Boyle John
Bioinformatics. 2005 May 15;21(10):2550-1. doi: 10.1093/bioinformatics/bti355. Epub 2005 Mar 3.
SeqExpress, a gene-expression analysis suite, has been extended to offer a number of cluster generation, refinement and visualization techniques. The cluster generation methods have been specialized to deal with aspects of the sparseness and extreme values that occur within microarray data. The results of such cluster analysis can then be refined using either: a functional enrichment based procedure, which examines each cluster to see if it possesses an unusually high or low concentration of ontology terms; or by using Expectation-Maximization to find a mixture of model based distributions within the datasets. Visualizations are provided both to explore and compare the results of the cluster generation algorithms. In addition, a tool has been developed which integrates SeqExpress with the Gene-Expression Omnibus repository. The tool provides seamless access to the large number of experimental results in the repository, so that they can be visualized and analysed locally using SeqExpress.
SeqExpress is available as a 6 MB download from http://www.seqexpress.com and runs under Windows. A server-based version is available and is required for the GEO integration. SeqExpress is not affiliated with any academic institution, funding body or commercial organization and is free to use by all.
基因表达分析套件SeqExpress已得到扩展，提供了多种聚类生成、优化和可视化技术。聚类生成方法专门用于处理微阵列数据中出现的稀疏性和极值问题。然后，可以使用以下任一方法优化此类聚类分析的结果：基于功能富集的程序，该程序检查每个聚类，看其是否具有异常高或低浓度的本体术语；或者使用期望最大化算法在数据集中找到基于模型分布的混合。提供可视化功能以探索和比较聚类生成算法的结果。此外，还开发了一个工具，将SeqExpress与基因表达综合数据库集成。该工具提供对数据库中大量实验结果的无缝访问，以便可以使用SeqExpress在本地对其进行可视化和分析。
