Besides some introductory material, there are four major topics that are presented in this course:

1)     Microarray principles and data analysis
How does the technology work that enables us to measure the level of expression of a set of genes? And how are expressions from several samples belonging to two or more groups condensed into a list of “differentially expressed genes” (= genes that show a stastically significant difference in expression across the groups)

2)     Sequencing principles and genome assembly
How do sequencing machines work, what are their technical strength and weaknesses? What algorithms or principles do we have to come from a huge set of short (100 - 200 bps) “reads” to a reconstruction of the full genome?

3)     Read alignment
How do we align our reads to an existing genome, in order to find out about the differences?

4)     RNAseq
How do we use sequencing of RNA to assess gene expression patterns, including differential gene expression (like we did with microarrays)?

GT is “KV” (“combined lecture”). This means that you will get one or two assignments during the lecture. Together with the result from the final exam, this will yield your mark for the course.