OpenMS: a flexible open-source software platform for mass spectrometry data analysis

Röst, Hannes L.; Sachsenberg, Timo; Aiche, Stephan; Bielow, Chris; Weisser, Hendrik; Aicheler, Fabian; Andreotti, Sandro; Ehrlich, Hans‐Christian; Gutenbrunner, Petra; Kenar, Erhan; Liang, Xiao; Nahnsen, Sven; Nilse, Lars; Pfeuffer, Julianus; Rosenberger, George; Rurik, Marc; Schmitt, Uwe; Veit, J.; Walzer, Mathias; Wojnar, David; Wolski, Witold; Schilling, Oliver; Choudhary, Jyoti S.; Malmström, Lars; Aebersold, Ruedi; Reinert, Knut; Kohlbacher, Oliver

doi:10.1038/nmeth.3959

Cited by 590 publications

(427 citation statements)

References 49 publications

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“…The OpenMS 27 featurefindermultiplex tool was used with the parameters listed in supplementary material Table 2. The search results were processed in KNIME to exclude any pairs with the integral of intensity differences greater than 25%.…”

Section: Methodsmentioning

confidence: 99%

Click Chemistry Reagent for Identification of Sites of Covalent Ligand Incorporation in Integral Membrane Proteins

et al. 2017

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Identifying sites of protein-ligand interaction is important for structure-based drug discovery and understanding protein structure-function relationships. Mass spectrometry (MS) has emerged as a useful tool for identifying residues covalently modified by ligands. Current methods use database searches that depend on acquiring interpretable fragmentation spectra (MS2) of peptide-ligand adducts. This is problematic for identifying sites of hydrophobic ligand incorporation in integral membrane proteins (IMPs) where poor aqueous solubility and ionization of peptide-ligand adducts and collision-induced adduct loss hinder the acquisition of quality MS2 spectra. To address these issues, we developed a Fast Ligand Identification (FLI) tag that can be attached to any alkyne-containing ligand via Cu(I)-catalyzed cycloaddition. FLI-tag adds charge to increase solubility and ionization, and utilizes stable isotope labeling for MS1 level identification of hydrophobic peptide-ligand adducts. FLI-tag was coupled to an alkynecontaining neurosteroid photolabeling reagent and used to identify peptide-steroid adducts in MS1 spectra via the stable heavy isotope pair. Peptide-steroid adducts were not identified in MS2-based database searches because collision-induced adduct loss was the dominant feature of CID fragmentation, but targeted analysis of MS1 pairs using electron transfer dissociation (ETD) markedly reduced adduct loss. Using FLI-tag and ETD we identified Glu73 as the site of photo-incorporation of our neurosteroid ligand in the IMP, mVDAC1, and top-down MS confirmed a single site of photolabeling.

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Section: Methodsmentioning

confidence: 99%

Click Chemistry Reagent for Identification of Sites of Covalent Ligand Incorporation in Integral Membrane Proteins

et al. 2017

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“…A rich set of such building blocks for mass-spectrometry data analysis is provided by the standalone, cross-platform command line tools of The OpenMS Proteomics Pipeline (TOPP) (Kohlbacher et al, 2007) which are built on top of the OpenMS C++ library (Rost et al, 2016) (an open-source software solution and programming framework for computational MS). It features more than 150 tools executing a wide range of computational mass spectrometry related tasks.…”

Section: Openmsmentioning

confidence: 99%

KNIME for reproducible cross-domain analysis of life science data

Fillbrunn

Dietz

Pfeuffer

et al. 2017

Journal of Biotechnology

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170

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Experiments in the life sciences often involve tools from a variety of domains such as mass spectrometry, next generation sequencing, or image processing. Passing the data between those tools often involves complex scripts for controlling data flow, data transformation, and statistical analysis. Such scripts are not only prone to be platform dependent, they also tend to grow as the experiment progresses and are seldomly well documented, a fact that hinders the reproducibility of the experiment. Workflow systems such as KNIME Analytics Platform aim to solve these problems by providing a platform for connecting tools graphically and guaranteeing the same results on different operating systems. As an open source software, KNIME allows scientists and programmers to provide their own extensions to the scientific community. In this review paper we present selected extensions from the life sciences that simplify data exploration, analysis, and visualization and are interoperable due to KNIME's unified data model. Additionally, we name other workflow systems that are commonly used in the life sciences and highlight their similarities and differences to KNIME.

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“…When not inside a cluster, the connection to a cluster can be configured by setting the appropriate environment variables. The Kubernetes integration in SciPipe is demonstrated through the implementation of a use case workflow consisting of a set of data preparation steps for mass-spectrometry data, using the OpenMS software suite [27] . It contains a Go file (With the .go extension) with the workflow, and a Kubernetes job-spec file in YAML format (with the .yml extension) for starting SciPipe inside a Kubernetes cluster is together with the workflow [28] .…”

Section: Scipipementioning

confidence: 99%

Approaches for containerized scientific workflows in cloud environments with applications in life science

Spjuth

Capuccini

Carone

et al. 2018

Preprint

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Containers are gaining popularity in life science research as they encompass all dependencies of provisioned tools and simplifies software installations for end users, as well as offering a form of isolation between processes. Scientific workflows are ideal to chain containers into data analysis pipelines to sustain reproducible science. In this manuscript we review the different approaches to use containers inside the workflow tools Nextflow, Galaxy, Pachyderm, Luigi, and SciPipe when deployed in cloud environments. A particular focus is placed on the workflow tool's interaction with the Kubernetes container orchestration framework.

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OpenMS: a flexible open-source software platform for mass spectrometry data analysis

Cited by 590 publications

References 49 publications

Click Chemistry Reagent for Identification of Sites of Covalent Ligand Incorporation in Integral Membrane Proteins

Click Chemistry Reagent for Identification of Sites of Covalent Ligand Incorporation in Integral Membrane Proteins

KNIME for reproducible cross-domain analysis of life science data

Approaches for containerized scientific workflows in cloud environments with applications in life science

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