Registration

OPEN, please register HERE

Times

9.30am - 4.30pm each day

Venue

Online

Places

24 for each workshop

You will be contacted by our finance team for full payment. Once payment is made, your place will be confirmed and full details sent by our training team.

Registration fee

£350 - University of Edinburgh staff/students
£375 - Other university or registered charity staff/students
£400 - Industrial researchers
 

Information

Contact our training team

The aim of this course is to introduce participants to the statistical computing language 'R' using examples and skills relevant to biological data science. This online workshop is taught by experienced Edinburgh Genomics trainers. By the end of the workshop, you will be comfortable with the basics of the R and R Studio environments, learning about the rules of the language and how R works with different data types and structures. We then move on to using functions, introducing a selection of packages for biological data science including the 'Tidyverse' family of packages. Finally, we will learn how to visualise your data to generate publication-ready plots using the package ggplot2.

"Thanks to the brilliant @Nathcmedd for transforming me from completely clueless to vaguely competent in just 3 days! 100% recommend for anyone looking to get into coding!" (August 2022)

"Really enjoyed the last few days of the "R for biologists course" of @edgenome. Thanks @nathcmedd  for the great introduction! Can highly recommend to anyone who wants to have a first try with R"  (April 2022)

Instructors

• Nathan Medd (Training Manager, EdGe)
• Heleen De Weerd (Bioinformatics Analyst, EdGe) 

Workshop format

The workshop consists of presentations and hands-on tutorials.

Who should attend

Graduates, postgraduates, and PIs, who are using, or planning to use, the statistical software R to manipulate and analyse NGS and other data in their research. This is an introductory level course: no prior experience of R is necessary before starting the workshop.

Covered topics

See tentative timetable below:

Day 1

• Intro to R 
• Rstudio, R markdown
• R objects, variables and data types 
• R resources: cheat sheets, help
• Simple data structures
•  

Day 2

• Data Importing and cleaning
• Data manipulation and subsetting
• User defined functions
• The 'Apply' family

Day 3

• Data viz with ggplot2
• Discussion/data clinic