R for Scientists (2.5 days)
R for Scientists
Leverage the power of the R programming language to unlock the potential in your data.
Why enroll onto this course?
Over the years R has established itself as the go to data analysis language for academics across many scientific disciplines, but as the talent pool expands it is finding more and more application within the enterprise market. Combined with access to cutting edge analysis, R boasts best in class graphics capabilities for generating professional plots and images. Technical benefits aside, R comes with a steep learning curve that quickly plateaus once you have a command of the basics. This course aims to march you through the first steps and place you firmly on that plateau in a position to confidently move forward with your own data and continue learning independently.
There are no pre-requisites for this course. This course is for anyone who understands the limitations of off-the-shelf data analysis products and the inevitable requirement for professional bespoke data analysis at scale. Attendees will be provided with all the materials and scripts required to complete it on a USB stick for reference once the course is completed.
Over two and a half days you will gain practical experience in the fundamentals of a data analysis using R. In addition specific time will be devoted to address your application specific challenges with one of our bioinformatics professionals.
• Day 1 - Become familiar with the R environment and its use as an advanced scientific calculator. Next we will learn about the available data structures in R. We will use this information to write our first script with the standard workflow of loading data, analyzing data then writing results. Following on we will introduce some standard R functions and flow control tools for writing more sophisticated scripts. Finally we will discuss R’s capability for supporting statistical analysis of data. (09:00-17:00h)
• Day 2 – We begin day 2 with a walkthrough example that recaps all of the functionality of R covered in day 1. Afterwards, the syntax of custom functions and the best practices around writing them will be discussed. A major challenge in data analysis is combining and homogenizing multiple data sets destined for a single analysis. We will walk through an exercise that demonstrates the tools and a typical approach to aggregating a dataset and generating an analyzable data object from it. Finally, we will cover basic graphics in R and the popular ggplot2 package. (09:00-17:00h)
• Day 3 – This optional session is split into a number of 1-on-1 consultations where course attendees can bring their own data and develop an approach in R for its analysis with the course instructor. By the end of this session, attendees will have all of the basics to develop novel analyses in R and a roadmap for moving forward with their own data. (09:00-13:00h)
For Research Use Only. Not for use in diagnostic procedures.
Tell a colleague about this course. Copy the following URL:
No classes currently scheduled (contact us to request a class).