The amount of data generated by biological experiments is increasing exponentially, mainly due to the development of new powerful technologies for the acquisition of large-scale genetic and genomic data sets. If we would compile the DNA sequence of the human genome into a book, it would be a 200,000 pages book that will take 10 years to read. Bioinformatics became a compulsory skill for next generation biologists. In recent years, R became the programming language of choice for bioinformatics and biologists in academia and industry are currently using many tools that were developed in R. Computational Data Analysis: R for Life Sciences provides a basic introduction to programming for biologists in R and aims to provide students with the necessary programming skills and hand-on experience in performing data analysis with R. This module would be essential for further bioinformatics courses that students would take in their third year.
Learning Outcomes
In order to pass this module the student will need to be able to:
1. write scripts and functions in R and comment the code;
2. read and write data files in different formats;
3. use the basic plot functionalities of R;
4. write documentation and examples of how your functions and scripts should be used;
5. perform basic statistical analysis in R (correlation analysis and statistical tests);
6. demonstrate the ability to work as part of a team.
- Module Supervisor: David Clark
- Module Supervisor: Robert Ferguson