Coding club - R
Date, time and place
Coding club - the R edition :-) will take place almost every Friday from 1pm-3pm in R3/08, starting on Friday 9th February 2018. On Friday 16th February, the club will take place from 2-4pm in HW2/32.
Requirements: R, R Studio and a text editor
To participate in the course, you will need to bring a computer with the following programmes and datasets:
R and R studio
Users of all platforms need first to install R (download version for Mac, Windows, Linux) and then install R Studio, an add-on that provides lots of useful bells and whistles on top of R. All our tasks and quizzes during the workshop will be done in R Studio.
Once you have R and R Studio installed, please execute the following commands in R console (copy each line into the console and press enter; you must be connected to the internet):
source("http://bioconductor.org/biocLite.R") biocLite("") install.packages("tidyverse")
During execution of these commands (see a short video below) you may be asked if R should update all/some/none of the packages: select “all” (
a). You may also be asked if R can install some packages in the user-writable directory - please agree (
y). Overall this may take several minutes. Don’t worry if something goes wrong, we should be able to sort things out during the first lesson.
Everybody needs a really good text editor.
- Windows users need to install a free text editor Notepad++;
- Mac users need to install a free text editor BBEdit (the full version of BBEdit is paid, but we will be using features only from the free basic version);
- Linux users need to install Gedit (Ubuntu Linux users have it already installed as their default text editor).
For the course materials, quizzes and answer submissions, we will use a shared Dropbox folder, so you will need to have Dropbox installed. You will receive the link to the shared folder before the first meeting.
I maintain a webpage of various computational biology resources that includes links to recent good papers arguing for computational biology skills, recommended textbooks and online sources plus various bits and pieces I use during the coding club and Software Carpentry lessons. Have a look: Computational Biology Resources FTW.
In particular, in our R lessons, we will be using R for Data Science: free online version of a very recent book by Garrett Grolemund and Hadley Wickham (it is also available on Amazon).
If you want to have a quick go at R before the first meeting, try this tutorial (no R installation necessary): Code School’s Try R. If you want to be quickly impressed at what R can do, follow this walkthrough on analysis of gene expression in yeast: Cleaning and visualizing genomic data: a case study in tidy analysis. You can copy-paste code from the walkthrough in your R Studio to go along with the author.
Software Carpentry workshops!
In 2017 and 2018 I am co-organising a series of 3-day-long workshops on essential computational skills for life scientists, along with Dr Maju J. O’Connell and Martin Callaghan from the University of Leeds. The workshops are sponsored by BBSRC and therefore are free for all BBSRC-funded researchers and staff and students from Universities of Leeds and Huddersfield. The detailed info about the upcoming workshop (there will be up to 10 workshops throughout a year) is available on the course webpage: Next Generation Biologists.
In terms of content, during the coding club we will cover topics roughly covered in day 2 of the workshop, so even if you attending the coding club you are still encouraged to apply.