Introduction to bioinformatics using NGS data (Online)

National course. The course is open for current and potential facility users such as PhD students, postdocs, group leaders and core facility staff in need of bioinformatic skills within all Swedish universities.  

This course is supported by SciLifeLab and run by the SciLifeLab National Bioinformatics Infrastructure Sweden (NBIS) 

IMPORTANT INFORMATION DUE TO COVID-19

2020-09-23 update: 
Due to the COVID-19 situation this course will be held online

Please contact edu.intro-ngs@nbis.se for general questions and  edu.intro-ngs@nbis.se for course specific questions.

Important dates

Application CLOSED

Confirmation to accepted students:  September 25, 2020

Responsible teachers:  Malin Larsson, Martin Dahlö, Roy Francs

Course fee 

No course fee will be invoiced for online courses. However, if you accept a position at the course and do not participate (no-show) you will be invoiced 2000 SEK.
*Please note that NBIS cannot invoice individuals

Course content

This intense one week course provides an introduction to the analysis of next generation sequencing data. Lectures on the theory of concepts will be paired with practical computational exercises in the Linux environment. The practical exercises will focus on data from the Illumina platform, but we will discuss other sequencing platforms and the advantages and challenges to using their data during the lectures.

After this course you should be able to:

• Describe the basic principles of next generation sequencing. 
• Use the Linux command line interface to manage simple file processing operations, and organize directory structures. 
• Connect to and work on a remote high performance compute cluster.
• Apply programs in Linux for analysis of NGS data.
• Describe the applications of different NGS technologies, and including the weakness and strengths of the approaches. 
• Explain common NGS file formats.
• Interpret quality control of NGS reads.
• Explain the steps involved in variant calling using whole genome sequencing data.
• Independently perform a basic variant calling workflow on example data.
• Explain the steps involved in differential gene expression using RNA seq data.
• Independently perform differential gene expression analysis on example data. 
• Be aware of good data management principles including “FAIR” data. 

Entry requirements

A background in genetics, cell biology, biomedicine, biochemistry, bioinformatics or comparable is desirable. To get the maximum benefit from the course we would like you to

• Have relevant previous experience in sequencing or analysis.
• Have a research project where you are currently using next generation sequencing or are planning to use next generation sequencing.
• It is beneficial if you are directly performing analyses or if you have a support role and will be able to participate in a wide range of projects and transfer your knowledge to others.

You need to bring your own laptop for the practical computational exercises.

Selection criteria include correct entry requirements, motivation to attend the course as well as gender and geographical balance.

Link to application

Application CLOSED