Bertsch Andreas, Gröpl Clemens, Reinert Knut, Kohlbacher Oliver
Division for Simulation of Biological Systems, WSI/ZBIT, Eberhard-Karls-Universität Tübingen, Tübingen, Germany.
Methods Mol Biol. 2011;696:353-67. doi: 10.1007/978-1-60761-987-1_23.
Proteomics experiments based on state-of-the-art mass spectrometry produce vast amounts of data, which cannot be analyzed manually. Hence, software is needed which is able to analyze the data in an automated fashion. The need for robust and reusable software tools triggered the development of libraries implementing different algorithms for the various analysis steps. OpenMS is such a software library and provides a wealth of data structures and algorithms for the analysis of mass spectrometric data. For users unfamiliar with programming, TOPP ("The OpenMS Proteomics Pipeline") offers a wide range of already implemented tools sharing the same interface and designed for a specific analysis task each. TOPP thus makes the sophisticated algorithms of OpenMS accessible to nonprogrammers. The individual TOPP tools can be strung together into pipelines for analyzing mass spectrometry-based experiments starting from the raw output of the mass spectrometer. These analysis pipelines can be constructed using a graphical editor. Even complex analytical workflows can thus be analyzed with ease.
基于最先进质谱技术的蛋白质组学实验会产生大量数据，这些数据无法手动分析。因此，需要能够以自动化方式分析数据的软件。对强大且可重复使用的软件工具的需求引发了用于各种分析步骤的、实现不同算法的库的开发。OpenMS就是这样一个软件库，它提供了大量用于分析质谱数据的数据结构和算法。对于不熟悉编程的用户，TOPP（“OpenMS蛋白质组学管道”）提供了广泛的已实现工具，这些工具共享相同的接口，并且各自针对特定的分析任务进行设计。因此，TOPP使非程序员也能够使用OpenMS的复杂算法。各个TOPP工具可以串联成管道，用于从质谱仪的原始输出开始分析基于质谱的实验。这些分析管道可以使用图形编辑器来构建。即使是复杂的分析工作流程也能轻松进行分析。
