Chapter 1 Preamble

Targeted audience and assumed background

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The course material is targeted to either proteomics practitioners or data analysts/bioinformaticians that would like to learn how to use R and Bioconductor to analyse proteomics data. Familiarity with MS or proteomics in general is desirable, but not essential as we will walk through and describe a typical MS data as part of learning about the tools. For approachable introductions to sample preparation, mass spectrometry, data interpretation and analysis, readers are redirected to:

• A beginner’s guide to mass spectrometry–based proteomics (Sinha and Mann ⊕2020Sinha, Ankit, and Matthias Mann. 2020. “A beginner’s guide to mass spectrometry–based proteomics.” The Biochemist, September. https://doi.org/10.1042/BIO20200057.)
• The ABC’s (and XYZ’s) of peptide sequencing (Steen and Mann ⊕2004Steen, Hanno, and Matthias Mann. 2004. “The ABC’s (and XYZ’s) of Peptide Sequencing.” Nat. Rev. Mol. Cell Biol. 5 (9): 699–711.)
• How do shotgun proteomics algorithms identify proteins? (Marcotte ⊕2007Marcotte, Edward M. 2007. “How Do Shotgun Proteomics Algorithms Identify Proteins?” Nat. Biotechnol. 25 (7): 755–57.)
• An Introduction to Mass Spectrometry-Based Proteomics (Shuken ⊕2023Shuken, Steven R. 2023. “An Introduction to Mass Spectrometry-Based Proteomics.” J. Proteome Res., June.)

A working knowledge of R (R syntax, commonly used functions, basic data structures such as data frames, vectors, matrices, … and their manipulation) is required. Familiarity with other Bioconductor omics data classes and the tidyverse syntax is useful, but not necessary.

Setup

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This material uses the latest version of the R for Mass Spectrometry package and their dependencies. It might thus be possible that even the latest Bioconductor stable version isn’t recent enough.

To install all the necessary package, please use the latest release of R and execute:

if (!requireNamespace("BiocManager", quietly = TRUE))
    install.packages("BiocManager")

BiocManager::install("tidyverse")
BiocManager::install("factoextra")
BiocManager::install("msdata")
BiocManager::install("mzR")
BiocManager::install("rhdf5")
BiocManager::install("rpx")
BiocManager::install("MsCoreUtils")
BiocManager::install("QFeatures")
BiocManager::install("Spectra")
BiocManager::install("ProtGenerics")
BiocManager::install("PSMatch")
BiocManager::install("pheatmap")
BiocManager::install("limma")
BiocManager::install("MSnID")
BiocManager::install("RforMassSpectrometry/SpectraVis")

Follow the instructions in this script to install the packages and download some of the data used in the following chapters. All software versions used to generate this document are recoded at the end of the book in 7.

To compile and render the teaching material, you will also need the BiocStyle package and the (slighly modified) Modern Statistics for Model Biology (msmb) HTML Book Style by Mike Smith:

BiocManager::install(c("bookdown", "BiocStyle", "lgatto/msmbstyle"))

Run the installation script by executing the line below to install all requirements to compile the book:

source("https://raw.githubusercontent.com/rformassspectrometry/book/main/install_docs_deps.R")

Acknowledgments

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Thank you to Charlotte Soneson for fixing many typos in a previous version of this book.

License

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This material is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License. You are free to share (copy and redistribute the material in any medium or format) and adapt (remix, transform, and build upon the material) for any purpose, even commercially, as long as you give appropriate credit and distribute your contributions under the same license as the original.