Skip to content

Workshop illustrating mass spectrometry data analysis in R and use of the updated xcms functionality for the preprocessing of LC-MS data.

Notifications You must be signed in to change notification settings

jorainer/metabolomics2018

Repository files navigation

DOI

  • 2021-03-25: provide a description on the good practice to define a phenodata/data files table containing also the names of the raw data files along with all sample information.
  • 2020-06-15: use new more data-driven gap-filling approach: fillChromPeaks with ChromPeakAreaParam.
  • 2020-02-04: add refineChromPeaks to allow refinement of peak detection results. Also, add the quantify method to extract the preprocessing results as SummarizedExperiment. Both required xcms version >= 2.9.2.
  • 2019-09-29: More updates and expansion of descriptions.
  • 2019-06-20: Updated to match xcms functionality available with Bioconductor version 3.9.

LC-MS data pre-processing with xcms

This workshop provides an overview of recent developments in Bioconductor to work with mass spectrometry (MSnbase) and specifically LC-MS data (xcms) and walks through the preprocessing of a toy data set emphasizing on selection of data-dependent settings for the individual pre-processing steps. The present workshop represents an updated version of the workshop given at the Metabolomics Society conference 2018 in Seattle (http://metabolomics2018.org).

Covered topics are:

  • Data import and representation.
  • Accessing, subsetting and visualizing data.
  • Centroiding of profile MS data.
  • Chromatographic peak detection.
  • Empirically determine appropriate settings for the analyzed data set.
  • Evaluation of identified peaks.
  • Alignment (retention time correction).
  • Correspondence (grouping of chromatographic peaks across samples).

The full R code of all examples along with comprehensive descriptions is provided in the xcms-preprocessing.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.

For those that can not attend the workshop: you can have a look at the presentation online xcms-preprocessing-ioslides.html.

Prerequisites

The analysis in this document requires an R version >= 3.6.0 and recent versions of the MSnbase and xcms (version >= 3.3.1 is needed) packages. The code below installs all packages for the analysis.

install("BiocManager")
BiocManager::install(c("xcms",
                       "MSnbase",
                       "msdata",
                       "magrittr",
                       "devtools",
                       "BiocParallel"))

Files

  • xcms-preprocessing.Rmd: file containing the complete R code and expanded description. Can be converted to a html file with rmarkdown::render("xcms-preprocessing.Rmd").

  • xcms-preprocessing-ioslides.Rmd: R markdown file that is rendered (with rmarkdown::render("xcms-preprocessing-ioslides.Rmd") into the html (ioslides-based) presentation for the conference. This file contains most of the R commands from xcms-preprocessing.Rmd but only few descriptions. (outdated!)

  • xcms-preprocessing-bullets.Rmd: file with complete R code but strongly reduced descriptive content (in form of bullet points). This file is thought to be used for an interactive presentation with RStudio (i.e. live execution of commands). (outdated!)

About

Workshop illustrating mass spectrometry data analysis in R and use of the updated xcms functionality for the preprocessing of LC-MS data.

Resources

Stars

Watchers

Forks

Releases

No releases published

Packages

No packages published

Languages