Centre for Research Informatics Training
Expression proteomics analysis in R
Event details
Sessions
- 19 January 2027 — 09:30 to 17:30 — Craik-Marshall
- 20 January 2027 — 09:30 to 17:30 — Craik-Marshall
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About the course
Expression proteomics aims to characterise the diversity and abundance of proteins within a biological system. This workshop provides a practical introduction to the bioinformatic analysis of expression proteomics data using dedicated Bioconductor packages in R.
Participants will work with a real-world dataset generated from a tandem mass tag (TMT) mass spectrometry experiment. The course covers the core data structures used to store and manipulate protein abundance data, approaches for quality control and filtering, and methods for visualising and exploring proteomics datasets. Participants will also learn how to perform differential abundance analysis between sample groups and how to interpret results through gene ontology analysis.
By the end of the workshop, participants should be able to analyse expression proteomics datasets from data import through to biological interpretation.
Teaching is primarily hands-on, with short presentations introducing the concepts and methods needed to analyse expression proteomics data.
Intended audience
This course is suitable for:
- proteomics practitioners who want to analyse expression proteomics data in R
- data analysts and bioinformaticians interested in proteomics data analysis workflows
- researchers seeking practical experience with Bioconductor packages for proteomics analysis
- participants interested in analysing and interpreting quantitative mass spectrometry data
Familiarity with mass spectrometry or proteomics is desirable but not essential, as the course includes an introduction to typical mass spectrometry experiments and data.
Prerequisites
Participants should have:
- a basic understanding of mass spectrometry
- a working knowledge of R and the tidyverse
For an overview of mass spectrometry technologies, we recommend watching this iBiology video.
The following experience is useful but not required:
- familiarity with Bioconductor data classes, including those commonly used for RNA-seq analysis
Course fees
All fees are per full training day.
| Category | Fee |
|---|---|
| Industry full charge | £130.00 |
| Academic / Government / charity concessionary | £65.00 |
| Cambridge University staff members / postdocs / visitors | £65.00 |
| Cambridge University registered students | Free |
| Cambridge University registered students non-attendance | £22.00 |
| Special events | Per event |
Payment options will be provided in booking confirmation emails sent after registration.
General information
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