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Computing in R

This course is part of the PhD course program of the Amsterdam UMC-AMC Graduate School.

  • Location: Academic Medical Center, Amsterdam.
  • Course material: All course material is provided during the course, no need to print anything yourself
  • ECTS: 0.4
  • Teachers: Perry Moerland (coordinator), Aldo Jongejan and Michel Hof

Goal

R is a simple programming language for statistical computing. Due to its flexibility and the large variety of statistical functions available in R, it is a popular alternative for programs like SPSS. However, for a beginner mastering R can be rather difficult. This course helps the student to become familiar with the basics of R. After the course the student will be able to write short programs in R for basic (data) analyses and for plotting figures.

Schedule and course material (September 2019 edition)

Location Day Time Topic Lectures Demo Exercises Exercises (answers)
L01-243/245 September 16, 2019 09.00-12.00   Handout Slides Slides on graphics Demo code (R, Rmd, html) pdf, html pdf, html, R code
  September 16, 2019 12.00-13.00 Lunch break        
L01-243/245 September 16, 2019 13.00-17.00          
L01-243/245 September 17, 2019 11.15-12.45          
  September 17, 2019 12.45-13.30 Lunch break        
L01-243/245 September 17, 2019 13.30-17.00          

Datasets for the exercises

Information on R

  • R homepage
  • R and its packages can be downloaded from CRAN
  • Introductory material
    • Learn R interactively using swirl. Use their 'R Programming' course to refresh what you learnt in our course.
    • A basic introduction to R, somewhat in line with this course
    • Another short introduction to R with a nice list of common error messages (and how to maybe solve them) on the last page
    • The Quick-R page shows the commands to be used for many aspects of a statistical analysis, and has been created especially for experienced users of some other statistical packages
    • Cookbook for R offers many great examples
    • Datacamp offers several on-line courses at the beginner and intermediate level with lots of exercises
    • YaRrr! The Pirate‚Äôs Guide to R is meant to introduce you to the basic analytical tools in R, from basic coding and analyses, to data wrangling, plotting, and statistical inference
    • Documentation for R packages organized by topical domains
    • Other sites to get you started are Impatient R and Statistics with R.
    • There is a book called "R for SAS and SPSS users''. The corresponding web site also has a freely downloadable early version of the book. It also has a comparison table that lists the corresponding R packages for many SAS and SPSS procedures.
  • Manuals (basic)
    • An introduction to R (pdf,html): R in 100 pages
    • R reference card: R in 6 pages
    • Other useful cheat sheets (for example, for ggplot2 and importing and transforming data via tidyr and dplyr) provided by the people at RStudio
  • Manuals (advanced)
    • R Data Import/Export (pdf,html)
    • R Language Definition (pdf,html)
    • Writing R Extensions (pdf,html)
    • R Installation and Administration (pdf,html)
  • Manuals (graphics)

Pointers

Information on Bioconductor

Bioconductor is an open source and open development software project for the analysis and comprehension of genomic data in R. Much of data analysis in bioinformatics is done within the R/Bioconductor statistical environment. For example, many statistical methods for the analysis of microarray and other high-throughput data are available from Bioconductor.

Topic revision: r55 - 10 Sep 2019, PerryMoerland
 

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