- Mark Dunning and Matt Eldridge, Cancer Research Uk Cambridge Institute
- Tom Carroll, MRC Clinical Sciences Centre, London
##Description:
It has been said that 80% of data analysis is spent on the process of cleaning and preparing the data. In this course we introduce some relatively-new additions to the R programming language; dplyr and ggplot2. In combination these provide a powerful toolkit to make the process of manipulating and visualising data easy and intuitive.
- Graduate students, Postdocs and Staff members from the University of Cambridge, Affiliated Institutions and other external Institutions or individuals
- Further details regarding eligibility criteria are available here
- Further details regarding the charging policy are available here
- Attending the "Introduction to Solving Biological Problems using R" course would be beneficial, but not essential. We will assume that you know how to load RStudio, create variables and use functions. Some good introductory videos can be found here -> http://shop.oreilly.com/product/0636920034834.do
- We would recommend this course to those with programming experience in other languages that want to know what R can offer them. Likewise you should also consider coming if you have used R for some years, but are not familiar with dplyr and ggplot2.
- How R enables reproducible research
- What constitues a tidy dataset
- "Piping" commands together to form a workflow
- Subseting and filtering datasets using dplyr
- Producing summary statistics from a dataset
- Joining datasets using dplyr
- The grammar of graphics approach to plotting used in ggplot2
- Create reproducible documents
- Import and tidy and datasets into R
- Use dplyr to explore a dataset interactively
- Produce simple analysis workflows in R
- Make publication-ready graphics using ggplot2