• Crash Course in Prostate Bioinformatics
• University of Oxford
• 18th -20th February 2019 09:30 - 17:00

• Processing of (bulk) rna-seq data using R
  • short single-cell teaser at end
• Survival Analysis
• Quality assessment, differential expression and visualisation
• Using DESeq2 workflow
  • other popular tools available
• Assuming that samples have already been aligned and counted
  • and experiment was appropriately-designed
• Materials to be shared online
  • https://sbc.shef.ac.uk/training/prostate-bioinformatics-2020-02-18/
• First we have to learn some R…

• Facebook,
• google,
• Microsoft (who recently invested in a commerical provider of R)
• The New York Times.
• Buzzfeed use R for some of their serious articles and have made the code publically available
• The New Zealand Tourist Board have R running in the background of their website
• The BBC makes code available for some of their stories (e.g. gender bias in music festivals)
• Airbnb

• The Rstudio environment
• Importing data from a spreadsheet
• Filtering Data
• Plotting
• Calculating numerical summaries
• Reporting
• Joining data from multiple spreadsheets

• We will cover a very small set of packages - the tidyverse

Image Credit: Aberdeen Study Group

• Spreadsheets are a common entry point for many types of analysis and Excel is used widely but
  • can be unwieldy and difficult to deal with large amounts of data
• error prone (e.g. gene symbols turning into dates)
• tedious and time consuming to repeatedly process multiple files
• how can you, or someone else, repeat what you did several months or years down the line?

• Live coding
  • no more slides!
• Exercises
• Tea and Coffee breaks!
• You can view the course notes online

• By the end of Day 1 we will be creating plots like this in a few lines of code

• Tidyverse website
• RStudio cheatsheets
• R graph gallery
• Sheffield R meetup
• Stack Overflow
• R bloggers
• google!