ArticleJournal of cheminformatics2025
Shinyscreen: mass spectrometry data inspection and quality checking utility.
Article in Journal of cheminformatics, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
2 citing papers in PubMed.
- pyMSscreen: an interactive interface for automated quality control and prescreening in mass spectrometry workflows.Journal of cheminformatics · 2026Article
- Adding open spectral data to MassBank and PubChem using open source tools to support non-targeted exposomics of mixtures.Environmental science. Processes & impacts · 2023Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
7 authors.
Funding
Abstract
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.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.