The QFeatures package provides infrastructure (that is classes to store data and the methods to process and manipulate them) to manage and analyse quantitative features from mass spectrometry experiments. It is based on the SummarizedExperiment and MultiAssayExperiment Bioconductor classes. Assays in a QFeatures object have a hierarchical relation: proteins are composed of peptides, themselves produced by spectra. Throughout the aggregation and processing of these data, the relations between assays are tracked and recorded, thus allowing users to easily navigate across spectra, peptide and protein quantitative data. In this workshop, we will demonstrate how to import data as QFeatures objects, how to process and analyse data in QFeatures objects, and how to interpret the results. Some familiarity with Bioconductor data analysis, in particular the SummarizedExperiment class, is recommended to follow this short workshop.

The content of this workshop is provided under a CC-BY ShareAlike license.


To cite package 'QFeaturesWorkshop2020' in publications use:

  Laurent Gatto (2020). QFeaturesWorkshop2020: QFeatures EuroBioc2020
  Workshop. R package version 0.2.1.
  https://github.com/lgatto/QFeaturesWorkshop2020

A BibTeX entry for LaTeX users is

  @Manual{,
    title = {QFeaturesWorkshop2020: QFeatures EuroBioc2020 Workshop},
    author = {Laurent Gatto},
    year = {2020},
    note = {R package version 0.2.1},
    url = {https://github.com/lgatto/QFeaturesWorkshop2020},
  }

Running the workshop

You can install all necessary packages to run the workshop locally by installing the following packages:

## general
install.packages("tidyverse")
install.packages("patchwork")
install.packages("factoextra")


## Bioconductor packages
if (!requireNamespace("BiocManager", quietly = TRUE))
    install.packages("BiocManager")
BiocManager::install("QFeatures")
BiocManager::install("msdata")
BiocManager::install("limma")

The lgatto/qfeaturesworkshop2020 docker container has all packages necessary for running the workshop vignettes.

The container can be downloaded and run with

docker run -e PASSWORD=bioc -p 8787:8787 lgatto/qfeaturesworkshop2020:latest

(you can choose any passwork, not only bioc, above)

Once running, navigate to https://localhost:8787/ and then login with user rstudio and password bioc.

During the EuroBioc2020 conference, the workshop can be run in the cloud.