An open-source framework for mass spectrometry and TOPP – The OpenMS Proteomics Pipeline

Proteome Discoverer Community Nodes

18/02/15: New version 2.0.2 of PD community nodes

This release contains a number of significant improvements and bug fixes. We strongly recommend to update!



  • Significant speedup of feature detection algorithm (30-50x!)
  • Now using a better RT alignment algorithm supporting non-linear transformations
  • Protein-level FDR filtering before protein quantification
  • Choose intensity normalization method (median, quantile, none)
  • Option to normalize using only a subset of the features (e.g., house-keeping proteins)
  • Prefiltering Fido input makes Fido much faster
  • Choose which m/z value to use for ID mapping: precursor or computed from peptide sequence
  • Various bug fixes, e.g. unique peptide quantification, path names containing commas


  • Advanced parameter “Fragment adducts” allows low-level customization of the fragmentation chemistry
  • Bug fixes


  • We now offer a manual installation package for the reported cases where the installer could not find the PD registry key and hence could not determine where to install the nodes
  • Improved documentation: installation instructions and user manual


New parameters have been added, others have become obsolete. Some parameter default values have changed. We recommend to download the current version of the processing and consensus workflows (see below), or to delete and reinsert our nodes to your existing workflows. Most importantly, the scaling of the averagine similarity score of LFQProfiler has changed. The prior default value is not a good choice.



Windows 64 bit PC with Proteome Discoverer 2.x. We recommend at least 4GB of RAM.

What are Proteome Discoverer Community Nodes?

Starting from version 2.0 Proteome Discoverer functionality can be extended by external plugins. Several OpenMS workflows are now made available as Proteome Discoverer Community Nodes. If you are interested in metabolite or small molecule analysis you might want to check out our Compound Discoverer Community Nodes.

Disclaimer: Please note that Thermo only provides the framework for the integration of third party plugins. They do neither provide any support nor take any legal responsibility for external contributions. If you have any questions, bug reports, or feature requests regarding the OpenMS Community Nodes for Proteome Discoverer, please contact the OpenMS developer mailing list instead: open-ms-developersatlistsdotsourceforgedotnet  (open-ms-developersatlistsdotsourceforgedotnet)  

License: OpenMS Proteome Discoverer Community Nodes are released under a 3-clause BSD license.

Special thanks to the SkylineProteoWizard developers for releasing their software under the Apache 2.0 license and thus allowing us to reuse their code. Our RNPxl cross-link spectrum visualization widget is based on the Skyline spectrum viewer code.

Note: Since we don’t have a way to automatically update the nodes or inform its users of an available update, please register to our OpenMS general mailing list, where updates will be announced, or check back here for updates!


Label-free quantification (LFQ) of peptides and proteins has become a very popular analytical technique in particular in clinical proteomics. Large-scale studies comprising hundreds or even thousands of LC-MS experiments require efficient computational processing tools. Here, we present the integration of an OpenMS-based LFQ workflow into the Proteome Discoverer platform.


In addition, we provide the intended processing and consensus workflow. Please note that, at the moment, the combination with Sequest HT and Percolator is mandatory, since our community nodes require some of the information produced by these nodes. Combinations with other peptide identification and validation nodes might work, but have not been tested yet.


UV induced cross-linking combined with LC-MS/MS analysis has been successful in the elucidation of protein DNA and protein RNA interactions. We recently presented RNPxl, a computational pipeline, implemented in the OpenMS framework, for the analysis of LC-MS/MS cross-link data. The RNPxl workflow is now made available to a larger audience by integration into the Proteome Discoverer platform. In addition, we were able to increase processing speed by a factor of ten compared to the previous version.


  • Q: My workflow crashes and/or an OpenMS community node complains that no spectra were found. What can I do?
  • A: Check your Spectrum Selector settings. By default, MS1 spectra are discarded. Set the “MS Order” parameter to “Any” to also keep the MS1 spectra, which are required by our tools.
  • Q: Why is the “MS/MS Spectrum Info” table in the results of the RNPxl workflow empty?
  • A: Try setting “Spectra to store” to “All” in your MSF files node in the consensus workflow.
  • Q: Can I use LFQProfiler in batch processing mode?
  • A: Yes, you can. This is described in the User Manual. However, we do not recommend to do it. See the User Manual for details.
  • Q: Can I extend the basic LFQProfiler workflow?
  • A: Yes, you can. You can do anything you want in the processing step, as long as the Sequest + Percolator part is there and LFQProfiler FF is called. The LFQProfiler consensus node requires the results from LFQProfiler FF, Sequest and Percolator, but should not interfere with additional consensus workflow branches (like grouping / validation / filtering, …). It should be safe to run these. However, LFQProfiler’s results won’t be affected by them (e.g., peptides filtered using a PD node might still be present in the LFQProfiler results, depending on the q-value filtering settings of LFQProfiler itself)
  • Q: This doesn’t work. I get “Execution failed” without further explanations!
  • A: Please let us know and send a bug report via email to our developer mailing list (see below). Please also grab your MagellanServer.log file right after the error happened and attach it (you’ll probably find it in C:\ProgramData\Thermo\Proteome Discoverer 2.x\Logs)


If you have any questions, bug reports, or feature requests, please contact the OpenMS developer mailing list: open-ms-developersatlistsdotsourceforgedotnet  (open-ms-developersatlistsdotsourceforgedotnet)  


Sturm et al. OpenMS – an open-source software framework for mass spetrometry. BMC Bioinformatics, 9:163, 2008.

Weisser et al. An automated pipeline for high-throughput label-free quantitative proteomics. J. Proteome Res., 12(4):1628–1644, 2013.

Kramer et al. Photo-cross-linking and high-resolution mass spectrometry for assignment of RNA-binding sites in RNA-binding proteins. Nat Methods., 11(10):1064-70, 2014.

Berthold et al. KNIME: The Konstanz Information Miner. In Studies in Classification, Data Analysis, and Knowledge Organization (GfKL 2007). Springer, 2007.

Serang et al. Efficient marginalization to compute protein posterior probabilities from shotgun mass spectrometry data. J Proteome Res., 9(10): 5346–5357, 2010.