Articles producció científica> Enginyeria Electrònica, Elèctrica i Automàtica

rMSIfragment: improving MALDI-MSI lipidomics through automated in-source fragment annotation

  • Identification data

    Identifier: imarina:9329938
  • Authors:

    Baquer G
    Sementé L
    Ràfols P
    Martín-Saiz L
    Bookmeyer C
    Fernández JA
    Correig X
    García-Altares M
  • Others:

    Author, as appears in the article.: Baquer G; Sementé L; Ràfols P; Martín-Saiz L; Bookmeyer C; Fernández JA; Correig X; García-Altares M
    Department: Enginyeria Electrònica, Elèctrica i Automàtica
    URV's Author/s: Correig Blanchar, Francesc Xavier / Ràfols Soler, Pere
    Keywords: Mass spectrometry imaging Maldi Lipids In-source fragmentation In-source decay Computation Cheminformatics Bioinformatics Annotation
    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.© 2023. Springer Nature Switzerland AG.
    Thematic Areas: Química Physical and theoretical chemistry Library and information sciences Computer science, interdisciplinary applications Computer science, information systems Computer science applications Computer graphics and computer-aided design Ciencias sociales Chemistry, multidisciplinary Biotecnología
    licence for use: https://creativecommons.org/licenses/by/3.0/es/
    Author's mail: pere.rafols@urv.cat xavier.correig@urv.cat
    Author identifier: 0000-0002-9240-4058 0000-0002-6902-3054
    Record's date: 2023-11-11
    Papper version: info:eu-repo/semantics/publishedVersion
    Link to the original source: https://jcheminf.biomedcentral.com/articles/10.1186/s13321-023-00756-2
    Licence document URL: http://repositori.urv.cat/ca/proteccio-de-dades/
    Papper original source: Journal Of Cheminformatics. 15 (1): 80-80
    APA: Baquer G; Sementé L; Ràfols P; Martín-Saiz L; Bookmeyer C; Fernández JA; Correig X; García-Altares M (2023). rMSIfragment: improving MALDI-MSI lipidomics through automated in-source fragment annotation. Journal Of Cheminformatics, 15(1), 80-80. DOI: 10.1186/s13321-023-00756-2
    Article's DOI: 10.1186/s13321-023-00756-2
    Entity: Universitat Rovira i Virgili
    Journal publication year: 2023
    Publication Type: Journal Publications
  • Keywords:

    Chemistry, Multidisciplinary,Computer Graphics and Computer-Aided Design,Computer Science Applications,Computer Science, Information Systems,Computer Science, Interdisciplinary Applications,Library and Information Sciences,Physical and Theoretical Chemistry
    Mass spectrometry imaging
    Maldi
    Lipids
    In-source fragmentation
    In-source decay
    Computation
    Cheminformatics
    Bioinformatics
    Annotation
    Química
    Physical and theoretical chemistry
    Library and information sciences
    Computer science, interdisciplinary applications
    Computer science, information systems
    Computer science applications
    Computer graphics and computer-aided design
    Ciencias sociales
    Chemistry, multidisciplinary
    Biotecnología
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