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xcms-based LC-MS/MS data preprocessing for FBMN with GNPS2

License: CC BY-NC 4.0
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This repository contains an example workflow for preprocessing and preparation of an LC-MS/MS data set for feature-based molecular networking (FBMN) with GNPS2.

Analysis workflow

xcms-based preprocessing for FBMS with GNPS

This workflow explains preprocessing of a public LC-MS/MS data set with xcms and export of the results for feature-based molecular networking with GNPS.

🎥 a video recording of a presentation of this workshop is available at https://youtu.be/yc6fsegFg-k.

📌 Reproducibility & Usage

The workflow is available as pre-rendered webpage xcms4gnps. In addition, a docker image is available allowing to run the workflow interactively:

  • If you don’t already have, install docker. Find installation information here.
  • Get the docker image of this tutorial e.g. from the command line with:
docker pull jorainer/xcms4gnps2:latest
  • Start the docker container, either through the Docker Desktop, or on the command line with
docker run -e PASSWORD=bioc -p 8787:8787 jorainer/xcms4gnps2:latest
  • Enter http://localhost:8787 in a web browser and log in with username rstudio and password bioc.
  • In the RStudio server version: open any of the Quarto files in the vignettes folder and evaluate the R code blocks in that document.

ℹ️ macOS users might need to emulate an AMD64 CPU to run the docker image:

docker pull --platform linux/amd64 jorainer/xcms4gnps2:latest
docker run --platform linux/amd64 -e PASSWORD=bioc -p 8787:8787 jorainer/xcms4gnps2:latest

As an alternative to the docker-based workshop, it is also be possible to run and evaluate the workshop natively in a local R installation (R version >= 4.6):

#' install the workshop and all required dependencies
install.packages(c("BiocManager", "remotes"))
BiocManager::install("jorainer/xcms4gnps2", dependencies = TRUE)
BiocManager::install("RforMassSpectrometry/MsBackendMassIVE")

The vignettes/MSV000090156-preprocessing.qmd file could then be opened with any editor (after downloading locally) and the individual code lines evaluated in an R session.

🤝 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

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EU Logo

Part of 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