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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

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.

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 16, 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 |

- 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 Pirateâ€™s 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)
- Manuals (graphics)
- A preprint of the book ggplot2: elegant graphics for data analysis

- Editors
- GUIs
- Many books have been written that explain how to use R for statistical analysis. See
- Miscellaneous
- A web site with many beautiful graphs and the corresponding R code
- There are programs that allow running R from Excel and from SPSS (or search on 'R plug-in' at https://www.ibm.com/developerworks/)

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.

- Bioconductor support site
- Recommended literature
- Bioconductor-related publications
- Bioconductor Case Studies, Hahne, F.; Huber, W.; Gentleman, R.; Falcon, S., Spinger, 2008.
- Bioinformatics and Computational Biology Solutions Using R and Bioconductor, Gentleman, R.; Carey, V.; Huber, W.; Irizarry, R.; Dudoit, S. (Eds.), Springer, 2005.

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