Feature-based Molecular Networking in the GNPS Analysis Environment

Nothias, L. F.; Petras, D.; Schmid, R.; Duehrkop, K.; Rainer, J.; Sarvepalli, A.; Protsyuk, I.; Ernst, M.; Tsugawa, H.; Fleischauer, M.; Aicheler, F.; Aksenov, A.; Alka, O.; Allard, P.-M.; Barsch, A.; Cachet, X.; Caraballo, M.; Da Silva, R.; Dang, T.; Garg, N.; Gauglitz, J. M.; Gurevich, A.; Isaac, G.; Jarmusch, A. K.; Kamenik, Z.; Kang, K. B.; Kessler, N.; Koester, I.; Korf, A.; Le Gouellec, A.; Ludwig, M.; Martin H., C.; McCall, L.-I.; McSayles, J.; Meyer, S.; Mohimani, H.; Morsy, M.; Moyne, O.; Neumann, S.; Neuweger, H.; Nguyen, N. H.; Esposito-Nothias, M.; Paolini, J.; Phelan, V.; Pluskal,

doi:10.1101/812404

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bioRxiv · 10.1101/812404

Feature-based Molecular Networking in the GNPS Analysis Environment

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Abstract

Molecular networking has become a key method used to visualize and annotate the chemical space in non-targeted mass spectrometry-based experiments. However, distinguishing isomeric compounds and quantitative interpretation are currently limited. Therefore, we created Feature-based Molecular Networking (FBMN) as a new analysis method in the Global Natural Products Social Molecular Networking (GNPS) infrastructure. FBMN leverages feature detection and alignment tools to enhance quantitative analyses and isomer distinction, including from ion-mobility spectrometry experiments, in molecular networks.

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Nothias, L. F., Petras, D., Schmid, R., Duehrkop, K., Rainer, J., Sarvepalli, A., Protsyuk, I., Ernst, M., Tsugawa, H., Fleischauer, M., Aicheler, F., Aksenov, A., Alka, O., Allard, P.-M., Barsch, A., Cachet, X., Caraballo, M., Da Silva, R., Dang, T., Garg, N., Gauglitz, J. M., Gurevich, A., Isaac, G., Jarmusch, A. K., Kamenik, Z., Kang, K. B., Kessler, N., Koester, I., Korf, A., Le Gouellec, A., Ludwig, M., Martin H., C., McCall, L.-I., McSayles, J., Meyer, S., Mohimani, H., Morsy, M., Moyne, O., Neumann, S., Neuweger, H., Nguyen, N. H., Esposito-Nothias, M., Paolini, J., Phelan, V., Pluskal,. 2019-10-20. Feature-based Molecular Networking in the GNPS Analysis Environment. https://doi.org/10.1101/812404

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