Lu Yue, He Xin, Zhong Sheng
Department of Computer Science, University of Illinois at Urbana-Champaign, IL, USA.
Nucleic Acids Res. 2007 Jul;35(Web Server issue):W105-14. doi: 10.1093/nar/gkm408. Epub 2007 Jun 1.
OSCAR is a web platform for cluster and cross-species analysis of microarray data. It provides a comprehensive but friendly environment to both users and algorithm developers. For users, OSCAR provides cluster tools for both single and multiple species data, together with interactive analysis features. For single species data, OSCAR currently provides Hierarchical Clustering, K-means, partition around medoids (PAM), Self-Organizing Map (SOM), Tight Clustering and a novel algorithm called 'Consensus Tight-clustering'. The new Consensus Tight-clustering algorithm delivers robust gene clusters and its result is more resistant to false positives than other state-of-the-art algorithms. For cross-species data analysis, OSCAR provides two novel computational tools: 'coherentCluster', 'coherentSubset' and a novel visualization tool: 'comparative heatmap'. Applying the coherentCluster algorithm to human and fly aging data, we identified several coherent clusters of genes, which share co-regulation patterns that are highly correlated with the aging process in both of the two species. One coherent cluster suggests insulin receptor (INSR) may regulate Pax6 in both species and across different tissues. Further analysis with human brain expression and pathological data suggests an INSR->Pax6->quinone oxidoreductase (NQO1)->detoxification neuro-protective pathway might be present in aging or diseased brain. For algorithm developers, OSCAR is a plug-and-play platform. With little effort, developers can plug their own algorithms into the OSCAR server without revealing the source codes, which will equip their command line executables with user-friendly interface and interactive analysis capability. In summary, OSCAR initiates an open platform for development and application of clustering and cross-species analysis programs. OSCAR stands for an open system for cluster analysis of microarray data. It is available at: http://biocomp.bioen.uiuc.edu/oscar.
OSCAR是一个用于微阵列数据聚类和跨物种分析的网络平台。它为用户和算法开发者提供了一个全面但友好的环境。对于用户而言,OSCAR提供了针对单物种和多物种数据的聚类工具,以及交互式分析功能。对于单物种数据,OSCAR目前提供层次聚类、K均值聚类、围绕中心点划分(PAM)、自组织映射(SOM)、紧密聚类以及一种名为“一致性紧密聚类”的新算法。新的一致性紧密聚类算法能够生成稳健的基因簇,其结果比其他现有算法更能抵抗假阳性。对于跨物种数据分析,OSCAR提供了两种新的计算工具:“相干聚类”、“相干子集”以及一种新的可视化工具:“比较热图”。将相干聚类算法应用于人类和果蝇衰老数据,我们识别出了几个基因相干簇,它们共享与这两个物种衰老过程高度相关的共调控模式。一个相干簇表明胰岛素受体(INSR)可能在两个物种的不同组织中调控Pax6。对人类大脑表达和病理数据的进一步分析表明,衰老或患病大脑中可能存在INSR->Pax6->醌氧化还原酶(NQO1)->解毒神经保护途径。对于算法开发者来说,OSCAR是一个即插即用的平台。开发者只需付出少量努力,就可以在不透露源代码的情况下将自己的算法插入到OSCAR服务器中,这将为他们的命令行可执行文件配备用户友好的界面和交互式分析能力。总之,OSCAR开创了一个用于聚类和跨物种分析程序开发与应用的开放平台。OSCAR代表微阵列数据聚类分析的开放系统。可通过以下网址获取:http://biocomp.bioen.uiuc.edu/oscar 。