Session content

Links should I tiny URL these ?

• Main landing page for boot camp: http://jennybc.github.io/2014-05-12-ubc/
• This page: http://jennybc.github.io/2014-05-12-ubc/ubc-r/
• GitHub repository that makes our boot camp website and holds all official SWC lesson material: https://github.com/jennybc/2014-05-12-ubc
• GitHub repository the instructors will develop during the boot camp: https://github.com/jennybc/bioinformatics.ca-swc-r
• The GapMinder data excerpt: http://tiny.cc/gapminder
• Our public digital whiteboard: https://etherpad.mozilla.org/ubc-r

We will write R code together "live" in the sessions, but below I link to written content on some topics, for your future reference.

Session 1.1: Basics of the R working environment and language

• Slides: slides/session01_bootcamp-deep-thoughts.pdf
• R basics, workspace and working directory, RStudio projects – source
• What does it mean to "write data for computers"?
  • Nine simple ways to make it easier to (re)use your data by Ethan P White, Elita Baldridge, Zachary T. Brym, Kenneth J. Locey, Daniel J. McGlinn, Sarah R. Supp. Ideas in Ecology and Evolution 6(2): 1–10, 2013. doi:10.4033/iee.2013.6b.6.f http://library.queensu.ca/ojs/index.php/IEE/article/view/4608. Section 4 "Use Standard Data Formats" is especially good reading.
  • Tidy data by Hadley Wickham. Submitted to The Journal of Statistical Software. Preprint available http://vita.had.co.nz/papers/tidy-data.pdf.

Session 1.2: Care and feeding of R objects

• Slides: slides/session02_objects.pdf
• Basic care and feeding of data in R – source
• R objects (beyond data.frames) and indexing – source

Session 1.3: Version control, introduction

• Slides: Intro to practical version control for scientists
• Using Git with RStudio

Session 1.4: Making figures using ggplot2

• Slides: slides/session04_ggplot2.pdf
• http://docs.ggplot2.org/
• Overview of the R graphics landscape
• Taking control of qualitative colors in ggplot2
• Head-to-head comparisons of ggplot2 and lattice
• Data Visualization with R & ggplot2 by Karthik Ram (first few slides make a good introduction)

Session 2.1: Writing functions

• Writing functions

Session 2.2: Data aggregation, including plyr

• Slides: slides/session07_dataAggregation.pdf
• plyr webpage
• Data aggregation – source
• Data aggregation section of a tutorial from STAT 540
• A Gist with R code that uses plyr to generate two files per country

Session 2.3: The shell, focus on file inspection and manipulation

Session 2.4: Version control, cont'd

• Getting Started with GitHub
• What we drew on whiteboard: slides/session07_git-github-rstudio.pdf

Session 2.5: Creating workflows and automated pipelines

• Slides: slides/session08_pipeline.pdf
• Getting data out of R – source
• Writing figures to file – source
• An introduction to Make by Karl Broman, aimed at stats / data science types