First Steps with R in Life Sciences
Lausanne, 9-10 March 2016
Trainers: Diana Marek Venue: University of Lausanne, Genopode building ECTS: 0.5 (given a passed exam) Fee: 100 CHF for academics. Others, please contact us Application deadline: 1 March 2016 Application status: CLOSED
R is a complete, flexible and open source system for statistical analysis which has become a tool of choice for biologists and biomedical scientists, who need to analyze and visualize large amounts of data. Due to its popularity, R is continuously updated and extended with the latest analysis tools that are available in the different research fields. In bioinformatics, in particular, most published papers include a link to an R package implementing the methods described in the article.
This "First Steps with R" two-day course is addressed to beginners wanting to become familiar with the R syntax and environment as well as with the most common commands to start using R to explore and interpret their data.
At the end of the course, participants should be comfortable with the R environment and be able to read, understand and write R commands, that will allow them to implement and interpret a workflow for their data analysis:
- Interact with the R environment
- Import data, explore it and summarize it
- Explore data with graphs
- Test statistical hypothesis
- Use statistical models
Knowledge / competencies:
As it is a course for beginners, no background in R or any programming language is required. However, you are encouraged to go through the R tutorial and documentation available here. Please also note this course is NOT a training on statistics but rather a training on how to use R to perform different tasks, statistics being one of them .
a Wi-Fi enabled laptop with latest R and R studio versions installed.
University of Lausanne, Genopode building, classroom 2020 (Metro M1 line, Sorge station)
Coordination: Diana Marek & Grégoire Rossier
You are welcome to register to the SIB courses mailing-list to be informed of all future courses and workshops, as well as all important deadlines using the form here.
For more information, please contact email@example.com.
Day 1 (9h-17h):
- Formatting your data
- What is R ? Advantages and drawbacks
- Getting familiar with R and RStudio environments
- Getting data into R
Day 2 (9h-17h):
- Building some graphics in R
- Doing some statistics in R
Examples and exercises are integrated in the chapters.