All GSMS courses
Only GSMS PhD students (including BCN PhD students) can participate in these courses. Use your P-number to register (ask your Personnel Office).
For registration please go to Upcoming courses.
Course: Very Quick-R
Summary: This course is not a full-size in-depth training in R programming language. It is mostly a bare minimum to what you have to know about R programming before you begin some analysis of biological data. It is remotely based on the Website Quick R, but with some modifications and shorter in length. It is intended only for those who have not tried R yet and want to test themselves. It especially important for those students, who will attend my course on “Gene Expression Data for beginners” but completely miss the knowledge of R programming. For complete course on programming in R check other possibilities in GSMS courses list.
Learning outcomes:
• Installation of R and R-studio on your laptop. General recommendations on updates, imported packages, organizing your scripts, keeping documentation in order.
• General idea on the R language, style, grammar, variables, script structure.
• Types of variables and basic operations with variables.
• Dealing with data tables. Manipulations with rows and columns. Simple transformations.
• Reading data from file. Extracting data, transforming data. Saving data to file.
Assumed pre-knowledge: The course is intended mostly for PhD students (but not exclusively) with a kind of a biological background (medical, pharmacy, biomed or similar). Prior knowledge of programming is not required. Motivation for programming is required. Postdocs, Master students, or PIs can also apply.
Equipment: Personal laptop with at least 8 GM RAM, any recent OS: Mac, Linux, or Windows10. Try to install recent version of R (with R-studio), not older than 1 year. If failed, it will be explained in the first session.
Compulsory literature : No. Useful links for self-improvement will be recommended during the course.
Exam: 99% participation required. Final evaluation is mostly based on successful homework. Expect homework after 1st two sessions.
Course schedule:
4 days 09:00-11:00 hours.
September
EC (without exam)
0.5
Course coordinator
- Leonid Bystrykh, PhD
Language
English