Skip to contents

Let’s Explore and Learn to Analyze Untargeted Metabolomics Data

License: CC BY-NC 4.0
DOI

Welcome to Metabonaut! 🚀

Metabonaut presents a series of workflows based on a small LC-MS/MS dataset, utilizing R and Bioconductor packages. These workflows demonstrate how to adapt various algorithms to specific datasets and seamlessly integrate R packages for efficient, reproducible data processing.

Available Vignettes

1. Complete End-to-End LC-MS/MS Metabolomic Data Analysis

This primary workflow guides you through each step of the analysis, from preprocessing raw data to statistical analysis and metabolite annotation.
📄 Full R code: end-to-end-untargeted-metabolomics.qmd

2. Dataset Investigation

Before diving into the analysis, learn about key aspects to examine in your dataset to ensure smooth processing and avoid troubleshooting later.

3. Seamless Alignment: Merging New Data with an Existing Preprocessed Dataset

Discover how to use a flexible alignment algorithm to integrate new datasets with previously processed ones based on features of interest.

4. LC-MS/MS Data Annotation using R and Python

Explore the SpectriPy package for LC-MS/MS data annotation. This tutorial demonstrates how to combining the strengths of Python and R MS libraries for annotation.

For a full list of all available vignettes, visit the Metabonaut website.

📌 Reproducibility & Updates

We strive for reproducibility. These workflows are designed to remain stable over time, allowing you to run all vignettes together as one comprehensive super-vignette.

  • Major updates will be documented here.
  • Minor updates can be found in the News section.

🎓 For R Beginners

The tutorials assume basic knowledge of R and RMarkdown. If you’re new to these, we recommend starting with a short tutorial before running the vignettes.

🛠️ Known Issues

This is just the beginning of our Metabonaut journey, and we’re actively refining the website. If you’re experiencing any issues:

✅ Ensure you have the latest versions of all required packages.
🐛 If the issue persists, report it with a reproducible example on GitHub Issues.

Currently, there are no known issues with the code.

🤝 Contribution

Interested in contributing? Please check out the RforMassSpectrometry Contributions Guide.

📜 Code of Conduct

We follow the RforMassSpectrometry Code of Conduct to maintain an inclusive and respectful community.

🙌 Acknowledgements

EU Logo
EU Logo

This work is funded by the European Union under the HORIZON-MSCA-2021 project 101073062: HUMAN – Harmonising and Unifying Blood Metabolic Analysis Networks.

🔗 Learn more: HUMAN Project Website