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Install

2024-10-30

Source: vignettes/install_v0.qmd

For manual installation, an R version >= 4.4.0 is required.

Notes: only a development version of metabonaut is available as of now but a stable version will come soon. Therefore, if you are having difficulty to run some part of the code we strongly recommend to use the Docker image, as it will have all the package necessary to run all the analysis presented in these workflows.

Running workflows locally

To install on your computer all the packages necessary for the workflows run the code as follow:

install.packages("BiocManager")
BiocManager::install('RforMassSpectrometry/MsIO', ask = FALSE, 
                     dependencies = TRUE)

BiocManager::install("RforMassSpectrometry/metabonaut",
                     dependencies = TRUE, ask = FALSE, update = TRUE)

If you get some error message when downloading form GitHub it might be due to an expired token. Remove them using this code below and try to install again:

#See if any token is there:
gitcreds::gitcreds_get()

# Delete them:
gitcreds::gitcreds_delete()

Docker image

The vignettes 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 vignettes can be evaluated within this environment (without the need to install any additional packages or files).

  • 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 Quarto files in the vignettes folder and evaluate the R code blocks in that document.