3 EC
Semester 2, period 4
5224TIMD3Y
| Owner | Master Biological Sciences |
| Coordinator | Anouk Zancarini |
| Part of | Master Biological Sciences, track General Biology, Master Biological Sciences, track Green Life Sciences, |
This course aims to develop practical skills in data handling, analysis and visualization for large “omics” data commonly found in contemporary plant research.
First, the Unix Shell will be introduced in order to acquire the basic skills to navigate through files and directories on your computer, construct command pipelines with two or more stages, write a loop that applies one or more commands separately to each file.
Then, three domain-specific projects will be addressed: i) RNA-seq analysis, ii) Genome comparison analysis and iii) Microbiome analysis. For each project, after introductory lectures on the topic, students will be trained to handle these specific datasets. Afterwards, they will have to process a dataset by themselves and build a result report to describe their biological conclusions from the experiment. They will receive feedback on their approach, including their R coding practices and the biological interpretation of their results.
During this course, importance of both experimental design and parameter choice will be discussed. The students will have to perform a data analysis in the most reproducible manner and visualize data to convey a biological answer to a research question.
Microbiome data analysis: https://www.nature.com/articles/nature11237
Microbiome data analysis: https://www.nature.com/articles/s41579-018-0029-9
Genome comparison and Phylogenomics data analysis: https://doi.org/10.1016/S0168-9525(03)00112-4
Gene expression data analysis (RNA-seq): https://www.nature.com/articles/s41576-019-0150-2
All documents will be made available in Canvas
All documents will be made available in Canvas
Windows users need to install Git for Windows: https://gitforwindows.org
First, lectures will explain the general concepts and give an overview of the omics data analysis process. Then, practicals will help the students to first learn in details how omics data are analysed and then apply what they just learnt through small exercices. During these practical sessions, students will be able to check if they can apply what they have learnt and discuss with the others students and the teacher. Finally, students will work in groups of two on projects in order to apply what they have learnt and analyse a new omics data set, describe and discuss their results.
Activity | Hours | |
Werkcollege | 54 | |
Self study | 30 | |
Total | 84 | (3 EC x 28 uur) |
Requirements of the programme concerning attendance (OER-B):
| Item and weight | Details |
|
Final grade |
The three assignments will be done in groups of two students. For each assignment, students need to change group partner. It will not be allowed to do two assignments with the same group partner. The three assignments will be graded. Feedback will be given via Canvas.
The 'Regulations governing fraud and plagiarism for UvA students' applies to this course. This will be monitored carefully. Upon suspicion of fraud or plagiarism the Examinations Board of the programme will be informed. For the 'Regulations governing fraud and plagiarism for UvA students' see: www.student.uva.nl
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The schedule for this course is published on DataNose.
We will arrange virtual machines for the students.
We changed the course format removing the Spreadsheet and R module and planning less lecture/practical hours per day.