A 1 day
R introductory course for non-programmers, using
microarrays as main thread. Also includes an intro to Bioconductor and
eSet infrastructure. Initially set up for the
Microarray Analysis using R and Bioconductor training (see tags for
specific courses). Partially based on the
Beginners guide to solving biological problems in
(see also here)
course by Robert Stojnić, Rob Foy, John Davey, Laurent Gatto and Ian
provide a general introduction to
the main data structures. Scripting and plotting is presented by means
of exercises using microarray data as example. Finally,
Bioconductor and the microarray
ExpressionSet classes are introduced and compared to the
previous introductory material and exercises.
- expression data and meta data
- matrices, data frames and lists.
- reading spreadsheets into
- saving/loading objects
- basic plotting
forloops: counting differentially expressed genes in three microarray result data
- combining multiple expression matrices and produce a heatmap
- extracting, parsing and visualising genes of interest
- Quality control
- Exploratory data analysis
See the TeachingMaterial repository for more material.
This material is licensed under the Creative Commons Attribution-ShareAlike 3.0 License.