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Mass Spectrometry Data Analysis with Spectra

License: CC BY-NC 4.0 docker pulls Docker Image Version (latest by date)

Tutorials and workshops for the use of the Spectra Bioconductor package to analyze mass spectrometry (MS) data.

Workshops/Tutorials

Seamless Integration of Mass Spectrometry Data from Different Sources

This tutorial (source: here) shows the use of different backends (extending the MsBackend class) to import and export mass spectrometry data from and to different file formats (and resources). As a simple use case, experimental MS/MS spectra are processed and cleaned, compared against reference spectra from a public database and finally exported.

Workshop goals and objectives

  • Understand the principles of different data backends.
  • Learn to handle and analyze mass spectrometry data with Spectra.

Pre-requisites

  • Basic knowledge of mass spectrometry data.
  • Basic knowledge of R.

Installation

To run the code of the tutorial locally a recent version of R is required (version >= 4.0) and a set of R/Bioconductor packages that can be installed with the code below:

install.packages(c("devtools", "rmarkdown", "BiocManager"))
BiocManager::install(c("BiocStyle",
                       "MsCoreUtils",
                       "Spectra",
                       "pheatmap"))
BiocManager::install("RforMassSpectrometry/MsBackendHmdb")
BiocManager::install("RforMassSpectrometry/MsBackendMgf")

Alternatively, a docker image with all necessary packages pre-installed is available here. This can be installed with docker pull jorainer/spectra_tutorials:latest.

To run the docker use:

docker run \
 	-e PASSWORD=bioc \
 	-p 8787:8787 \
 	jorainer/spectra_tutorials:latest

Interaction with the R within the running docker container is then possible by entering the address http://localhost:8787/ in a web browser and logging in with user rstudio password bioc. This gives access to a RStudio instance running within the container.