Exploring, visualising and analysing proteomics data in R

PrerequisitesNew

This course will present a set of R/Bioconductor packages to access, manipulate, visualise and analyse mass spectrometry (MS) and quantitative proteomics data.

The training room is located on the first floor and there is currently no wheelchair or level access available to this level.

Please note that if you are not eligible for a University of Cambridge Raven account you will need to book or register your interest by linking here.

• The course is targeted to either proteomics practitioners or data analysts/bioinformaticians that would like to learn how to use R to analyse proteomics data. Familiarity with mass spectrometry or proteomics in general is desirable, but not essential as we will walk through a MS typical experiment and data as part of learning about the tools.
• Graduate students, Postdocs and Staff members from the University of Cambridge, Affiliated Institutions and other external Institutions or individuals
• Please be aware that these courses are only free for registered University of Cambridge students. All other participants will be charged a registration fee in some form. Registration fees and further details regarding the charging policy are available here
• Further details regarding eligibility criteria are available here

• Participants need to have a working knowledge of R (R syntax, commonly used functions, basic data structures such as data frames, vectors, matrices, … and their manipulation).
• The Introduction to R for biologists course is suggested as a prerequisite to this course but not compulsory if you already have a working knowledge in R as mentioned above.
• Familiarity with other Bioconductor omics data classes and the tidyverse syntax is useful, but not required.

Number of sessions: 1

Bioinformatics, Biology, Data handling, Data visualisation, Proteomics

After this course you should be able to:

• Prepare/convert proteomics data for it to be analysed in R.
• Import MS experiments and extract, process and visualise parts all or thereof, such as for example plot the raw spectra for a protein of interest.
• Generate quantitative data or import data from third party software such as, for example, MaxQuant or Proteome Discoverer.
• Process and visualise and analyse quantitative data in R such as, for example, filter or impute missing values, produce heatmaps or PCA plots, normalise your data and run a statistical test.

During this course you will learn about:

• R/Bioconductor data structures for mass spectrometry data and proteomics data
• Accessing data from the public PRIDE repository
• Reading, manipulating and visualising raw data
• Reading, visualising and processing quantitative data
• Learn how the MS and proteomics R/Bioconductor infrastructure fits in the general Bioconductor ecosystem.

Presentations and practicals

• Free for registered University of Cambridge students
• £ 50/day for all University of Cambridge staff, including postdocs, temporary visitors (students and researchers) and participants from Affiliated Institutions. Please note that these charges are recovered by us at the Institutional level
• It remains the participant's responsibility to acquire prior approval from the relevant group leader, line manager or budget holder to attend the course. It is requested that people booking only do so with the agreement of the relevant party as costs will be charged back to your Lab Head or Group Supervisor.
• £ 50/day for all other academic participants from external Institutions and charitable organizations. These charges must be paid at registration
• £ 100/day for all Industry participants. These charges must be paid at registration
• Further details regarding the charging policy are available here

1

• Introduction to R for Biologists (IN-PERSON)
• CRUK: Data Carpentry in R