MSIpixel: a fully automated pipeline for compound annotation and quantitation in mass spectrometry imaging experiments.
MSIpixel
annotations
mass spectrometry imaging
metabolomics
Journal
Briefings in bioinformatics
ISSN: 1477-4054
Titre abrégé: Brief Bioinform
Pays: England
ID NLM: 100912837
Informations de publication
Date de publication:
22 Nov 2023
22 Nov 2023
Historique:
received:
23
06
2023
revised:
13
10
2023
accepted:
22
11
2023
medline:
16
12
2023
pubmed:
16
12
2023
entrez:
15
12
2023
Statut:
ppublish
Résumé
Mass spectrometry imaging (MSI) is commonly used to map the spatial distribution of small molecules within complex biological matrices. One of the major challenges in imaging MS-based spatial metabolomics is molecular identification and metabolite annotation, to address this limitation, annotation is often complemented with parallel bulk LC-MS2-based metabolomics to confirm and validate identifications. Here we applied MSI method, utilizing data-dependent acquisition, to visualize and identify unknown molecules in a single instrument run. To reach this aim we developed MSIpixel, a fully automated pipeline for compound annotation and quantitation in MSI experiments. It overcomes challenges in molecular identification, and improving reliability and comprehensiveness in MSI-based spatial metabolomics.
Identifiants
pubmed: 38102070
pii: 7473608
doi: 10.1093/bib/bbad463
pii:
doi:
Types de publication
Journal Article
Langues
eng
Sous-ensembles de citation
IM
Subventions
Organisme : IRCCS Humanitas Research Hospital Metabolomics
Informations de copyright
© The Author(s) 2023. Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oup.com.