In:
Metabolomics, Springer Science and Business Media LLC, Vol. 16, No. 9 ( 2020-09)
Kurzfassung:
Direct infusion untargeted mass spectrometry-based metabolomics allows for rapid insight into a sample’s metabolic activity. However, analysis is often complicated by the large array of detected m/z values and the difficulty to prioritize important m/z and simultaneously annotate their putative identities. To address this challenge, we developed MetaboShiny, a novel R/RShiny-based metabolomics package featuring data analysis, database- and formula-prediction-based annotation and visualization. To demonstrate this, we reproduce and further explore a MetaboLights metabolomics bioinformatics study on lung cancer patient urine samples. MetaboShiny enables rapid and rigorous analysis and interpretation of direct infusion untargeted mass spectrometry-based metabolomics data.
Materialart:
Online-Ressource
ISSN:
1573-3882
,
1573-3890
DOI:
10.1007/s11306-020-01717-8
Sprache:
Englisch
Verlag:
Springer Science and Business Media LLC
Publikationsdatum:
2020
ZDB Id:
2182289-X
