Autor según el artículo: Brezmes, J.; Domingo-Almenara, X.; Venturini, G.; Vivó-Truyols, G.; Perera, A.; Vinaixa, M.
Departamento: Enginyeria Electrònica, Elèctrica i Automàtica
Autor/es de la URV: BREZMES LLECHA, JESÚS JORGE; Domingo-Almenara, X.; Venturini, G.; Vivó-Truyols, G.; Perera, A.; VINAIXA CREVILLENT, MARIA
Palabras clave: metabolomics mass spectrometry Gas Chromatography
Resumen: Introduction: Current computational tools for gas chromatography—mass spectrometry (GC–MS) metabolomics profiling do not focus on metabolite identification, that still remains as the entire workflow bottleneck and it relies on manual data reviewing. Metabolomics advent has fostered the development of public metabolite repositories containing mass spectra and retention indices, two orthogonal properties needed for metabolite identification. Such libraries can be used for library-driven compound profiling of large datasets produced in metabolomics, a complementary approach to current GC–MS non-targeted data analysis solutions that can eventually help to assess metabolite identities more efficiently. Results: This paper introduces Baitmet, an integrated open-source computational tool written in R enclosing a complete workflow to perform high-throughput library-driven GC–MS profiling in complex samples. Baitmet capabilities were assayed in a metabolomics study involving 182 human serum samples where a set of 61 metabolites were profiled given a reference library. Conclusions: Baitmet allows high-throughput and wide scope interrogation on the metabolic composition of complex samples analyzed using GC–MS via freely available spectral data. Baitmet is freely available at http://CRAN.R-project.org/package=baitmet.
Grupo de investigación: Signal Processing for Omic Sciences
Áreas temáticas: Electronic engineering Ingeniería electrónica Enginyeria electrònica
Acceso a la licencia de uso: https://creativecommons.org/licenses/by/3.0/es/
ISSN: 1573-3882
Identificador del autor: 0000-0002-7704-8550; ; ; ; ; 0000-0001-9804-0171
Fecha de alta del registro: 2017-10-23
Volumen de revista: 13
Versión del articulo depositado: info:eu-repo/semantics/acceptedVersion
Programa de financiación: altres; Fundação de Amparo à Pesquisa do Estado de São Paulo; FAPESP; 2012/12042-7 plan; MINECO Grant; SEIDI; TEC2015¿69076-P plan; MINECO Grant; SEIDI; TEC2014¿60337-R
URL Documento de licencia: https://repositori.urv.cat/ca/proteccio-de-dades/
Entidad: Universitat Rovira i Virgili
Año de publicación de la revista: 2017
Página inicial: 93
Tipo de publicación: Article Artículo Article
Repositori URV