Onoprishvili, Tornike, Yuan, Jui-Hung, Petrov, Kamen, Ingalalli, Vijay, Khederlarian, Lila, Leuchtenmuller, Niklas, Chandra, Sona, Duarte, Aurelien, Bender, Andreas, and Gloaguen, Yoann
Bioinformatics Feb 2025
Untargeted metabolomics involves a large-scale comparison of the fragmentation pattern of a mass spectrum against a database containing known spectra. Given the number of comparisons involved, this step can be time-consuming.In this work, we present a GPU-accelerated cosine similarity implementation for Tandem Mass Spectrometry (MS), with an approximately 1000-fold speedup compared to the MatchMS reference implementation, without any loss of accuracy. This improvement enables repository-scale spectral library matching for compound identification without the need for large compute clusters. This impact extends to any spectral comparison-based methods such as molecular networking approaches and analogue search.All code, results, and notebooks supporting are freely available under the MIT license at https://github.com/pangeAI/simms/.