MetaboShiny: interactive analysis and metabolite annotation of mass spectrometry-based metabolomics data
Joanna C. Wolthuis, Stefanía Magnúsdóttir, Mia L. Pras‐Raves, Maryam Moshiri, Judith Jans, Boudewijn Burgering, Saskia W. C. van Mil, Jeroen de Ridder
Abstract
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.