R Package design and development and reproducible data science for biologists (RPKG01)
16 September 2019 - 20 September 2019£275.00 - £550
This course will help students develop professional R coding skills by leading them through the process of making reproducible, sharable and easily communicated software centered around developing fully functional R packages and extensions. In addition to teaching traditional uses of R packages to share quantitative tools, we’ll also show how R packages can be easily developed for individual research projects to share reproducible results. To develop skills, we’ll build several R packages full of useful and general utility functions that will hone coding skills and teach coding tips through the design of these functions. Each day, we’ll reserve time for open work sessions where students can receive mentoring while applying new skills to developing their own application specific package or refining the packages we’re developing for the course.
Anyone wanting to make their data science work accessible, reproducible and usable by others (the importance of specific R packages has grown considerable now that they are frequently cited in peer reviewed literature). This can include researches developing their own quantitative tools or those interested in taking the next step in making their research projects fully reproducible and easily shared.
Venue – PR statistics head office, 53 Morrison Street, Glasgow, G5 8LB – Google map
Availability – 30 places
Duration – 5 days
Contact hours – Approx. 35 hours
ECT’s – Equal to 3 ECT’s
Language – English
We offer COURSE ONLY and ACCOMMODATION PACKAGES;
• COURSE ONLY – Includes lunch and refreshments.
• ACCOMMODATION PACKAGE (to be purchased in addition to the course only option) – Includes breakfast, lunch, welcome dinner Monday evening, farewell dinner Thursday evening, refreshments and accommodation. Self catering facilities are available in the accommodation. Accommodation is approx. a 6 minute walk form the PR statistics head office. Accommodation is multiple occupancy (max 3-4 people) single sex en-suite rooms. Arrival Sunday 15th September (after 5pm) and departure Friday 20th September (accommodation must be vacated by 9am).
To book ‘COURSE ONLY’ with the option to add the additional ‘ACCOMMODATION PACKAGE’ please scroll to the bottom of this page.
Other payment options are available please email email@example.com
Cancellation policy: Cancellations are accepted up to 28 days before the course start date subject to a 25% cancellation fee. Cancellations later than this may be considered, contact firstname.lastname@example.org Failure to attend will result in the full cost of the course being charged. In the unfortunate event that PRstatistics must cancel this course due to unforeseen circumstances a full refund for the course will be credited. However PRstatistics cannot be held responsible for any travel fees, accommodation or other expenses incurred to you as a result of the cancellation.
Dr. Cory Merow
Dr. Andy Rominger
Each day there will be theoretical sessions (lectures) based on particular themes as outlined in the course timetable, as well as practical sessions based on the topics covered during the theory sessions.
Assumed quantitative knowledge
Some basic coding experience and familiarity with R
Assumed computer background
Basic experience with R, including regressions, graphics, and manipulating data frames. This ‘experience’ often corresponds to one or more years of using R regularly. Contrary to popular belief, you do not need to be an R expert to create a package. We’ll teach the ‘expert’ skills you’ll need. The course will use RStudio to work with R.
Equipment and software requirements
A laptop/personal computer with a working version of R or RStudio installed.
R and RStudio are supported by both PC and MAC and can be downloaded for free by following these links
UNSURE ABOUT SUITABLILITY THEN PLEASE ASK email@example.com
Meet at Flat 2/1, 43 Cook Street, Glasgow G5 8JN at approx. 17:00 to 21:00
Monday 16th – Classes from 09:30 to 17:30
We’ll begin with polishing core skills in the creation, documentation and distribution of code:
Making your code reproducible by documenting it with RMarkdown and ROxygen
Making your first package, breaking it, then fixing it
Tuesday 17th – Classes from 09:30 to 17:30
Next we dive into specifics critical for the success of collaborative, reproducible and sharable projects:
Principles of software development and reproducible projects
Writing useful documentation and examples
Collaboration with git and GitHub
Wednesday 18th – Classes from 09:30 to 17:30
We will continue learning about the details that help to make a package robust to different use cases:
Dependencies, and achieving independency
The rules of CRAN and GitHub
Thursday 19th – Classes from 09:30 to 17:30
By now students will have fulling functioning, collaboratively produced, and reproducible R packages. We now turn to two key aspects of software usability: its computational burden, and its cognitive burden. Put simply, we will focus today on making code computationally fast and easy for users to quickly and intuitively understand.
Writing fast code
Profiling code for speed
S3 and S4 objects
Friday 20th – Classes from 09:30 to 16:00
On the final day we will culminate our software development by learning and implementing powerful ways to share our projects with a large audience.
Adding a shiny web app to a project
Publishing your own package
The instructors were excellent and clearly were the reasons for my previous comments. They both combined a deep understanding of statistics and ecology at the same level.Any questions or queries I’ve had, were thus first answered with an ecological point of view and then translated into statistical consideration thereby making much more sense on both side.In addition the course was very well organised, the course director and the two instructors were very friendly as well as professional. On the top of learning many useful things, I’ve also had a very good time during the week there.” Clement Garcia,
Spatial ecologist, Centre For Environment, Fisheries & Aquaculture Science (CEFAS), England
(Attended ADVR course)