5.1 Some links and some extras
This is for collecting factoids, ideas, and links that may be useful as reference (if not inspiration) for your future R practice.
5.1.1 Ideas for figures
- An interactive page showing different types of figures
- A R graph gallery
- Claus Wilke’s cowplot package is a great way to make multi-panel figures with ggplot, so A B etc.
5.1.2 More links
swirl is an excellent interactive tutorial package you can install and work through yourself for more practice, get started here
A whole bunch of cheatsheets and example sheets of common commands and ways to do things, check under “Contributed Cheatsheets” for some great ones, or browse them all
- Claus Wilke’s dataviz bookdown
- Computational Genomics with R
- UC Davis bioinformatics trainings
- R Programming for Data Science
- Biostars books on scripting, programming, genomics
5.1.3 More about workflows
We talked about workflows in R, but much of bioinformatics workflows are happening outside of R, in bash (etc). To handle those, there are more sophisticated workflows that will generate steps from combinations of parameters, schedule and allocate those across HPC and remote commercial (amazon/google) computing, and automatically generate analytics and reports to help you optimize your workflows.
These include SnakeMake, Nextflow, and CWL. And others, but these are the main ones. This author recommends Nextflow. There’s a bit more of a learning curve than SnakeMake, but it is well built and very flexible.
These will not be necessary for summer projects, but may be useful skills for bioinformatics research for at least the next 5-10 years.
5.1.4 Rmarkdown for slides
Want to put a bunch of R plots into some slides? You can also turn your Rmarkdown file into a set of presentation slides, by adding the following line in the YAML header:
output: slidy_presentation
output:
slidy_presentation:
theme: default
This makes a HTML file you can open in your browser, like slides (left, right for the slides).
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