Exploring and analyzing LC-MS data

This walks through the preprocessing of a small data set emphasizing on selection of data-dependent settings for the individual preprocessing steps.

The full R code of all examples along with comprehensive descriptions is provided in the end-to-end-untargeted-metabolomics.Rmd file. This file can be opened with e.g. RStudio which allows execution of the individual R commands (see section below for additionally required R packages). The R command rmarkdown::render("xcms-preprocessing.Rmd") would generate the html file xcms-preprocessing.html.

Important to note

This tutorial expect a user that has some basic knowledge of R and Rmarkdown. We would advise to go through a short tutorial for each in order to be comfortable testing the code and easily adapting it to your own data. For Rmarkdown, click here for R, here

Installation

The workshop files along with an R runtime environment including all required packages and the RStudio (Posit) editor are all bundled in a docker container. After installation, this docker container can be run on the computer and the code and examples from the workshop can be evaluated within this environment (without the need to install any additional packages or files).

This version of the workshop uses packages from Bioconductor devel and hence bases on Bioconductor's docker container with the development version of the packages. A more stable version will come soon. The required steps for installation are:

• 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 rformassspectrometry/metabonaut:latest.
• Start the docker container, either through the Docker Desktop, or on the command line with

  docker run \
      -e PASSWORD=bioc \
      -p 8787:8787 \
      rformassspectrometry/metabonaut: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 R-markdown (.Rmd) files in the vignettes folder and evaluate the R code blocks in that document.

For manual installation, an R version >= 4.4.0 is required as well as recent versions of the packages used in the workflow.

For now 2 packages used in this workflow are not on bioconductor and therefore need to be downloaded from github. Run the code as follow:

install.packages("BiocManager")
BiocManager::install("RforMassSpectrometry/MsBackendMetaboLights", dependencies = TRUE)
BiocManager::install("RforMassSpectrometry/MsIO", dependencies = TRUE)

Known issues

This workflow is still getting ready to be fully deployed, therefore we have some ongoing issue that we are actively resolving.

• The chunks between the Line 414 to 453 are not being rendered and should not be rendered as we are having some issue with the backend.

If you have any other issue, do not hesitate to report them to us.

Contribution

For contributions, see the RforMassSpectrometry contributions guideline.

Code of Conduct

See the RforMassSpectrometry Code of Conduct.