Putting the R in Reproducible Research - Anna Krystalli (Research Software Engineering, The University of Sheffield)

R and its ecosystem of packages offers a wide variety of statistical and graphical techniques and is increasing in popularity as the tool of choice for data analysis in academia. In addition to its powerful analytical features, the R ecosystem provides a large number of tools and conventions to help support more open, robust and reproducible research. This includes tools for managing research projects, building robust analysis workflows, documenting data and code, testing code and disseminating and sharing analyses. In this talk we’ll take a whistle-stop tour of the breadth of available tools, demonstrating the ways R and the Rstudio integrated development environment can be used to underpin more open reproducible research and facilitate best practice.

Cloud Computing with R - Alison Parton (Animal and Plant Sciences, The University of Sheffield)

R has cemented itself as the language of choice for many a statistician and data scientist, but is often heckled as a sluggish competitor to the likes of Python. This talk will discuss one avenue for maintaining the comfort and power of R (see Anna’s talk!) without having to wait days for your desktop analysis to complete. The foreach package is a set of functions that allow virtually anything that can be expressed as a for-loop as a set of parallel tasks. By registering a parallel backend through the doParallel package, you can speed up the run-time of your work by utilising the full capacity of your machine. Alison will introduce how to rewrite workflows to utilise the foreach approach and show how you can implement a parallel workflow on your own machine with doParallel. For a low-range machine, this will reduce your run-time by 4-fold and for those lucky few with high-range budgets you’ll receive something around 16-fold. So how about going one step further, and increasing to hundreds-fold? We can achieve this by using cloud computing services, taking the load away from your own machine. Cloud computing services have been seen to have a steep learning curve and this has led to many shying away from using such a useful resource. Alison will introduce you to the doAzureParallel package for R, create by Microsoft to bypass this learning curve and allow you to implement the foreach package in parallel in the cloud with only minor amendments to the R code that has been blighting you for months. 

R Validation Hub Project - Lyn Taylor (Phastar, PSI AIMS SIG Lead, RSS Local Group chair)

To date, the use of R Software in the pharmaceutical industry has been relatively limited to exploratory work and not routinely used in regulatory submissions where SAS® Software is still favoured. One of the difficulties in using R for submissions is being able to provide the regulators with appropriate documentation of testing and validation for the packages used. In June 2018, the R consortium granted funding for a PSI AIMS SIG initiative to create an online ‘R package validation repository’. With representatives from Abbvie, Amgen, Biogen, Eli Lilly, FDA, GSK, J&J, Merck, Merck KGaA, Novartis, PPD, PRA, Pfizer, Roche / Genentech, Syne qua non and the Transcelerate project, the ‘R Validation Hub’ team launched a free to access web site to host validation documentation and metrics for R packages (https://www.pharmar.org/). Although, the project is still in its early stages, it is looking to expand on the website content and encourage contribution of R metrics and tests for packages from all R-users. The talk will discuss what is meant by validation, how R differs to SAS, justify our approach to the validation issue and present the future capabilities of the website and how all R-users are set to benefit from the work.