Autor segons l'article: Rafols, Pere; Heijs, Bram; del Castillo, Esteban; Yanes, Oscar; McDonnell, Liam A; Brezmes, Jesus; Perez-Taboada, Iara; Vallejo, Mario; Garcia-Altares, Maria; Correig, Xavier
Departament: Enginyeria Electrònica, Elèctrica i Automàtica
Autor/s de la URV: Brezmes Llecha, Jesús Jorge / Correig Blanchar, Francesc Xavier / Del Castillo Pérez, Esteban / Garcia-Altares Pérez, Maria / Ràfols Soler, Pere / Yanes Torrado, Óscar
Paraules clau: Workflow; Software; Mass spectrometry; Computer systems; Algorithms
Resum: © The Author(s) 2020. Published by Oxford University Press. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com. SUMMARY: Mass spectrometry imaging (MSI) can reveal biochemical information directly from a tissue section. MSI generates a large quantity of complex spectral data which is still challenging to translate into relevant biochemical information. Here, we present rMSIproc, an open-source R package that implements a full data processing workflow for MSI experiments performed using TOF or FT-based mass spectrometers. The package provides a novel strategy for spectral alignment and recalibration, which allows to process multiple datasets simultaneously. This enables to perform a confident statistical analysis with multiple datasets from one or several experiments. rMSIproc is designed to work with files larger than the computer memory capacity and the algorithms are implemented using a multi-threading strategy. rMSIproc is a powerful tool able to take full advantage of modern computer systems to completely develop the whole MSI potential. AVAILABILITY AND IMPLEMENTATION: rMSIproc is freely available at https://github.com/prafols/rMSIproc. CONTACT: pere.rafols@urv.cat. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.
Àrees temàtiques: Statistics and probability; Statistics & probability; Odontología; Nutrição; Molecular biology; Medicina veterinaria; Medicina ii; Medicina i; Mathematics, interdisciplinary applications; Mathematical & computational biology; Matemática / probabilidade e estatística; Interdisciplinar; General medicine; Engenharias iv; Economia; Computer science, interdisciplinary applications; Computer science applications; Computational theory and mathematics; Computational mathematics; Ciências biológicas iii; Ciências biológicas ii; Ciências biológicas i; Ciências agrárias i; Ciência da computação; Biotecnología; Biotechnology & applied microbiology; Biology, miscellaneous; Biodiversidade; Biochemistry; Biochemical research methods; Astronomia / física
Accès a la llicència d'ús: https://creativecommons.org/licenses/by/3.0/es/
Adreça de correu electrònic de l'autor: oscar.yanes@urv.cat; maria.garcia-altares@urv.cat; pere.rafols@urv.cat; esteban.delcastillo@urv.cat; jesus.brezmes@urv.cat; xavier.correig@urv.cat
ISSN: 1367-4803
Data d'alta del registre: 2025-01-28
Pàgina final: 3619
Volum de revista: 36
Versió de l'article dipositat: info:eu-repo/semantics/acceptedVersion
Enllaç font original: https://academic.oup.com/bioinformatics/article-abstract/36/11/3618/5766117?redirectedFrom=fulltext
Referència a l'article segons font original: Bioinformatics. 36 (11): 3618-3619
Referència de l'ítem segons les normes APA: Rafols, Pere; Heijs, Bram; del Castillo, Esteban; Yanes, Oscar; McDonnell, Liam A; Brezmes, Jesus; Perez-Taboada, Iara; Vallejo, Mario; Garcia-Altares (2020). rMSIproc: an R package for mass spectrometry imaging data processing. Bioinformatics, 36(11), 3618-3619. DOI: 10.1093/bioinformatics/btaa142
URL Document de llicència: https://repositori.urv.cat/ca/proteccio-de-dades/
DOI de l'article: 10.1093/bioinformatics/btaa142
Entitat: Universitat Rovira i Virgili
Any de publicació de la revista: 2020
Pàgina inicial: 3618
Tipus de publicació: Journal Publications