Course description
The course includes a combination of lectures and practical sessions where participants are directly performing bioinformatics analysis on NGS data. We focus on developing practical skills beyond the quality assessment of raw data; therefore, you need to have experience within the linux environment.
Topics covered include: quality assessment, SNP analysis in targeted resequencing, differential gene analysis and downstream analysis such as pathway analysis, clustering and gene ontology.
The course will be given in English.
Participans are required to bring their own computer and have the corresponding adminstrator rights
Tentative schedule: please see "Link to website".
Requirements and Selection
Entry requirements
Admitted to postgraduate education.
To be able to follow the course you should have:
- a background in genetics, cell biology, biomedicine, biochemistry, bioinformatics or similar,
- a research project where you are currently using next generation sequencing or are planning to use next generation sequencing.
You must have experience within linux environment.
The course is an elective course within the third cycle at Sahlgrenska Academy.
Selection
Selection is performed according to the following:
- PhD students at Sahlgrenska Academy,
- PhD students enrolled at another university within a formal collaborative agreement on doctoral education with Sahlgrenska Academy,
- PhD students enrolled at another faculty at the University of Gothenburg or another university in Sweden,
- PhD students enrolled at a university outside Sweden.
Other information
Course coordinator: Subazini Thankaswamy, subazini@gu.se
Course administrator: Zerif Olsen, zerif.olsen@gu.se
Course dates: 20 October - 14 November 2025
Teaching: Mondays half days
Selfstudies: 6-8 hours per week
Examination: Friday, 14 November 2025
Number of course places: 7-20
Link to website
https://www.gu.se/en/core-facilities/courses-for-phd-students-by-core-facilities
Course syllabus
SC00024
Department
Core Facilities
Subject
Health Sciences
Type of course
Method course
Keywords
NGSD, analysis of NGS data, genexpression, pathway analysis