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Grant support

The authors acknowledge the financial support of the Spanish Ministry of Economy and Competitivity through the project RTI2018096061-B-100. GB acknowledges the financial support of the European Union's Horizon 2020 research and innovation program under the Marie Sklodowska-Curie grant Agreement No. 713679 and the Universitat Rovira i Virgili (URV). LS acknowledges the financial support of Universitat Rovira i Virgili through the pre-doctoral grant 2017PMF-PIPF-60. MGA acknowledges the financial support from the Agency for Management of University and Research Grants of the Generalitat de Catalunya (AGAUR) through the postdoctoral grant 2018 BP 00188.

Analysis of institutional authors

Garcia-Altares, MAuthor

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December 19, 2023
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rMSIfragment: improving MALDI-MSI lipidomics through automated in-source fragment annotation

Publicated to:Journal Of Cheminformatics. 15 (1): 80- - 2023-09-15 15(1), DOI: 10.1186/s13321-023-00756-2

Authors: Baquer, Gerard; Semente, Lluc; Rafols, Pere; Martin-Saiz, Lucia; Bookmeyer, Christoph; Fernandez, Jose A; Correig, Xavier; Garcia-Altares, Maria

Affiliations

Inst Invest Sanit Pere Virgili, Tarragona, Spain - Author
Spanish Biomed Res Ctr Diabet & Associated Metab D, Madrid, Spain - Author
Univ Basque Country UPV EHU, Fac Sci & Technol, Dept Phys Chem, Leioa, Spain - Author
Univ Munster, Inst Hyg, Munster, Germany - Author
Univ Rovira I Virgili, Dept Elect Engn, Tarragona, Spain - Author
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Abstract

Matrix-Assisted Laser Desorption Ionization Mass Spectrometry Imaging (MALDI-MSI) spatially resolves the chemical composition of tissues. Lipids are of particular interest, as they influence important biological processes in health and disease. However, the identification of lipids in MALDI-MSI remains a challenge due to the lack of chromatographic separation or untargeted tandem mass spectrometry. Recent studies have proposed the use of MALDI in-source fragmentation to infer structural information and aid identification. Here we present rMSIfragment, an open-source R package that exploits known adducts and fragmentation pathways to confidently annotate lipids in MALDI-MSI. The annotations are ranked using a novel score that demonstrates an area under the curve of 0.7 in ROC analyses using HPLC-MS and Target-Decoy validations. rMSIfragment applies to multiple MALDI-MSI sample types and experimental setups. Finally, we demonstrate that overlooking in-source fragments increases the number of incorrect annotations. Annotation workflows should consider in-source fragmentation tools such as rMSIfragment to increase annotation confidence and reduce the number of false positives.

Keywords

AnnotationBasicsBioinformaticsCheminformaticsComputationIn-source decayIn-source fragmentationLipidsMaldiMass spectrometry imagingMass-spectrometrySource decay

Quality index

Bibliometric impact. Analysis of the contribution and dissemination channel

The work has been published in the journal Journal Of Cheminformatics due to its progression and the good impact it has achieved in recent years, according to the agency WoS (JCR), it has become a reference in its field. In the year of publication of the work, 2023, it was in position 19/250, thus managing to position itself as a Q1 (Primer Cuartil), in the category Computer Science, Information Systems. Notably, the journal is positioned above the 90th percentile.

From a relative perspective, and based on the normalized impact indicator calculated from the Field Citation Ratio (FCR) of the Dimensions source, it yields a value of: 2.14, which indicates that, compared to works in the same discipline and in the same year of publication, it ranks as a work cited above average. (source consulted: Dimensions Jul 2025)

Specifically, and according to different indexing agencies, this work has accumulated citations as of 2025-07-16, the following number of citations:

  • WoS: 4
  • Google Scholar: 3

Impact and social visibility

From the perspective of influence or social adoption, and based on metrics associated with mentions and interactions provided by agencies specializing in calculating the so-called "Alternative or Social Metrics," we can highlight as of 2025-07-16:

  • The use, from an academic perspective evidenced by the Altmetric agency indicator referring to aggregations made by the personal bibliographic manager Mendeley, gives us a total of: 24.
  • The use of this contribution in bookmarks, code forks, additions to favorite lists for recurrent reading, as well as general views, indicates that someone is using the publication as a basis for their current work. This may be a notable indicator of future more formal and academic citations. This claim is supported by the result of the "Capture" indicator, which yields a total of: 26 (PlumX).

With a more dissemination-oriented intent and targeting more general audiences, we can observe other more global scores such as:

  • The Total Score from Altmetric: 4.45.
  • The number of mentions on the social network X (formerly Twitter): 8 (Altmetric).

It is essential to present evidence supporting full alignment with institutional principles and guidelines on Open Science and the Conservation and Dissemination of Intellectual Heritage. A clear example of this is:

  • The work has been submitted to a journal whose editorial policy allows open Open Access publication.

Leadership analysis of institutional authors

This work has been carried out with international collaboration, specifically with researchers from: Germany.

There is a significant leadership presence as some of the institution’s authors appear as the first or last signer, detailed as follows: Last Author (GARCIA ALTARES PEREZ, MARIA).