This lesson is still being designed and assembled (Pre-Alpha version)

Proteomics data analysis with QFeatures

Mass spectrometry-based quantitative proteomics data can be representated as a matrix of quantitative values for features (PSMs, peptides, proteins) arranged along the rows, measured for a set of samples, arranged along the columns. The SummarizedExperiment and MultiAssayExperiment classes (Morgan et al. 2020) can handle such data. QFeatures is derived from MultiAssayExperiment.


This lesson assumes a working understanding of R.

This lesson assumes familiarity with proteomics data analysis.

The course is targeted to proteomics practitioners that would like to learn how to use R to analyse proteomics data.

Things You Need To Know

  1. Don’t panic.
  2. Everything is going to be fine.
  3. We are learning together.


Setup Download files required for the lesson
00:00 1. Introduction to quantitative proteomics data What data do we have?
What analyses can we apply?
How can we check the data throughout the analysis?
00:15 2. Identifying the anatomy of SummarizedExperiment and QFeatures objects How do SummarizedExperiment and QFeatures objects look like?
01:05 3. Importing txt into Qfeatures How can we import txt file into QFeatures object?
How can we add metadata to QFeatures?
How can we inspect QFeatures features?
01:20 Finish

The actual schedule may vary slightly depending on the topics and exercises chosen by the instructor.