Department of Pharmaceutical Chemistry, University of California San Francisco, San Francisco, California, USA.
BMC Bioinformatics. 2011 Nov 9;12:436. doi: 10.1186/1471-2105-12-436.
In the post-genomic era, the rapid increase in high-throughput data calls for computational tools capable of integrating data of diverse types and facilitating recognition of biologically meaningful patterns within them. For example, protein-protein interaction data sets have been clustered to identify stable complexes, but scientists lack easily accessible tools to facilitate combined analyses of multiple data sets from different types of experiments. Here we present clusterMaker, a Cytoscape plugin that implements several clustering algorithms and provides network, dendrogram, and heat map views of the results. The Cytoscape network is linked to all of the other views, so that a selection in one is immediately reflected in the others. clusterMaker is the first Cytoscape plugin to implement such a wide variety of clustering algorithms and visualizations, including the only implementations of hierarchical clustering, dendrogram plus heat map visualization (tree view), k-means, k-medoid, SCPS, AutoSOME, and native (Java) MCL.
Results are presented in the form of three scenarios of use: analysis of protein expression data using a recently published mouse interactome and a mouse microarray data set of nearly one hundred diverse cell/tissue types; the identification of protein complexes in the yeast Saccharomyces cerevisiae; and the cluster analysis of the vicinal oxygen chelate (VOC) enzyme superfamily. For scenario one, we explore functionally enriched mouse interactomes specific to particular cellular phenotypes and apply fuzzy clustering. For scenario two, we explore the prefoldin complex in detail using both physical and genetic interaction clusters. For scenario three, we explore the possible annotation of a protein as a methylmalonyl-CoA epimerase within the VOC superfamily. Cytoscape session files for all three scenarios are provided in the Additional Files section.
The Cytoscape plugin clusterMaker provides a number of clustering algorithms and visualizations that can be used independently or in combination for analysis and visualization of biological data sets, and for confirming or generating hypotheses about biological function. Several of these visualizations and algorithms are only available to Cytoscape users through the clusterMaker plugin. clusterMaker is available via the Cytoscape plugin manager.
在后基因组时代，高通量数据的快速增长需要能够整合各种类型数据的计算工具，并有助于识别其中具有生物学意义的模式。例如，已经对蛋白质-蛋白质相互作用数据集进行了聚类以识别稳定的复合物，但科学家们缺乏易于访问的工具来方便地对来自不同类型实验的多个数据集进行联合分析。在这里，我们介绍了 clusterMaker，这是一个 Cytoscape 插件，它实现了几种聚类算法，并提供了网络、聚类树和热图视图的结果。Cytoscape 网络与所有其他视图相关联，因此在一个视图中进行选择会立即反映在其他视图中。clusterMaker 是第一个实现如此广泛的聚类算法和可视化的 Cytoscape 插件，包括层次聚类、聚类树加热图可视化（树视图）、k-均值、k-中位数、SCPS、AutoSOME 和本机（Java）MCL 的唯一实现。
结果以三种使用场景的形式呈现：使用最近发表的小鼠相互作用组和近百种不同细胞/组织类型的小鼠微阵列数据集分析蛋白质表达数据；鉴定酵母酿酒酵母中的蛋白质复合物；以及毗邻氧螯合物（VOC）酶超家族的聚类分析。对于场景一，我们探索了特定于特定细胞表型的功能丰富的小鼠相互作用组，并应用了模糊聚类。对于场景二，我们使用物理和遗传相互作用簇来详细探索前折叠复合物。对于场景三，我们探索了 VOC 超家族中可能将蛋白质注释为甲基丙二酰辅酶 A 差向异构酶。所有三个场景的 Cytoscape 会话文件都在附加文件部分提供。
Cytoscape 插件 clusterMaker 提供了许多聚类算法和可视化效果，可单独或组合使用，用于分析和可视化生物数据集，并确认或生成关于生物功能的假设。这些可视化效果和算法中的一些仅可通过 clusterMaker 插件提供给 Cytoscape 用户。clusterMaker 可通过 Cytoscape 插件管理器获得。
