OpenMS pipeline

OpenMS specifications


Unique identifier OMICS_02387
Name OpenMS
Software type Framework/Library
Interface Command line interface
Restrictions to use None
Operating system Unix/Linux, Mac OS, Windows
Programming languages C++, Python
License BSD 3-clause “New” or “Revised” License, GNU Lesser General Public License version 3.0
Computer skills Advanced
Version 2.2.0
Stability Stable
Maintained Yes


  • ConsensusID
  • ProteinQuantifier
  • TOPP



Add your version



  • person_outline Oliver Kohlbacher <>
  • person_outline jpfeuffer <>

Additional information ConsensusID: ProteinQuantifier:

Publications for OpenMS

OpenMS IN pipelines

PMCID: 5499783
PMID: 28713550
DOI: 10.5256/f1000research.12693.r23454

[…] sweden). in addition, europe also hosts worldwide renowned groups that are focused on the development and application of widely-used bioinformatics tools and resources, including maxquant 4, the openms framework 5, compomics 6 tools, such as peptideshaker 7, the pride database, as the world-leading proteomics repository 8 (also coordinating the global proteomexchange consortium of proteomics […]

PMCID: 5311252
PMID: 27477696
DOI: 10.1038/onc.2016.242

[…] and n-termini, and carbamidomethylation on cysteine residues, a variable modification was used for oxidation on methionine residues. quantification of tmt-10plex reporter ions was carried out using openms project's isobaricanalyzer57 (v2.0). peptide spectrum matches found at 1% false discovery rate were used to infer gene identities, which were quantified using the medians of peptide spectrum […]

PMCID: 4252003
PMID: 25420746
DOI: 10.1186/s12859-014-0376-0

[…] and bland-altman plot [23] (figures 6 and 7). in figures 6 and 7, peak area values were used for ab3d, mzmine 2 and msight, volume values were used for superhirn and intensity values were used for openms, which does not provide area values. parameters and detected features (rt and m/z) using data set 3 for each software package are provided in additional file 1 and additional file 5, […]

PMCID: 3371593
PMID: 22701464
DOI: 10.3389/fpls.2012.00123

[…] mzidentml format was developed based on the examples provided with the release of mzidentml v1.1 (jones et al., 2012) and on a mzidentml file converted with the id convert algorithm provided by the openms platform (sturm et al., 2008) from a pep.xml sequest/peptideprophet (eng et al., 1994; keller et al., 2002) search output of arabidopsis proteome measurements. the p2p4a script parses […]

PMCID: 3477001
PMID: 23095859
DOI: 10.1186/1471-2164-13-S5-S4

[…] method for identification assessment, the out files (containing assignments produced by sequest) of each set was converted to a unique idxml (v1.1) file. this is the format used by the algorithm (openms v1.4) for retention time prediction described by pfeifer et al. [18]., following elias et al. [19] recommendation, all searches used a database constructed as a composition of target protein […]

OpenMS institution(s)
Applied Bioinformatics, Department for Computer Science, University of Tuebingen, Tuebingen, Germany; Center for Bioinformatics, University of Tuebingen, Tuebingen, Germany; Center for Quantitative Biology, University of Tuebingen, Tuebingen, Germany; Biomolecular Interactions, Max Planck Institute for Developmental Biology, Tuebingen, Germany; Chair for Bioinformatics and Information Mining, Department of Computer and Information Science, University of Konstanz, Konstanz, Germany; Institute of Molecular Medicine and Cell Research, Freiburg University, Freiburg, Germany; Algorithmic Bioinformatics, Institute for Bioinformatics, FU Berlin, Berlin, Germany; European Molecular Biology Laboratory, European Bioinformatics Institute (EMBL-EBI), Wellcome Trust Genome Campus, Hinxton, Cambridge, UK
OpenMS funding source(s)
Supported by BMBF (grant numbers 031A535A, 031A430C, and 01ZX1301F) and Deutsche Forschungsgemeinschaft (SFB685/B1, Core Facilities Initiative QBiC2).

OpenMS review

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Marc Dubois's avatar image No country

Marc Dubois

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OpenMS is a C++ library for developers. Their programming interface is well done and very clear. A Python binding exposing most classes C ++ was created, an initiative that should be welcomed. It includes many algorithms for metabolomics and proteomics, all of which can be finely set. It brings new concepts of data reduction rather interesting (concept RawMap, PeakMap, FeatureMap) to theoretically manage large amounts of data. In theory only, since the development team announced reviewing the kernel openMS to greatly improve performance.