ShinyMetID: An R shiny package for metabolite identification by mass spectral matching.

Area of Science:

• Analytical Chemistry
• Bioinformatics
• Metabolomics

Background:

• Metabolite identification is crucial for understanding biological pathways.
• Untargeted metabolomics generates complex datasets requiring robust analytical tools.
• Mass spectral matching is a common technique for metabolite identification.

Purpose of the Study:

• To present novel R Shiny software for metabolite identification.
• To provide an accessible tool for mass spectral matching in GC-MS untargeted metabolomics.
• To demonstrate the software's functionality with a graphical user interface and toy example.

Main Methods:

• Development of an R Shiny application.
• Implementation of various spectral similarity measures.
• Utilizing a graphical user interface for user interaction.
• Application to gas chromatography-mass spectrometry (GC-MS) data.

Main Results:

• A user-friendly software for metabolite identification was successfully developed.
• The software facilitates mass spectral matching for untargeted metabolomics data.
• A toy example demonstrates the graphical user interface and analytical capabilities.

Conclusions:

• The presented R Shiny software offers an accessible solution for metabolite identification.
• This tool can aid researchers in analyzing GC-MS based untargeted metabolomics data.
• The software simplifies the process of mass spectral matching, improving data interpretation.