A universal language for finding mass spectrometry data patterns
Tito Damiani, Alan K. Jarmusch, Allegra T. Aron, Daniel Petras, Vanessa V. Phelan, Haoqi Nina Zhao, Wout Bittremieux, Deepa Acharya, Mohammed M. A. Ahmed, Anelize Bauermeister, Matthew J. Bertin, Paul D. Boudreau, Ricardo M. Borges, Benjamin P. Bowen, Christopher J. Brown, Fernanda O. Chagas, Kenneth D. Clevenger, Mário S. P. Correia, William J. Crandall, Max Crüsemann, Eoin Fahy, Oliver Fiehn, Neha Garg, William H. Gerwick, Jeffrey R. Gilbert, Daniel Globisch, Paulo Wender Portal Gomes, Steffen Heuckeroth, C. Andrew James, Scott A. Jarmusch, Sarvar A. Kakhkhorov, Kyo Bin Kang, Nikolas Kessler, Roland D. Kersten, Hyun Woo Kim, Riley D. Kirk, Oliver Kohlbacher, Eftychia Eva Kontou, Ken Liu, Itzel Lizama-Chamu, Gordon T. Luu, Tal Luzzatto‐Knaan, Helena Mannochio-Russo, Michael T. Marty, Yuki Matsuzawa, Andrew C. McAvoy, Laura‐Isobel McCall, Osama G. Mohamed, Omri Nahor, Heiko Neuweger, Timo H. J. Niedermeyer, Kozo Nishida, Trent R. Northen, Kirsten E. Overdahl, Johannes Rainer, Raphael Reher, Elys P. Rodríguez, Timo Sachsenberg, Laura M. Sanchez, Robin Schmid, Cole Stevens, Shankar Subramaniam, Zhenyu Tian, Ashootosh Tripathi, Hiroshi Tsugawa, Justin J. J. van der Hooft, Andrea Vicini, Axel Walter, Tilmann Weber, Quanbo Xiong, Tao Xu, Tomáš Pluskal, Pieter C. Dorrestein, Mingxun Wang
Abstract
Despite being information rich, the vast majority of untargeted mass spectrometry data are underutilized; most analytes are not used for downstream interpretation or reanalysis after publication. The inability to dive into these rich raw mass spectrometry datasets is due to the limited flexibility and scalability of existing software tools. Here we introduce a new language, the Mass Spectrometry Query Language (MassQL), and an accompanying software ecosystem that addresses these issues by enabling the community to directly query mass spectrometry data with an expressive set of user-defined mass spectrometry patterns. Illustrated by real-world examples, MassQL provides a data-driven definition of chemical diversity by enabling the reanalysis of all public untargeted metabolomics data, empowering scientists across many disciplines to make new discoveries. MassQL has been widely implemented in multiple open-source and commercial mass spectrometry analysis tools, which enhances the ability, interoperability and reproducibility of mining of mass spectrometry data for the research community.