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Auto-deconvolution and molecular networking of gas chromatography-mass spectrometry data.
- Aksenov, Alexander A;
- Laponogov, Ivan;
- Zhang, Zheng;
- Doran, Sophie LF;
- Belluomo, Ilaria;
- Veselkov, Dennis;
- Bittremieux, Wout;
- Nothias, Louis Felix;
- Nothias-Esposito, Mélissa;
- Maloney, Katherine N;
- Misra, Biswapriya B;
- Melnik, Alexey V;
- Smirnov, Aleksandr;
- Du, Xiuxia;
- Jones, Kenneth L;
- Dorrestein, Kathleen;
- Panitchpakdi, Morgan;
- Ernst, Madeleine;
- van der Hooft, Justin JJ;
- Gonzalez, Mabel;
- Carazzone, Chiara;
- Amézquita, Adolfo;
- Callewaert, Chris;
- Morton, James T;
- Quinn, Robert A;
- Bouslimani, Amina;
- Orio, Andrea Albarracín;
- Petras, Daniel;
- Smania, Andrea M;
- Couvillion, Sneha P;
- Burnet, Meagan C;
- Nicora, Carrie D;
- Zink, Erika;
- Metz, Thomas O;
- Artaev, Viatcheslav;
- Humston-Fulmer, Elizabeth;
- Gregor, Rachel;
- Meijler, Michael M;
- Mizrahi, Itzhak;
- Eyal, Stav;
- Anderson, Brooke;
- Dutton, Rachel;
- Lugan, Raphaël;
- Boulch, Pauline Le;
- Guitton, Yann;
- Prevost, Stephanie;
- Poirier, Audrey;
- Dervilly, Gaud;
- Le Bizec, Bruno;
- Fait, Aaron;
- Persi, Noga Sikron;
- Song, Chao;
- Gashu, Kelem;
- Coras, Roxana;
- Guma, Monica;
- Manasson, Julia;
- Scher, Jose U;
- Barupal, Dinesh Kumar;
- Alseekh, Saleh;
- Fernie, Alisdair R;
- Mirnezami, Reza;
- Vasiliou, Vasilis;
- Schmid, Robin;
- Borisov, Roman S;
- Kulikova, Larisa N;
- Knight, Rob;
- Wang, Mingxun;
- Hanna, George B;
- Dorrestein, Pieter C;
- Veselkov, Kirill
- et al.
Published Web Location
https://doi.org/10.1038/s41587-020-0700-3Abstract
We engineered a machine learning approach, MSHub, to enable auto-deconvolution of gas chromatography-mass spectrometry (GC-MS) data. We then designed workflows to enable the community to store, process, share, annotate, compare and perform molecular networking of GC-MS data within the Global Natural Product Social (GNPS) Molecular Networking analysis platform. MSHub/GNPS performs auto-deconvolution of compound fragmentation patterns via unsupervised non-negative matrix factorization and quantifies the reproducibility of fragmentation patterns across samples.
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