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Course module: B-MCMIGE
B-MCMIGE
Microbial Genomics
Course infoSchedule
Course codeB-MCMIGE
ECTS Credits3
Category / LevelM (Master)
Course typeCourse
Language of instructionEnglish
Offered byFaculty of Science; Graduate School of Life Sciences; Graduate School of Life Sciences;
Contact persondr. B.E. Dutilh
E-mailB.E.Dutilh@uu.nl
Lecturers
Contactperson for the course
dr. B.E. Dutilh
Other courses by this lecturer
Lecturer
dr. B.E. Dutilh
Other courses by this lecturer
Lecturer
dr. R. de Jonge
Other courses by this lecturer
Lecturer
dr. R.A. Ohm
Other courses by this lecturer
Teaching period
3-GS  (03/02/2020 to 17/04/2020)
Teaching period in which the course begins
3-GS
Time slot-: Not in use
Study mode
Full-time
Remark6-17 april 2020
Enrolment periodfrom 28/10/2019 up to and including 24/11/2019
Enrolling through OSIRISYes
Enrolment open to students taking subsidiary coursesYes
Pre-enrolmentNo
Post-registrationYes
Post-registration openfrom 20/01/2020 up to and including 17/02/2020
Waiting listYes
Aims
Learning Objectives


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.
Content
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
Competencies
-
Entry requirements
-
Prerequisite knowledge
Knowledge of Python and R, knowledge about genome biology and genome sequencing.
For registration students should include prove for sufficient background knowledge by including their transcript/grade list form Osiris.
Required materials
-
Instructional formats
Computer practical

Individual

Lecture

Lecture/seminar

Tests
Final result
Test weight100
Minimum grade-

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Kies de Nederlandse taal