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An introduction to R for beginners, using microarrays as main thread
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Exercises
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README.md
RIntro.Rnw
RIntro.pdf
Sec-AboutR.Rnw
Sec-BiocCase.Rnw
Sec-DataTypes1.Rnw
Sec-DataTypes2.Rnw
Sec-IntroR.Rnw
Sec-Manip.Rnw
Sec-Packages.Rnw
Sec-Plotting.Rnw
Sec-Programming.Rnw
Sec-RBioc.Rnw
Sec-UseCase.Rnw
Sec-Useful.Rnw
Sec-objects.Rnw
knitr.Rnw

README.md

A 1 day R introductory course for non-programmers, using microarrays as main thread. Also includes an intro to Bioconductor and the eSet infrastructure. Initially set up for the diXa Microarray Analysis using R and Bioconductor training (see tags for specific courses). Partially based on the Beginners guide to solving biological problems in R (see also here) course by Robert Stojnić, Rob Foy, John Davey, Laurent Gatto and Ian Roberts.

Slides

The slides provide a general introduction to R and the main data structures. Scripting and plotting is presented by means of exercises using microarray data as example. Finally, Bioconductor and the microarray eSet/ExpressionSet classes are introduced and compared to the previous introductory material and exercises.

Exercises

  1. Using R interactively and running a script.
  2. Vectors
  3. How to store microarray data
  • expression data and meta data
  • matrices, data frames and lists.
  1. A short microarray analysis
  • reading spreadsheets into R
  • saving/loading objects
  • basic plotting
  • for loops: counting differentially expressed genes in three microarray result data
  1. Another microarray analysis
  • combining multiple expression matrices and produce a heatmap
  • extracting, parsing and visualising genes of interest
  1. A short Bioconductor data analysis
  • Quality control
  • Exploratory data analysis

See also

See the TeachingMaterial repository for more material.

This material is licensed under the Creative Commons Attribution-ShareAlike 3.0 License.

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