R for reproducible scientific analysis - Imperial College London

April 15-16, 2019

10:00 - 17:00

Instructors: Margarita Cariolou, Elzbieta Lauzikaite, Kiana West, Anat Melamed

Helpers: Aris Aristodemou, Amit Mandal, Andrew McArdle

General Information

Software Carpentry aims to help researchers get their work done in less time and with less pain by teaching them basic research computing skills. This hands-on workshop will cover basic concepts and tools, including program design, version control, data management, and task automation. Participants will be encouraged to help one another and to apply what they have learned to their own research problems.

For more information on what we teach and why, please see our paper "Best Practices for Scientific Computing".

Who: The course is aimed at graduate students and other researchers. You don't need to have any previous knowledge of the tools that will be presented at the workshop.

Where: School of Medicine, SMMS 142 - Hynds computer room, St Mary's Campus. Get directions with OpenStreetMap or Google Maps.

When: April 15-16, 2019. Add to your Google Calendar.

Requirements: Participants must bring a laptop with a Mac, Linux, or Windows operating system (not a tablet, Chromebook, etc.) that they have administrative privileges on. They should have a few specific software packages installed (listed below).

Code of Conduct: Everyone who participates in Carpentries activities is required to conform to the Code of Conduct. This document also outlines how to report an incident if needed.

Accessibility: We are committed to making this workshop accessible to everybody. The workshop organizers have checked that:

Materials will be provided in advance of the workshop and large-print handouts are available if needed by notifying the organizers in advance. If we can help making learning easier for you (e.g. sign-language interpreters, lactation facilities) please get in touch (using contact details below) and we will attempt to provide them.

Contact: Please email k.michalickova@imperial.ac.uk for more information.


Please be sure to complete these surveys before and after the workshop.

Pre-workshop Survey

Post-workshop Survey


The class is fully booked.

You are welcome to put your name on the waiting list.


Day 1

10:00 R for reproducible scientific analysis 1
R studio introduction, getting help, lists and subsetting
coffee at 11:30
13:00 Lunch break
14:00 R for reproducible scientific analysis 2
data frames, exploring data frames, control flow (loops and if statements)
coffee at 15:30
17:00 END

Day 2

10:00 R for reproducible scientific analysis 3
plotting with ggplot, data manipulation with tidyverse and dplyr
coffee at 11:30
13:00 Lunch break
13:45 R for reproducible scientific analysis 4
R markdown and producing reports with knitr, interactive data analysis with shiny
coffee at 15:15
16:30 Rich FitzJohn: Researchers, Research Software Engineers and the importance of interfaces (School of Medicine, G64)
17:30 Reception

We will use this collaborative document for chatting, taking notes, and sharing URLs and bits of code.


R for Reproducible Scientific Analysis


To participate in a Software Carpentry workshop, you will need access to the software described below. In addition, you will need an up-to-date web browser.

We maintain a list of common issues that occur during installation as a reference for instructors that may be useful on the Configuration Problems and Solutions wiki page.


R is a programming language that is especially powerful for data exploration, visualization, and statistical analysis. To interact with R, we use RStudio.

Video Tutorial

Install R by downloading and running this .exe file from CRAN. Also, please install the RStudio IDE. Note that if you have separate user and admin accounts, you should run the installers as administrator (right-click on .exe file and select "Run as administrator" instead of double-clicking). Otherwise problems may occur later, for example when installing R packages.

You can download the binary files for your distribution from CRAN. Or you can use your package manager (e.g. for Debian/Ubuntu run sudo apt-get install r-base and for Fedora run sudo dnf install R). Also, please install the RStudio IDE.