Computational Methods for Massively Parallel Sequencing Course
This course will provide an introduction to a wide range of analytical techniques for massively parallel sequencing. We will pair lectures on the theory of analysis algorithms with practical computational exercises demonstrating the use of common tools for analyzing data from each of several common sequencing study designs.
Topics covered will include
- alignment of reads to a reference
- variation detection
- RNA-Seq alignment and expression analysis
- ChIP-Seq alignment and enrichment analysis
- de novo assembly of both genome and transcriptome data
Analysis techniques covered will focus mostly on data from the Illumina and SOLiD platforms, but we will discuss other sequencing platforms and the advantages and challenges to using their data.
The course is open for PhD students, postdocs, researchers, and other employees in need of bioinformatic skills within all Swedish universities.
A background in genetics, cell biology, biomedicine, biochemistry, bioinformatics or comparable is desirable. Familiarity with basic linux command line will be beneficial but not expected; no programming knowledge is required.
To get the maximum benefit from the course we would like you to have
- Relevant previous experience in sequencing or analysis
- A current 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.
October 22nd. Limited to 20 participants.