MargheRita: an R package for LC-MS/MS metabolomics data analysis and confident metabolite identification based on a spectral library of reference standards

Untargeted metabolomics studies by mass spectrometry technologies generate huge numbers of metabolite signals, requiring computational analyses for post-acquisition processing and dedicated databases for metabolite identification. Web-based data processing solutions frequently include only a part of the entire workflow thus implying the use of different platforms. The R package margheRita addresses the complete workflow for metabolomic profiling in untargeted studies based on liquid chromatography (LC) coupled with tandem mass spectrometry (MS/MS). This pipeline is specially advantageous in the case of data-independent acquisition (DIA), where all MS/MS spectra are acquired with high resolution. Interestingly, the R package margheRita enhances fragment matching accuracy by providing an original metabolite spectral library acquired in both polarities using different chromatographic columns. This R package provides a comprehensive solution for metabolomics, covering the entire analysis workflow from raw data processing to biological interpretation.

The package provides:

  • a series of pre-processing functions (quality control, filtering and normalization) with a particular focus on methods specifically recommended for metabolomic profiles, such as filtering by mass defects, filtering by coefficient of variation (samples vs QCs) and probabilistic quotient normalization;
  • metabolite annotation up to level-1, based on in-house spectral libraries as well as freely available libraries;
  • spectral libraries that covers 4 different chromatographic column types: RP-C18, HILIC, RP-C8 and pZIC-HILIC Zwitterionic.
  • simplified execution of parametric and non-parametric statistical tests over a large number of features;
  • pathway analysis based on ORA and MSEA over various databases.

Documentation: https://emosca-cnr.github.io/margheRita

Source code: https://github.com/emosca-cnr/margheRita

Citation: Ettore Mosca, Marynka Ulaszewska, Zahrasadat Alavikakhki, Edoardo Niccolò Bellini, Valeria Mannella, Gianfranco Frigerio, Denise Drago, Annapaola Andolfo. MargheRita: an R package for LC-MS/MS SWATH metabolomics data analysis and confident metabolite identification based on a spectral library of reference standards. bioRxiv 2024.06.20.599545; doi: https://doi.org/10.1101/2024.06.20.599545

Contacts:

Installation

See https://emosca-cnr.github.io/margheRita/articles/margheRita.html