ViMMS 2.0: A framework to develop, test and optimise fragmentation strategies in LC-MS metabolomics

Wandy, J. , Davies, V. , McBride, R., Weidt, S., Rogers, S. and Daly, R. (2022) ViMMS 2.0: A framework to develop, test and optimise fragmentation strategies in LC-MS metabolomics. Journal of Open Source Software, 7(71), 3990. (doi: 10.21105/joss.03990)

Abstract

Summary The choice of fragmentation strategies used during mass-spectrometry-based data acquisition directly affects the quality and coverage of subsequent structural identification – a crucial step in untargeted metabolomics data analysis. However, developing novel fragmentation strategies is challenging due to the high experimental cost of running an actual mass spectrometry instrument and the lack of a programmable simulation environment to support their development. ViMMS 2.0 is a software framework that can be used to develop new fragmentation strategies in metabolomics completely in-silico as well as on mass spectrometry instruments. The framework allows users to generate chemical objects (produced synthetically or extracted from existing mzML files) and simulate a tandem mass spectrometry process, where different fragmentation strategies can be rapidly implemented, tested and evaluated. In this paper, we present ViMMS 2.0, highlighting the software design choices of the framework and illustrate with an example how a new fragmentation strategy could be implemented in ViMMS 2.0.

• Item Type: Articles
• Status: Published
• Refereed: Yes
• Glasgow Author(s) Enlighten ID: McBride, Mr Ross and Weidt, Dr Stefan and Daly, Dr Ronan and Davies, Dr Vinny and Wandy, Dr Joe and Rogers, Dr Simon
• Authors: Wandy, J., Davies, V., McBride, R., Weidt, S., Rogers, S., and Daly, R.
• College/School: College of Medical Veterinary and Life Sciences; College of Science and Engineering > School of Computing Science
• Journal Name: Journal of Open Source Software
• Publisher: Open Journals
• ISSN: 2475-9066
• ISSN (Online): 2475-9066
• Copyright Holders: Copyright © Wandy et al. (2022)
• First Published: First published in Journal of Open Source Software 7(71):3990
• Publisher Policy: Reproduced under a Creative Commons licence

Project Code	Award No	Project Name	Principal Investigator	Funder's Name	Funder Ref	Lead Dept
300982		Exploiting Closed-Loop Aspects in Computationally and Data Intensive Analytics	Roderick Murray-Smith	Engineering and Physical Sciences Research Council (EPSRC)	EP/R018634/1	Computing Science