Spectral binning as an approach to post-acquisition processing of high resolution FIE-MS metabolome fingerprinting data

This is the code and analysis repository for the article:

Finch, J.P., Wilson, T., Lyons, L., Phillips, H., Beckmann, M. and Draper, J., 2022. Spectral binning as an approach to post-acquisition processing of high resolution FIE-MS metabolome fingerprinting data. Metabolomics, 18(8), pp.1-9.

All code is written in R and the drake package has been used for workflow management. The renv package has been used to ensure a reproducible R environment.

Compile the manuscript

Using docker

The manuscript can be compiled using a pre-built docker image, directly from GitHub:

docker run -v $(pwd):/home/rstudio/Spectral_binning_as_an_approach_to_post-acquisition_processing_of_FIE-HRMS_data ghcr.io/jasenfinch/spectral-binning:latest

Locally

To generate the manuscript, simply clone the repository, open the R console, set the working directory to the repository clone using setwd() and run the command drake::r_make().