1. OpenMS 3 enables reproducible analysis of large-scale mass spectrometry data
- Author
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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, Matthias, Patikas, N., Pilz, M., Startek, M.P., Kutuzova, S., Heumos, L., Charkow, J., Sing, J.C., Feroz, A., Siraj, A., Weisser, H., Dijkstra, T.M.H., Perez-Riverol, Y., Röst, H., Kohlbacher, O., Sachsenberg, T., 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, Matthias, Patikas, N., Pilz, M., Startek, M.P., Kutuzova, S., Heumos, L., Charkow, J., Sing, J.C., Feroz, A., Siraj, A., Weisser, H., Dijkstra, T.M.H., Perez-Riverol, Y., Röst, H., Kohlbacher, O., and Sachsenberg, T.
- Abstract
Mass spectrometry (MS) has become an indispensable analytical technique in the life sciences. For more than two decades, the OpenMS1 open-source project has been aiding mass spectrometrists with data processing. In version 3, OpenMS extends its capabilities beyond bottom-up proteomics to include high-throughput workflows in top-down proteomics, metabolomics, structural biology and oligonucleotide mass spectrometry. OpenMS makes analyses from emerging fields available to experimentalists, enhances computational workflows, and provides a reworked Python interface to make the computational methods more accessible to bioinformaticians and data scientists (Fig. 1). To help new users explore and quickly become productive with OpenMS, the website and documentation were modernized for this release. For a detailed overview of new tools and changes — based on more than 20,000 Git commits contributed by 150+ developers since the last major release in 2015 — we refer the reader to the Supplementary Note and Supplementary Table 1.
- Published
- 2024