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R and Bioconductor for proteomics

Bioconductor

Bioconductor provides tools for the analysis and comprehension of high-throughput biology (genomics, proteomics, metabolomics, flow cytometry, ...) data. Bioconductor uses the R statistical programming language, and is open source and open development. It has two releases each year, 1295 software packages, and an active user community.

In addition to software package, it also has experiment and annotation packages.

Installing Bioconductor packages

First time

## try http:// if https:// URLs are not supported
source("https://bioconductor.org/biocLite.R")
biocLite("RforProteomics")

Then

library("BiocInstaller")
biocLite("RforProteomics")

To install all Bioconductor software that will be used throughout this workshop:

biocLite(c("RforProteomics", "pRolocGUI"), dependencies = TRUE)

See the detailed session information in the wrap up section for packages and versions used to generate this material.

Support

Some packages have GitHub pages and use GitHub issues. That would be a good place to report bugs. But the preferred place to ask questions is the support forum.

Proteomics and mass spectrometry

The easiest way to browser and search Bioconductor packages is to navigate task views.

Particularly relevant for this course are the mass spectrometry, mass spectrometry data and proteomics task views.

The RforProteomics package

The RforProteomics package contains code to illustrate the Using R and Bioconductor for proteomics data analysis and Visualisation of proteomics data using R and Bioconductor papers. Two vignettes describe the code and data needed to reproduce all the examples and figures.

library("RforProteomics")
## 
## This is the 'RforProteomics' version 1.11.2.
## 
##   To get started, visit
##     http://lgatto.github.com/RforProteomics/
## 
##   or, in R, open package vignettes by typing
##     RforProteomics() # R/Bioc for proteomics overview
##     RProtVis()       # R/Bioc for proteomics visualisation
## 
##   For a full list of available documents:
##     vignette(package='RforProteomics')

Package vignettes are overview package documentations. They generally provide a complete use case demonstrating the package's functionality. All Bioconductor software packages have vignettes in addition to all function manuals.

Package landing pages

Each Bioconductor package has an official page on the Bioconductor website:

  • http://www.bioconductor.org/packages/packageName

For example

These pages summarise general information about the package and provides links to its vignettes.

Proteomics/MS data structures

Data type File format Data structure Package
Raw mzXML or mzML mzRpwiz or mzRramp mzR
Raw mzXML or mzML list of MassSpectrum objects MALDIquantForeign
Raw mzXML or mzML MSnExp MSnbase
Identification mzIdentML mzRident mzR
Identification mzIdentML mzID mzID
Quantitative mzTab MSnSet MSnbase
Peak lists mgf MSnExp MSnbase
Imaging imzML or Analyze 7.5 MSImageSet Cardinal
Imaging imzML or Analyze 7.5 list of MassSpectrum objects MALDIquantForeign

References

Gatto L. and Christoforou A. Using R and Bioconductor for proteomics data analysis, Biochim Biophys Acta - Proteins and Proteomics, 2013. PMID:23692960(preprint)

Gatto L, Breckels LM, Naake T, Gibb S. Visualisation of proteomics data using R and Bioconductor. Proteomics. 2015 Feb 18. doi: 10.1002/pmic.201400392. PMID:25690415.