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HAMSTER: visualizing microarray experiments as a set of minimum spanning trees

机译:仓鼠:将微阵列实验可视化为一组最小生成树

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Background Visualization tools allow researchers to obtain a global view of the interrelationships between the probes or experiments of a gene expression (e.g. microarray) data set. Some existing methods include hierarchical clustering and k-means. In recent years, others have proposed applying minimum spanning trees (MST) for microarray clustering. Although MST-based clustering is formally equivalent to the dendrograms produced by hierarchical clustering under certain conditions; visually they can be quite different. Methods HAMSTER (Helpful Abstraction using Minimum Spanning Trees for Expression Relations) is an open source system for generating a set of MSTs from the experiments of a microarray data set. While previous works have generated a single MST from a data set for data clustering, we recursively merge experiments and repeat this process to obtain a set of MSTs for data visualization. Depending on the parameters chosen, each tree is analogous to a snapshot of one step of the hierarchical clustering process. We scored and ranked these trees using one of three proposed schemes. HAMSTER is implemented in C++ and makes use of Graphviz for laying out each MST. Results We report on the running time of HAMSTER and demonstrate using data sets from the NCBI Gene Expression Omnibus (GEO) that the images created by HAMSTER offer insights that differ from the dendrograms of hierarchical clustering. In addition to the C++ program which is available as open source, we also provided a web-based version (HAMSTER+) which allows users to apply our system through a web browser without any computer programming knowledge. Conclusion Researchers may find it helpful to include HAMSTER in their microarray analysis workflow as it can offer insights that differ from hierarchical clustering. We believe that HAMSTER would be useful for certain types of gradient data sets (e.g time-series data) and data that indicate relationships between cells/tissues. Both the source and the web server variant of HAMSTER are available from http://hamster.cbrc.jp/ webcite.
机译:背景可视化工具可让研究人员获得基因表达(例如微阵列)数据集的探针或实验之间的相互关系的全局视图。现有的一些方法包括层次聚类和k均值。近年来,其他人提出将最小生成树(MST)用于微阵列聚类。尽管基于MST的聚类在形式上等效于在某些条件下通过分层聚类产生的树状图;在视觉上,它们可以完全不同。方法HAMSTER(使用最小生成树的表达关系的帮助抽象)是一个开放源代码系统,用于根据微阵列数据集的实验生成一组MST。尽管先前的工作已经从数据集中为数据聚类生成了一个MST,但我们递归合并实验并重复此过程以获得一组用于数据可视化的MST。根据选择的参数,每棵树都类似于分层聚类过程的一个步骤的快照。我们使用三种提议的方案之一对这些树进行了评分和排名。 HAMSTER用C ++实现,并利用Graphviz布局每个MST。结果我们报告了HAMSTER的运行时间,并使用NCBI基因表达综合(GEO)的数据集证明了HAMSTER创建的图像提供了与层次聚类树状图不同的见解。除了作为开放源代码提供的C ++程序之外,我们还提供了基于Web的版本(HAMSTER +),该版本允许用户通过Web浏览器来应用我们的系统,而无需任何计算机编程知识。结论研究人员可能会发现将HAMSTER纳入其微阵列分析工作流程会有所帮助,因为它可以提供与层次聚类不同的见解。我们认为HAMSTER对于某些类型的梯度数据集(例如时间序列数据)和指示细胞/组织之间关系的数据很有用。可以从http://hamster.cbrc.jp/webcite获得HAMSTER的源代码和Web服务器变体。

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