A Python-Based Pipeline for Preprocessing LC–MS Data for Untargeted Metabolomics Workflows

Preprocessing data in a reproducible and robust way is one of the current challenges in untargeted metabolomics workflows. Data curation in liquid chromatography–mass spectrometry (LC–MS) involves the removal of biologically non-relevant features (retention time, m/z pairs) to retain only high-quali...

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Detalles Bibliográficos
Autores principales: Riquelme, Gabriel, Zabalegui, Nicolás, Marchi, Pablo, Jones, Christina M., Monge, María Eugenia
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2020
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7602939/
https://www.ncbi.nlm.nih.gov/pubmed/33081373
http://dx.doi.org/10.3390/metabo10100416

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7602939/
https://www.ncbi.nlm.nih.gov/pubmed/33081373
http://dx.doi.org/10.3390/metabo10100416

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