ReviewMetabolomics : Official journal of the Metabolomic Society2026
Metabonaut: an open educational resource for learning reproducible, script-based untargeted LC-MS/MS metabolomics.
Review in Metabolomics : Official journal of the Metabolomic Society, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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
0 citing papers in PubMed.
No citing paper in PubMed yet.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
10 authors.
Funding
Abstract
backgroundTwo decades after the Metabolomics Standards Initiative, public deposition of raw LC-MS/MS data into archives such as MetaboLights, Metabolomics Workbench, GNPS and MassBank has matured, but the analyses that turn raw files into reported feature tables remain difficult to share, audit and reuse. The FAIR principles, originally formulated for data, later extended to research software and to workflows, make a strong case that this gap matters; we adopt that view and ask how an educational resource can help researchers cross it. AIM OF REVIEW: This is an educational review where we describe the principles of FAIR and reproducible analysis as they apply to untargeted LC-MS metabolomics, and we show how those principles are realised in Metabonaut, an open educational resource built on top of the R for Mass Spectrometry/Bioconductor ecosystem. Metabonaut provides executable example workflows from raw mzML files to annotated feature tables, demonstrates interoperability across programming languages, and is built with and for the community. KEY SCIENTIFIC CONCEPTS OF REVIEW: After a brief tour of the underlying software ecosystem and of literate programming, the review discusses three topics, each through one or more Metabonaut vignettes: visual inspection and quality control, reuse of public archives at scale, and cross-language interoperability. Together, they teach how to carry FAIR practice from data to analysis: making the analysis itself, and not only the data it consumes, shareable, auditable and reusable. The source code of Metabonaut and links to pre-rendered workflow documents are available at https://github.com/RforMassSpectrometry/Metabonaut .
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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.