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.

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.

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.

4. A short microarray analysis

• reading spreadsheets into R
• saving/loading objects
• basic plotting
• for loops: counting differentially expressed genes in three microarray result data

5. Another microarray analysis

• combining multiple expression matrices and produce a heatmap
• extracting, parsing and visualising genes of interest

6. A short Bioconductor data analysis

• Quality control
• Exploratory data analysis

See the TeachingMaterial repository for more material.

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