicate experiments or different clustering algorithms. This application was designed specifically for the analysis of gene expression data, but may be used with any numerical data as long as it is in the right format.
SC²ATmd may be freely downloaded from http://www.compbiosci.wfu.edu/tools.htm.
微阵列数据的标准和共识聚类分析工具（SC²ATmd）是一个基于 MATLAB 实现的应用程序，专门用于通过聚类来探索微阵列基因表达数据。两种聚类验证方法的实施允许在不同的聚类算法之间进行性能比较，并根据每个数据集的不同特征来调整聚类分析过程。除了标准聚类算法外，该应用程序还提供了一种共识聚类方法，可在重复实验或不同聚类算法之间生成可重复的聚类。该应用程序专门用于分析基因表达数据，但只要数据格式正确，也可以用于任何数值数据。
SC²ATmd 可从 http://www.compbiosci.wfu.edu/tools.htm 免费下载。
