OpenMS 3 enables reproducible analysis of large-scale mass spectrometry data

Julianus Pfeuffer; Chris Bielow; Samuel Wein; Kyowon Jeong; Eugen Netz; Axel Walter; Oliver Alka; Lars Nilse; Pasquale Domenico Colaianni; Douglas McCloskey; Jihyung Kim; George Rosenberger; Leon Bichmann; Mathias Walzer; Johannes Veit; Bertrand Boudaud; Matthias Bernt; Nikolaos Patikas; Matteo Pilz; Michał Piotr Startek; Svetlana Kutuzova; Lukas Heumos; Joshua Charkow; Justin Cyril Sing; Ayesha Feroz; Arslan Siraj; Hendrik Weisser; Tjeerd M.H. Dijkstra; Yasset Perez-Riverol; Hannes Röst; Oliver Kohlbacher; Timo Sachsenberg

doi:10.1038/s41592-024-02197-7

OpenMS 3 enables reproducible analysis of large-scale mass spectrometry data

Julianus Pfeuffer, Chris Bielow, Samuel Wein, Kyowon Jeong, Eugen Netz, Axel Walter, Oliver Alka, Lars Nilse, Pasquale Domenico Colaianni, Douglas McCloskey, Jihyung Kim, George Rosenberger, Leon Bichmann, Mathias Walzer, Johannes Veit, Bertrand Boudaud, Matthias Bernt, Nikolaos Patikas, Matteo Pilz, Michał Piotr StartekSvetlana Kutuzova, Lukas Heumos, Joshua Charkow, Justin Cyril Sing, Ayesha Feroz, Arslan Siraj, Hendrik Weisser, Tjeerd M.H. Dijkstra, Yasset Perez-Riverol, Hannes Röst, Oliver Kohlbacher, Timo Sachsenberg^*

^*Corresponding author for this work

Research output: Contribution to journal › Letter › Research › peer-review

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Original language	English
Journal	Nature Methods
Volume	21
Issue number	3
Pages (from-to)	365–367
ISSN	1548-7091
DOIs	https://doi.org/10.1038/s41592-024-02197-7
Publication status	Published - 2024

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Pfeuffer, J., Bielow, C., Wein, S., Jeong, K., Netz, E., Walter, A., Alka, O., Nilse, L., Colaianni, P. D., McCloskey, D., Kim, J., Rosenberger, G., Bichmann, L., Walzer, M., Veit, J., Boudaud, B., Bernt, M., Patikas, N., Pilz, M., ... Sachsenberg, T. (2024). OpenMS 3 enables reproducible analysis of large-scale mass spectrometry data. Nature Methods, 21(3), 365–367. https://doi.org/10.1038/s41592-024-02197-7

OpenMS 3 enables reproducible analysis of large-scale mass spectrometry data. / Pfeuffer, Julianus; Bielow, Chris; Wein, Samuel; Jeong, Kyowon; Netz, Eugen; Walter, Axel; Alka, Oliver; Nilse, Lars; Colaianni, Pasquale Domenico; McCloskey, Douglas; Kim, Jihyung; Rosenberger, George; Bichmann, Leon; Walzer, Mathias; Veit, Johannes; Boudaud, Bertrand; Bernt, Matthias; Patikas, Nikolaos; Pilz, Matteo; Startek, Michał Piotr; Kutuzova, Svetlana; Heumos, Lukas; Charkow, Joshua; Sing, Justin Cyril; Feroz, Ayesha; Siraj, Arslan; Weisser, Hendrik; Dijkstra, Tjeerd M.H.; Perez-Riverol, Yasset; Röst, Hannes; Kohlbacher, Oliver; Sachsenberg, Timo.

In: Nature Methods, Vol. 21, No. 3, 2024, p. 365–367.

Research output: Contribution to journal › Letter › Research › peer-review

Pfeuffer, J, Bielow, C, Wein, S, Jeong, K, Netz, E, Walter, A, Alka, O, Nilse, L, Colaianni, PD, McCloskey, D, Kim, J, Rosenberger, G, Bichmann, L, Walzer, M, Veit, J, Boudaud, B, Bernt, M, Patikas, N, Pilz, M, Startek, MP, Kutuzova, S, Heumos, L, Charkow, J, Sing, JC, Feroz, A, Siraj, A, Weisser, H, Dijkstra, TMH, Perez-Riverol, Y, Röst, H, Kohlbacher, O & Sachsenberg, T 2024, 'OpenMS 3 enables reproducible analysis of large-scale mass spectrometry data', Nature Methods, vol. 21, no. 3, pp. 365–367. https://doi.org/10.1038/s41592-024-02197-7

Pfeuffer, Julianus ; Bielow, Chris ; Wein, Samuel ; Jeong, Kyowon ; Netz, Eugen ; Walter, Axel ; Alka, Oliver ; Nilse, Lars ; Colaianni, Pasquale Domenico ; McCloskey, Douglas ; Kim, Jihyung ; Rosenberger, George ; Bichmann, Leon ; Walzer, Mathias ; Veit, Johannes ; Boudaud, Bertrand ; Bernt, Matthias ; Patikas, Nikolaos ; Pilz, Matteo ; Startek, Michał Piotr ; Kutuzova, Svetlana ; Heumos, Lukas ; Charkow, Joshua ; Sing, Justin Cyril ; Feroz, Ayesha ; Siraj, Arslan ; Weisser, Hendrik ; Dijkstra, Tjeerd M.H. ; Perez-Riverol, Yasset ; Röst, Hannes ; Kohlbacher, Oliver ; Sachsenberg, Timo. / OpenMS 3 enables reproducible analysis of large-scale mass spectrometry data. In: Nature Methods. 2024 ; Vol. 21, No. 3. pp. 365–367.

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title = "OpenMS 3 enables reproducible analysis of large-scale mass spectrometry data",

author = "Julianus Pfeuffer and Chris Bielow and Samuel Wein and Kyowon Jeong and Eugen Netz and Axel Walter and Oliver Alka and Lars Nilse and Colaianni, {Pasquale Domenico} and Douglas McCloskey and Jihyung Kim and George Rosenberger and Leon Bichmann and Mathias Walzer and Johannes Veit and Bertrand Boudaud and Matthias Bernt and Nikolaos Patikas and Matteo Pilz and Startek, {Micha{\l} Piotr} and Svetlana Kutuzova and Lukas Heumos and Joshua Charkow and Sing, {Justin Cyril} and Ayesha Feroz and Arslan Siraj and Hendrik Weisser and Dijkstra, {Tjeerd M.H.} and Yasset Perez-Riverol and Hannes R{\"o}st and Oliver Kohlbacher and Timo Sachsenberg",

note = "Funding Information: C.B. was in part supported by the Chan Zuckerberg EOSS program (179). J.P. was funded by Forschungscampus MODAL (project grant 3FO18501). K.J., E.N. and T.S. were supported by the Ministry of Science, Research and Arts Baden-W{\"u}rttemberg. A.S. and A.F. are part of the MSCA-ITN-2020 PROTrEIN project, which received funding from the European Union{\textquoteright}s Horizon 2020 research and innovation program under the Marie Sk{\l}odowska-Curie grant agreement No: 956148. J.C. was funded by the Government of Canada through Genome Canada and the Ontario Genomics Institute (OGI-164) and supported by the Ontario Graduate Scholarship. J.C.S. was funded by the European Research Area Network Personalized Medicine Cofund (PerProGlio). A.W. was supported by the Deutsche Forschungsgemeinschaft (DFG, German Research Foundation TRR 261/1,Z03). S.W. was supported by de.NBI (031A535A), Analytics for Biologics (H2020-MSCA-ITN-2017), the EU H2020 project EPIC-XS (H2020-INFRAIA), TRR (TP Z03), and TUE.AI. S.K. was funded by Horizon 2020 under grant agreement No 686070. M.P.S. was funded by Polish National Science Centre grant no. 2017/26/D/ST6/00304. Y.P.-R. acknowledges funding from EMBL core funding, Wellcome grants (208391/Z/17/Z, 223745/Z/21/Z), and the EU H2020 project EPIC-XS (823839). ",

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AU - Pfeuffer, Julianus

AU - Bielow, Chris

AU - Wein, Samuel

AU - Jeong, Kyowon

AU - Netz, Eugen

AU - Walter, Axel

AU - Alka, Oliver

AU - Nilse, Lars

AU - Colaianni, Pasquale Domenico

AU - McCloskey, Douglas

AU - Kim, Jihyung

AU - Rosenberger, George

AU - Bichmann, Leon

AU - Walzer, Mathias

AU - Veit, Johannes

AU - Boudaud, Bertrand

AU - Bernt, Matthias

AU - Patikas, Nikolaos

AU - Pilz, Matteo

AU - Startek, Michał Piotr

AU - Kutuzova, Svetlana

AU - Heumos, Lukas

AU - Charkow, Joshua

AU - Sing, Justin Cyril

AU - Feroz, Ayesha

AU - Siraj, Arslan

AU - Weisser, Hendrik

AU - Dijkstra, Tjeerd M.H.

AU - Perez-Riverol, Yasset

AU - Röst, Hannes

AU - Kohlbacher, Oliver

AU - Sachsenberg, Timo

N1 - Funding Information: C.B. was in part supported by the Chan Zuckerberg EOSS program (179). J.P. was funded by Forschungscampus MODAL (project grant 3FO18501). K.J., E.N. and T.S. were supported by the Ministry of Science, Research and Arts Baden-Württemberg. A.S. and A.F. are part of the MSCA-ITN-2020 PROTrEIN project, which received funding from the European Union’s Horizon 2020 research and innovation program under the Marie Skłodowska-Curie grant agreement No: 956148. J.C. was funded by the Government of Canada through Genome Canada and the Ontario Genomics Institute (OGI-164) and supported by the Ontario Graduate Scholarship. J.C.S. was funded by the European Research Area Network Personalized Medicine Cofund (PerProGlio). A.W. was supported by the Deutsche Forschungsgemeinschaft (DFG, German Research Foundation TRR 261/1,Z03). S.W. was supported by de.NBI (031A535A), Analytics for Biologics (H2020-MSCA-ITN-2017), the EU H2020 project EPIC-XS (H2020-INFRAIA), TRR (TP Z03), and TUE.AI. S.K. was funded by Horizon 2020 under grant agreement No 686070. M.P.S. was funded by Polish National Science Centre grant no. 2017/26/D/ST6/00304. Y.P.-R. acknowledges funding from EMBL core funding, Wellcome grants (208391/Z/17/Z, 223745/Z/21/Z), and the EU H2020 project EPIC-XS (823839).

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JO - Nature Methods

JF - Nature Methods

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