| Autor: |
Gauglitz, Julia M., West, Kiana A., Bittremieux, Wout, Williams, Candace L., Weldon, Kelly C., Panitchpakdi, Morgan, Di Ottavio, Francesca, Aceves, Christine M., Brown, Elizabeth, Sikora, Nicole C., Jarmusch, Alan K., Martino, Cameron, Tripathi, Anupriya, Meehan, Michael J., Dorrestein, Kathleen, Shaffer, Justin P., Coras, Roxana, Vargas, Fernando, Goldasich, Lindsay DeRight, Schwartz, Tara |
| Zdroj: |
Nature Biotechnology; Dec2022, Vol. 40 Issue 12, p1774-1779, 6p |
| Abstrakt: |
Human untargeted metabolomics studies annotate only ~10% of molecular features. We introduce reference-data-driven analysis to match metabolomics tandem mass spectrometry (MS/MS) data against metadata-annotated source data as a pseudo-MS/MS reference library. Applying this approach to food source data, we show that it increases MS/MS spectral usage 5.1-fold over conventional structural MS/MS library matches and allows empirical assessment of dietary patterns from untargeted data. Metabolomics is improved by using a reference library of both known and unknown molecules. [ABSTRACT FROM AUTHOR] |
| Databáze: |
Complementary Index |
| Externí odkaz: |
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