Label-free quantification with OpenMS


Timo Sachsenberg⁽¹⁾, Julianus Pfeuffer⁽²⁾ and Oliver Kohlbacher⁽³⁾
1 University of Tübingen
2 Freie Unibersität Berlin
3 Eberhard Karls University Tuebingen

Description of the workshop:

Computational mass spectrometry provides important tools and bioinformatic solutions for the analysis of proteomics and metabolomics data. Non-targeted methods are ideal for unbiased discovery studies and scale well for large-scale studies (e.g., clinical proteomics/metabolomics). This de.NBI training event introduces key concepts of non-targeted label-free analysis and workflow-based processing using real-life datasets. We will introduce several open-source software tools for proteomics, primarily focusing on OpenMS ( In a hands-on session, we will demonstrate how to combine these tools into complex data analysis workflows including visualization of the results. Participants will have the opportunity to bring their own data and design custom analysis workflows together with instructors. If requested by participants, we can also guide in implementing novel methods or tool into the OpenMS framework.

Training material and handouts will be prepared for both users that want to design proteomic workflows, as well as training material for algorithm and tool developers.

Software/Data Requirements: 

The participants should bring their own laptop computers. Installer versions of all required software will be available.


Röst, Hannes L., et al. “OpenMS: a flexible open-source software platform for mass spectrometry data analysis.” Nature methods 13.9 (2016): 741-748.

Sturm, Marc, et al. “OpenMS–an open-source software framework for mass spectrometry.” BMC bioinformatics 9.1 (2008): 163.

Kohlbacher, Oliver, et al. “TOPP—the OpenMS proteomics pipeline.” Bioinformatics 23.2 (2007): e191-e197.