Workflows for automated downstream data analysis and visualization in large-scale computational mass spectrometry.
Workflows for automated downstream data analysis and visualization in large-scale computational mass spectrometry.
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DOI：
10.1002/pmic.201400391
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发表时间：
2015-04
期刊：
影响因子：
3.4
通讯作者：
Kohlbacher, Oliver
中科院分区：
文献类型：
--
作者：
Aiche, Stephan;Sachsenberg, Timo;Kenar, Erhan;Walzer, Mathias;Wiswedel, Bernd;Kristl, Theresa;Boyles, Matthew;Duschl, Albert;Huber, Christian G.;Berthold, Michael R.;Reinert, Knut;Kohlbacher, Oliver
基于MS的蛋白质组学和代谢组学是由新仪器、实验方法和分析方法的发展驱动的快速发展的研究领域。单片分析工具在单一任务上表现良好，但缺乏科普不断变化的要求和实验设置的灵活性。工作流系统将小型处理工具联合收割机组合成复杂的分析管道，允许定制和灵活的数据处理工作流，可以发布或与协作者共享。在这篇文章中，我们提出了从开源软件框架OpenMS到工作流引擎Konstanz Information Miner（KNIME）的计算MS的既定工具的集成，用于分析大型数据集和生产高质量的可视化。我们提供了示例工作流程来演示计算MS中三种不同任务的组合数据处理和可视化：在复杂的实验设置中基于同量异位素质量标签的定量，代谢物的无标记定量和鉴定，以及蛋白质组学实验的质量控制。
MS-based proteomics and metabolomics are rapidly evolving research fields driven by the development of novel instruments, experimental approaches, and analysis methods. Monolithic analysis tools perform well on single tasks but lack the flexibility to cope with the constantly changing requirements and experimental setups. Workflow systems, which combine small processing tools into complex analysis pipelines, allow custom-tailored and flexible data-processing workflows that can be published or shared with collaborators. In this article, we present the integration of established tools for computational MS from the open-source software framework OpenMS into the workflow engine Konstanz Information Miner (KNIME) for the analysis of large datasets and production of high-quality visualizations. We provide example workflows to demonstrate combined data processing and visualization for three diverse tasks in computational MS: isobaric mass tag based quantitation in complex experimental setups, label-free quantitation and identification of metabolites, and quality control for proteomics experiments.
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影响因子：
3
作者：
Sturm M;Bertsch A;Gröpl C;Hildebrandt A;Hussong R;Lange E;Pfeifer N;Schulz-Trieglaff O;Zerck A;Reinert K;Kohlbacher O
通讯作者：
Kohlbacher O
HMDB：人类代谢组数据库。
影响因子：
14.9
作者：
Wishart, David S;Tzur, Dan;Knox, Craig;Eisner, Roman;Guo, An Chi;Young, Nelson;Cheng, Dean;Jewell, Kevin;Arndt, David;Sawhney, Summit;Fung, Chris;Nikolai, Lisa;Lewis, Mike;Coutouly, Marie-Aude;Forsythe, Ian;Tang, Peter;Shrivastava, Savita;Jeroncic, Kevin;Stothard, Paul;Amegbey, Godwin;Block, David;Hau, David D;Wagner, James;Miniaci, Jessica;Clements, Melisa;Gebremedhin, Mulu;Guo, Natalie;Zhang, Ying;Duggan, Gavin E;Macinnis, Glen D;Weljie, Alim M;Dowlatabadi, Reza;Bamforth, Fiona;Clive, Derrick;Greiner, Russ;Li, Liang;Marrie, Tom;Sykes, Brian D;Vogel, Hans J;Querengesser, Lori
通讯作者：
Querengesser, Lori
影响因子：
7.4
作者：
Thompson, A;Schäfer, J;Hamon, C
通讯作者：
Hamon, C
影响因子：
4.4
作者：
Weisser, Hendrik;Nahnsen, Sven;Malinstroemt, Lars
通讯作者：
Malinstroemt, Lars
影响因子：
5.8
作者：
Craig, R;Beavis, RC
通讯作者：
Beavis, RC