PhD Course: Analysis of Next Generation Sequencing Data
The course includes a combination of lectures and practical sessions where participants are directly performing bioinformatics analysis of NGS data. From raw data (fastq files) to variant analysis (DNA sequencing), differential gene expression analysis (RNA sequencing) and pathway analysis. We focus on developing practical skills; therefore, you need to have experience in the Linux environment. Experience in R is not mandatory but recommended.
| Hours (HP): | 54 (2,0) |
| Code (s): | SC00024 |
| Weeks (s): | 43-47 |
The following topics covered are:
- Experimental design
- NGS quality assessment
- SNP analysis in targeted resequencing
- Differential gene analysis from RNAseq data
- Downstream analysis such as pathway analysis, clustering and gene ontology
Notes
The course comprises 54 working hours where you are expected to spend time of your own to complete the exercises (self-studies).
Participants are required to bring their own computer with the corresponding administrator rights.
Course Prerequisites
Experience within the Linux environment is a requirement. An entry assignment must be completed to be accepted.
If you are a Linux beginner or have not worked in this environment we recommend taking our "Unix applied to genomic data" course.
Experience with R programming is recommended. If you are a beginner or have not worked in this environment we recommend you take our "R programming" course.