Compound identification; Data processing; Docker; High resolution mass spectrometry; MetFrag; Non-targeted analysis; Shiny; Spectral data analysis; Visualisation; Computer Science Applications; Physical and Theoretical Chemistry; Computer Graphics and Computer-Aided Design; Library and Information Sciences
Abstract :
[en] Shinyscreen is an R package and Shiny-based web application designed for the exploration, visualization, and quality assessment of raw data from high resolution mass spectrometry instruments. Its versatile list-based approach supports the curation of data starting from either known or "suspected" compounds (compound list-based screening) or detected masses (mass list-based screening), making it adaptable to diverse analytical needs (target, suspect or non-target screening). Shinyscreen can be operated in multiple modes, including as an R package, an interactive command-line tool, a self-documented web GUI, or a network-deployable service. Shinyscreen has been applied in environmental research, database enrichment, and educational initiatives, showcasing its broad utility. Shinyscreen is available in GitLab ( https://gitlab.com/uniluxembourg/lcsb/eci/shinyscreen ) under the Apache License 2.0. The repository contains detailed instructions for deployment and use. Additionally, a pre-configured Docker image, designed for seamless installation and operation is available, with instructions also provided in the main repository. Scientific Contribution: Shinyscreen is a fully open source prescreening application to assist analysts in the high throughput quality control of the thousands of peaks detected in high resolution mass spectrometry experiments. As a vendor-independent, cross operating system application it covers an important niche in open mass spectrometry workflows. Shinyscreen supports quality control of data for further identification or upload of spectra to public data resources, as well as teaching efforts to educate students on the importance of data quality control and rigorous identification methods.
Disciplines :
Life sciences: Multidisciplinary, general & others
Author, co-author :
KONDIC, Todor ; University of Luxembourg > Luxembourg Centre for Systems Biomedicine > Environmental Cheminformatics > Team Emma SCHYMANSKI
ELAPAVALORE, Anjana ; University of Luxembourg > Luxembourg Centre for Systems Biomedicine (LCSB) > Environmental Cheminformatics
KRIER, Jessy ; University of Luxembourg > Luxembourg Centre for Systems Biomedicine > Environmental Cheminformatics > Team Emma SCHYMANSKI
LAI, Adelene ; University of Luxembourg > Luxembourg Centre for Systems Biomedicine > Environmental Cheminformatics > Team Emma SCHYMANSKI ; Institute for Inorganic and Analytical Chemistry, Friedrich-Schiller University, Lessing Strasse 8, 07743, Jena, Germany
Taha, Hiba Mohammed ; Luxembourg Centre for Systems Biomedicine (LCSB), University of Luxembourg, 6 Avenue du Swing, 4367, Belvaux, Luxembourg
NARAYANAN, Mira ; University of Luxembourg > Luxembourg Centre for Systems Biomedicine > Environmental Cheminformatics > Team Emma SCHYMANSKI
Fonds National de la Recherche Luxembourg The European Union Research and Innovation program Horizon Europe for PARC
Funding text :
TK, AE, AL, HMT and ELS acknowledge funding support from the Luxembourg National Research Fund (FNR) for project A18/BM/12341006. AE and HMT also acknowledge funding support from the European Union Research and Innovation program Horizon Europe for PARC, Grant No. 101057014.
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