Autor segons l'article: Baquer, Gerard; Semente, Lluc; Garcia-Altares, Maria; Lee, Young Jin; Chaurand, Pierre; Correig, Xavier; Rafols, Pere
Departament: Enginyeria Electrònica, Elèctrica i Automàtica
e-ISSN: 1758-2946
Autor/s de la URV: Baquer Gómez, Gerard Sergi / Correig Blanchar, Francesc Xavier / Garcia-Altares Pérez, Maria / Ràfols Soler, Pere / Sementé Fernández, Lluc
Paraules clau: Spectral processing Spatial metabolomics Small-molecule analysis Silver-assisted laser/desorption ionization Resolution Overlapping-signal detection Ms Matrix annotation Mass spectrometry imaging Fingermarks Desorption-ionization
Resum: Mass spectrometry imaging (MSI) has become a mature, widespread analytical technique to perform non-targeted spatial metabolomics. However, the compounds used to promote desorption and ionization of the analyte during acquisition cause spectral interferences in the low mass range that hinder downstream data processing in metabolomics applications. Thus, it is advisable to annotate and remove matrix-related peaks to reduce the number of redundant and non-biologically-relevant variables in the dataset. We have developed rMSIcleanup, an open-source R package to annotate and remove signals from the matrix, according to the matrix chemical composition and the spatial distribution of its ions. To validate the annotation method, rMSIcleanup was challenged with several images acquired using silver-assisted laser desorption ionization MSI (AgLDI MSI). The algorithm was able to correctly classify m/z signals related to silver clusters. Visual exploration of the data using Principal Component Analysis (PCA) demonstrated that annotation and removal of matrix-related signals improved spectral data post-processing. The results highlight the need for including matrix-related peak annotation tools such as rMSIcleanup in MSI workflows.
Àrees temàtiques: 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
Accès a la llicència d'ús: https://creativecommons.org/licenses/by/3.0/es/
Adreça de correu electrònic de l'autor: maria.garcia-altares@urv.cat pere.rafols@urv.cat lluc.semente@estudiants.urv.cat lluc.semente@estudiants.urv.cat gerard.baquer@estudiants.urv.cat gerard.baquer@estudiants.urv.cat xavier.correig@urv.cat
Identificador de l'autor: 0000-0002-9240-4058 0000-0002-4433-4972 0000-0002-4433-4972 0000-0002-6902-3054
Data d'alta del registre: 2024-11-09
Versió de l'article dipositat: info:eu-repo/semantics/publishedVersion
Enllaç font original: https://jcheminf.biomedcentral.com/articles/10.1186/s13321-020-00449-0
URL Document de llicència: https://repositori.urv.cat/ca/proteccio-de-dades/
Referència a l'article segons font original: Journal Of Cheminformatics. 12 (1): 45-
Referència de l'ítem segons les normes APA: Baquer, Gerard; Semente, Lluc; Garcia-Altares, Maria; Lee, Young Jin; Chaurand, Pierre; Correig, Xavier; Rafols, Pere (2020). rMSIcleanup: an open-source tool for matrix-related peak annotation in mass spectrometry imaging and its application to silver-assisted laser desorption/ionization. Journal Of Cheminformatics, 12(1), 45-. DOI: 10.1186/s13321-020-00449-0
DOI de l'article: 10.1186/s13321-020-00449-0
Entitat: Universitat Rovira i Virgili
Any de publicació de la revista: 2020
Tipus de publicació: Journal Publications