Author, as appears in the article.: Rainer J; Vicini A; Salzer L; Stanstrup J; Badia JM; Neumann S; Stravs MA; Hernandes VV; Gatto L; Gibb S; Witting M
Department: Enginyeria Electrònica, Elèctrica i Automàtica
URV's Author/s: Badia Aparicio, José María
Keywords: Untargeted analysis Tandem mass-spectra Small-compound databases Reproducible research R programming Metabolomics Annotation untargeted analysis tool small-compound databases search reproducible research r programming fragmentation annotation
Abstract: Liquid chromatography-mass spectrometry (LC-MS)-based untargeted metabolomics experiments have become increasingly popular because of the wide range of metabolites that can be analyzed and the possibility to measure novel compounds. LC-MS instrumentation and analysis conditions can differ substantially among laboratories and experiments, thus resulting in non-standardized datasets demanding customized annotation workflows. We present an ecosystem of R packages, centered around the MetaboCoreUtils, MetaboAnnotation and CompoundDb packages that together provide a modular infrastructure for the annotation of untargeted metabolomics data. Initial annotation can be performed based on MS1 properties such as m/z and retention times, followed by an MS2-based annotation in which experimental fragment spectra are compared against a reference library. Such reference databases can be created and managed with the CompoundDb package. The ecosystem supports data from a variety of formats, including, but not limited to, MSP, MGF, mzML, mzXML, netCDF as well as MassBank text files and SQL databases. Through its highly customizable functionality, the presented infrastructure allows to build reproducible annotation workflows tailored for and adapted to most untargeted LC-MS-based datasets. All core functionality, which supports base R data types, is exported, also facilitating its re-use in other R packages. Finally, all packages are thoroughly unit-tested and documented and are available on GitHub and through Bioconductor.
Thematic Areas: Molecular biology Medicina ii Farmacia Endocrinology, diabetes and metabolism Ciências biológicas ii Ciências biológicas i Biotecnología Biochemistry & molecular biology Biochemistry
licence for use: https://creativecommons.org/licenses/by/3.0/es/
Author's mail: josepmaria.badia@urv.cat josepmaria.badia@urv.cat josepmaria.badia@urv.cat
Record's date: 2024-09-07
Papper version: info:eu-repo/semantics/publishedVersion
Link to the original source: https://www.mdpi.com/2218-1989/12/2/173
Licence document URL: https://repositori.urv.cat/ca/proteccio-de-dades/
Papper original source: Metabolites. 12 (2):
APA: Rainer J; Vicini A; Salzer L; Stanstrup J; Badia JM; Neumann S; Stravs MA; Hernandes VV; Gatto L; Gibb S; Witting M (2022). A Modular and Expandable Ecosystem for Metabolomics Data Annotation in R. Metabolites, 12(2), -. DOI: 10.3390/metabo12020173
Article's DOI: 10.3390/metabo12020173
Entity: Universitat Rovira i Virgili
Journal publication year: 2022
Publication Type: Journal Publications