A web-based system for creating, viewing, and editing precursor mass spectrometry ground truth data
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A web‑based system for creating, viewing, and editing precursor mass spectrometry ground truth data Jessica Henning and Rob Smith*
*Correspondence: [email protected] Department of Computer Science, University of Montana, 32 Campus Drive, Missoula, MT 59812, USA
Abstract Background: Mass spectrometry (MS) uses mass-to-charge ratios of measured particles to decode the identities and quantities of molecules in a sample. Interpretation of raw MS depends upon data processing algorithms that render it human-interpretable. Quantitative MS workflows are complex experimental chains and it is crucial to know the performance and bias of each data processing method as they impact accuracy, coverage, and statistical significance of the result. Creation of the ground truth necessary for quantitatively evaluating MS1-aware algorithms is difficult and tedious task, and better software for creating such datasets would facilitate more extensive evaluation and improvement of MS data processing algorithms. Results: We present JS-MS 2.0, a software suite that provides a dependency-free, browser-based, one click, cross-platform solution for creating MS1 ground truth. The software retains the first version’s capacity for loading, viewing, and navigating MS1 data in 2- and 3-D, and adds tools for capturing, editing, saving, and viewing isotopic envelope and extracted isotopic chromatogram features. The software can also be used to view and explore the results of feature finding algorithms. Conclusions: JS-MS 2.0 enables faster creation and inspection of MS1 ground truth data. It is publicly available with an MIT license at github.com/optimusmoose/jsms. Keywords: Mass spectrometry, Mass spectrometry viewer, MS1 feature finding, Open source mass spectrometry software
Background Mass spectrometry (MS) is a powerful tool for the analysis of molecular components (such as proteins, peptides, lipids, and metabolites) in biological samples across a broad range of applications [1]. MS experiments generate datasets consisting of millions of 3-D points consisting of mass-to-charge (m/z), retention time (RT), and intensity. MS experiments require the mapping of all or some of these points to signal groups that correspond to a single (or multiple, in the case of isomers) molecules at a given charge state. This process, called feature detection, has been addressed by numerous algorithms, commercial software, and public software such as MaxQuant [2], MZMine 2 [3], © The Author(s) 2020. This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not i
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