Journal of the American Society for Mass SpectrometryBioinformaticsPeer-reviewed journal article
Comparison of Cosine, Modified Cosine, and Neutral Loss Based Spectrum Alignment For Discovery of Structurally Related Molecules
Wout BittremieuxiD, Robin SchmidiD, Florian HuberiD, Justin J. J. van der HooftiD, Mingxun WangiD, Pieter C. DorresteiniD
- Citations
- 90
- FWCI
- 5.47
- Field percentile
- top 2%
Abstract
Spectrum alignment of tandem mass spectrometry (MS/MS) data using the modified cosine similarity and subsequent visualization as molecular networks have been demonstrated to be a useful strategy to discover analogs of molecules from untargeted MS/MS-based metabolomics experiments. Recently, a neutral loss matching approach has been introduced as an alternative to MS/MS-based molecular networking, with an implied performance advantage in finding analogs that cannot be discovered using existing MS/MS spectrum alignment strategies. To comprehensively evaluate the scoring properties of neutral loss matching, the cosine similarity, and the modified cosine similarity, similarity measures of 955,228 peptide MS/MS spectrum pairs and 10 million small molecule MS/MS spectrum pairs were compared. This comparative analysis revealed that the modified cosine similarity outperformed neutral loss matching and the cosine similarity in all cases. The data further indicated that the performance of MS/MS spectrum alignment depends on the location and type of the modification, as well as the chemical compound class of fragmented molecules.
Reproducibility ledger
Nobody has reported trying to reproduce this paper yet. Did you replicate an experiment or run the code? Your report saves the next lab a week.
Sign in to file a reproducibility report.
Related papers
- Spec2Vec: Improved mass spectral similarity scoring through learning of structural relationships
Florian Huber, Lars Ridder, … Justin J. J. van der Hooft·PLoS Computational BiologyPeer-reviewed·Feb 16, 2021
- BLINK: Ultrafast tandem mass spectrometry cosine similarity scoring
Thomas V. Harwood, Daniel G. C. Treen, … Benjamin P. Bowen·bioRxiv·Feb 14, 2023
- SIMILE enables alignment of fragmentation mass spectra with statistical significance
Daniel G. C. Treen, Trent R. Northen, Benjamin P. Bowen·bioRxiv·Feb 24, 2021
- MS2DeepScore - a novel deep learning similarity measure for mass fragmentation spectrum comparisons
Florian Huber, Sven van der Burg, … Lars Ridder·bioRxiv·Apr 18, 2021
- METLIN Neutral Loss Database Enhances Similarity Analysis
G. Siuzdak, A. Aisporna, … M. Giera·bioRxiv·Apr 2, 2021
- Implementations of the chemical structural and compositional similarity metric in R and Python
Asker Brejnrod, Madeleine Ernst, … Manimozhiyan Arumugam·bioRxiv·Feb 11, 2019