Automated workflow composition in mass spectrometry-based proteomics
Automated workflow composition in mass spectrometry-based proteomics
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DOI：
10.1093/bioinformatics/bty646
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发表时间：
2019-02-15
期刊：
影响因子：
5.8
通讯作者：
Schwammle, Veit
中科院分区：
文献类型：
--
作者：
Palmblad, Magnus;Lamprecht, Anna-Lena;Schwammle, Veit
动机：在文献中描述了对质谱（MS）数据进行操作的许多软件实用程序，并且提供了作为用于组装专用工作流的构建块的特定操作。找出哪些工具和组合在实践中是适用的或最佳的往往是困难的。因此，研究人员面临的困难，在选择实际和有效的数据分析pipelines为一个特定的实验design.Results：我们提供了一个工具包，以支持研究人员在识别，比较和基准多个工作流程，从个人的生物信息学工具。自动化的工作流组合是由工具的语义注释埃达姆本体。为了证明我们的框架的实际使用，我们创建和评估了一些逻辑和语义等效的工作流程，用于代表基于MS的蛋白质组学中常见任务的四个用例。事实上，我们发现，工作流程计算的结果可能会有很大的不同，强调了一个框架，促进他们的系统探索的好处。
Motivation: Numerous software utilities operating on mass spectrometry (MS) data are described in the literature and provide specific operations as building blocks for the assembly of on-purpose workflows. Working out which tools and combinations are applicable or optimal in practice is often hard. Thus researchers face difficulties in selecting practical and effective data analysis pipelines for a specific experimental design.Results: We provide a toolkit to support researchers in identifying, comparing and benchmarking multiple workflows from individual bioinformatics tools. Automated workflow composition is enabled by the tools' semantic annotation in terms of the EDAM ontology. To demonstrate the practical use of our framework, we created and evaluated a number of logically and semantically equivalent workflows for four use cases representing frequent tasks in MS-based proteomics. Indeed we found that the results computed by the workflows could vary considerably, emphasizing the benefits of a framework that facilitates their systematic exploration.