Chen Yidong, Meltzer Paul S
National Human Genome Research Institute, National Institutes of Health, Bethesda, Maryland, USA.
Curr Protoc Bioinformatics. 2005 Jul;Chapter 7:Unit 7.11. doi: 10.1002/0471250953.bi0711s10.
Expression profiling of biological samples using microarray technologies has proven to be a powerful tool for molecular classification and biomarker identification. Visualization of similarities between biological samples from their molecular signatures is essential in forming new hypotheses. Multidimensional scaling is one of the methods that converts the structure in the similarity matrix to a simple geometrical picture: the larger the dissimilarity between two samples (evaluated through gene expression profiling), the further apart the points representing the experiments in the picture should be. In this unit, we will discuss the mathematical fundamentals of this method, along with step-by-step procedures that allow users to quickly obtain the results, provided that all necessary resources are ready. Examples of applying the MDS program and the interpretation of these results are also provided in this unit.
使用微阵列技术对生物样品进行表达谱分析已被证明是分子分类和生物标志物鉴定的有力工具。从分子特征可视化生物样品之间的相似性对于形成新假设至关重要。多维标度是将相似性矩阵中的结构转换为简单几何图形的方法之一:两个样品之间的差异越大(通过基因表达谱评估),图中代表实验的点就应相距越远。在本单元中,我们将讨论该方法的数学基础,以及在所有必要资源准备就绪的情况下,让用户能够快速获得结果的分步程序。本单元还提供了应用MDS程序的示例以及这些结果的解释。