Transcriptomics

Faculteit | Science and Engineering |
Jaar | 2022/23 |
Vakcode | WMBS014-05 |
Vaknaam | Transcriptomics |
Niveau(s) | master |
Voertaal | Engels |
Periode | semester II a (20-02-2023 till 12-03-2023) |
ECTS | 5 |
Rooster | rooster.rug.nl |
Uitgebreide vaknaam | Transcriptomics: RNAseq | ||||||||
Leerdoelen | At the end of the course, the student is able to: 1) know how to design a transcriptomics experiment for a biological problem. 2) apply the proper statistical method for analyzing transcriptome data. 3) examine the results by coupling the data to biological knowledge using literature data. 4) show plans for downstream research. 5) work accurately on RNA isolation, cDNA synthesis and library preparation for NGS. 6) interpret and analyze ChIP-Seq and RNA-seq data. 7) use statistical webserver and perform shell scripting on a High Performance Computing (Peregrine) system 8) evaluate problems, progress and results with the other course students, PhD students and teachers. 9) summarize results and research strategy in a PowerPoint presentation and a report. |
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Omschrijving | In this course, theory and practicals are combined to give an in-depth view of transcriptomics research in eukaryotes and prokaryotes. This master course is divided into three parts. The first part focuses on the theoretical background of Next Generation Sequencing (DNA-Seq and RNA-Seq) and on how important the role of RNA is in modern science. The assessment for this part consists of a literature case study on ChIP-Seq in Eukaryotes. The second part consists of 3 - 4 days lab work to practice working with RNA; quality control of the RNA, library preparation for Next Generation Sequencing and running samples on an Illumina sequencer. The projects selected for this part are based on research questions of PhD students and post-doctoral fellows of the department of Molecular Genetics. In principle the experiment has not been done before, which means that the generated data is novel. The last part of the course concerns statistics and data analysis on High-Performance Computing required for transcriptome analyses. Students will analyze and draw conclusions on their own datasets and will link results to biological knowledge by using additional statistical methods. Also, based on their findings, students will be encouraged to propose ideas for further experiments. |
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Uren per week | |||||||||
Onderwijsvorm |
Hoorcollege (LC), Practisch werk (PRC), Werkcollege (T)
(All parts of this course are mandatory. During the lectures the necessary information for preforming the statistics and practicals will be explained. Missing a part without consulting the coordinator will result in not succeeding the course.) |
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Toetsvorm |
Practisch werk (PR), Presentatie (P), Verslag (R)
(Final grade is points/10 ; Part 1 ChIP-seq report/presentation (35) + Shell Scripting (5) + Practicals and logbook (10) + Final Report (35) + Oral presentation (15)) |
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Vaksoort | master | ||||||||
Coördinator | dr. A. de Jong | ||||||||
Docent(en) | dr. A. de Jong , D. Incarnato, PhD. ,prof. dr. J. Kok | ||||||||
Verplichte literatuur |
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Entreevoorwaarden | The course assumes prior knowledge acquired from Microbiology & Genetics research or equivalent. | ||||||||
Opmerkingen | Students from the degree programme Biomolecular Sciences have priority, to register please send an email to: academicadvisor.mscbio@rug.nl Course coordinator: dr Anne de Jong, anne.de.jong@rug.nl, 050 363 2047 Location: Research group Molecular Genetics (GBB), Centre for Life Sciences. Students in Biomolecular Sciences have priority for this course. capacity: 24 students |
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Opgenomen in |