OpenMS Community nodes for Proteome Discoverer provide workflows integrated into Thermo Fisher Proteome Discoverer (PD)

Currently, extends PD with methods for:

  • Label-free quantification
  • Protein-RNA cross-link identification.





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


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

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 nodes in Proteome Discoverer, please create a new issue at:

More Information

For additional information about OpenMS integration in Proteome Discoverer please visit the Getting Started page.

Release notes: 16/07/16: New version 2.0.3 of PD community nodes

This release contains important bug fixes and other improvements. Please note that the parameters of the RNPxl processing node and the LFQProfiler consensus node have changed. Users who upgrade from previous versions must remove and re-add these nodes from existing workflows.

The list of closed issues solved by this release can be found here


  • All LFQProfiler result tables are now interconnected and can be conveniently navigated via “Show Associated Tables”
  • Nodes requiring a sequence DB nodes now allow to select multiple FASTA files
  • Bug fix: Aborting workflows is no longer delayed by running external OpenMS processes
  • Bug fix: RNPxl spectrum visualization UI crashes
  • Bug fix: RNPxl XIC filtering uses wrong m/z tolerance value

Release notes: 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.


  • 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)