MSplusR: An R Package for Visualization of MS/MS Spectral Data Using UMAP
DOI:
https://doi.org/10.51094/jxiv.1042Keywords:
mass spectrometry, metabolomics, dimensionality reductionAbstract
Mass spectrometry-based omics research requires efficient tools for processing and visualizing MS/MS spectral data. To address this, we developed MSplusR, an R package that integrates preprocessing, similarity computation, dimensionality reduction, and interactive visualization. MSplusR processes raw mzML files into binned and normalized spectral matrices, computes similarity matrices for clustering, and employs UMAP and PCA for dimensionality reduction. An interactive Shiny viewer enables visualization of UMAP projections and MS/MS spectra. Applicable to metabolomics, proteomics, and lipidomics, MSplusR facilitates biomarker discovery and sample clustering. The package is open-source and available on GitHub, with documentation to ensure reproducibility and broad adoption.
Conflicts of Interest Disclosure
No conflicts of interest to disclose.Downloads *Displays the aggregated results up to the previous day.
References
Dunn W.B., Erban A., Weber R.J., Creek D.J., Brown M., Breitling R., Hankemeier T., Goodacre R., Neumann S., Kopka J., Viant M.R. (2013). "Mass appeal: metabolite identification in mass spectrometry-focused untargeted metabolomics." Metabolomics, 9(1), 44–66. doi:10.1007/s11306-012-0434-4.
Aebersold R., Mann M. (2016). "Mass-spectrometry-based proteomics." Nature, 537(7620), 347–355. doi:10.1038/nature19949.
Tanaka S., Fujita Y., Parry H.E., Yoshizawa A.C., Morimoto K., Murase M., Yamada Y., Yao J., Utsunomiya S., Kajihara S., Fukuda M., Ikawa M., Tabata T., Takahashi K., Aoshima K., Nihei Y., Nishioka T., Oda Y., Tanaka K. (2014). "Mass++: A visualization and analysis tool for mass spectrometry." Journal of Proteome Research, 13(8), 3846–3853. doi:10.1021/pr5006636.
Kind T., Fiehn O. (2010). "Advances in structure elucidation of small molecules using mass spectrometry." Bioanalytical Reviews, 2(1–4), 23–60. doi:10.1007/s12566-010-0015-6.
Smith C.A., Want E.J., O’Maille G., Abagyan R., Siuzdak G. (2006). "XCMS: Processing mass spectrometry data for metabolite profiling using nonlinear peak alignment, matching, and identification." Analytical Chemistry, 78(3), 779–787. doi:10.1021/ac051437y.
Shannon P., Markiel A., Ozier O., Baliga N.S., Wang J.T., Ramage D., Amin N., Schwikowski B., Ideker T. (2003). "Cytoscape: A software environment for integrated models of biomolecular interaction networks." Genome Research, 13(11), 2498–2504. doi:10.1101/gr.1239303.
Becht E., McInnes L., Healy J., Dutertre C.A., Kwok I.W., Ng L.G., Ginhoux F., Newell E.W. (2019). "Dimensionality reduction for visualizing single-cell data using UMAP." Nature Biotechnology, 37(1), 38–44. doi:10.1038/nbt.4314.
McInnes L., Healy J., Melville J. (2018). "UMAP: Uniform Manifold Approximation and Projection for Dimension Reduction." arXiv preprint arXiv:1802.03426. Retrieved from https://arxiv.org/abs/1802.03426.
Couvillion S.P., Nagana Gowda G.A., Raftery D., Suslick K.S. (2015). "Metabolomics." Annual Review of Analytical Chemistry, 8, 17–37. doi:10.1146/annurev-anchem-071114-040237.
Tyanova S., Temu T., Cox J. (2016). "The MaxQuant computational platform for mass spectrometry-based shotgun proteomics." Nature Protocols, 11(12), 2301–2319. doi:10.1038/nprot.2016.136.
Downloads
Posted
Submitted: 2025-01-13 00:16:39 UTC
Published: 2025-01-16 08:21:24 UTC
License
Copyright (c) 2025
Hiroyuki Yamamoto
This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.
