At the end of the course, students should have a profound understanding of, and be able to analyze and evaluate:
1. Assessing sequencing quality control (FastQC).
2. How genome assembly is performed.
3. The impact of sequencing strategy and genome structure on the quality of prokaryotic and eukaryotic genome assemblies.
4. How to identify genes on a genome sequence, the difficulties of gene prediction, and how to incorporate other data for genome annotation.
5. Scatterplots, histograms, and boxplots generated in R.
6. The principle and use of orthologous groups.
7. The power and usefulness of comparative genome analysis.
8. Tools to work with genomic data and how to visualize results (e.g. in R).
At the end of the course, students should be able to apply and creatively design ways to:
1. Navigate your file system using the command line.
2. Develop an automated workflow with a series of sequential commands.
3. Examine the command line analysis results with Integrative Genomics Viewer (IGV).
4. Evaluate the associated metadata with R.
5. Develop a workflow (includes trimming, quality control) to analyse datasets with learned techniques.
6. Execute a genome assembly.
7. Select appropriate commands in R to carry out association scoring.
8. Hypothesize on the causes of the phenotypes associated with the different datasets.
9. Map RNA-Seq reads, determine gene expression values, perform differential gene expression analysis.
10. Perform functional annotation of predicted protein sequences and interpret the results.
11. Design and execute comparative genomics analyses and interpret the results.
12. Perform a resequencing analysis and interpret the results.
Microbes are crucial for life on earth and are highly relevant for human life as beneficials, pathogens, food producers, nutrient cycling, agriculture and many other aspects of our daily lives. The genomes of microbes provide a wealth of information on the processes and mechanisms that these organisms use in their environment. For instance on mechanisms that pathogens use to overcome host immunity or antibiotics, or enzymes that fungi use to produce interesting metabolites that can be used in medicine or agriculture.
In this course you will learn how to analyse genome data of individual microbes, but also of microbiual communities (metagenomics). The first week will be focused on basic bioinformatic skills (linux, R, bash, and command line tools) and the analysis of bacterial genomes. In the second week the analyses will be on Eukaryotic microbes with a focus on fungal genomes, comparative approaches and expression analysis.
The course will have theroretical lectures, but will mainly consist of hands-on bioinformatic practicals. Knowledge on programming is therefore a prerequisite.
Literature/study material used:
Online material and papers.
Mandatory for students in Master’s programme: NO.
Optional for students in other Master’s programmes GS-LS: Yes, all GSLS