Resources

A rough resource lists for where tutorials or resources can be found from various sources on the internet.

When in doubt with any programming problem Google and Stack Exchange should always be your first port of call and lots of great programming idioms can be learnt this way.

Python

• Software Carpentary provide resources for workshops that are run all around the world, including here at Victoria University. Their lessons are also avaialable to follow online for free inluding their intro to python.

R resources

• The University of Edinburgh Coding Club have a number of excellent tutorials on how to code in R, and to conduct data analysis. As these are mainly ecology and environmental science students the type of data science they focus on is very relevant to biology

• Intro to R by Bioinformatics Canada will provide a solid basis for learning coding in R and will be appropriate for complete beginners.

• EDA in R, also by Bioinformatics Canada is a good next step for coding in R and will equip you well for analysing biological data in R.

• Swirl is an R package that will ”teach you R programming and data science interactively, at your own pace, and right in the R console!”

  • This is highly recommended as a great place to start

• Software Carpentary also have an introduction to R. This focuses on the analysis of a dataset for inflammation in patients over a number of days.

Bioinformatics

• Rosalind is an online bioinformatics platform that provides challenges and is a great way to apply what coding you’ve learnt in a biological setting. It has a real focus on sequencing work and there are sections for both writing new code and for the application of existing bioinformatic solutions.

• Bioinformatics Canada provide open access to the workshops they run on computational biology. These cover very diverse fields and have great tutorials and online lectures.

• OMGenomics has videos on tutorials on data analysis and visualisation for high-throughput genomic data.