RNA-Seq analysis for differential expression


You will execute a complete analysis workflow in GenePattern, Galaxy or command line and R to detect differential expression between two conditions


We'll go through the different steps of the workflow:

  • Quality control of the sequence reads to detect biases or contaminating adapters.
  • Mapping of the reads to the reference genome with use of a transcript database model.
  • Quality control  of the mapping results.
  • Adjusting the mapping data to compensate for artefacts like duplicates.
  • Calculate transcript counts usable for differential expression and merging of count tables 
  • Computing differential expression using  DESeq2.

Covered tools

• fastQC
• trimmomatic
• Groomer
• samtools
• Picard
• HTSeq
• R - RStudio - Bioconductor - various packages


Familiarity with
  • the Illumina sequencing process
  • basic NGS data formats: FASTQ, SAM/BAM, GTF, ...
  • R syntax
To meet these requirements you can follow the "Introduction to NGS data analysis​" training and the Basic statistics in R ​training.

Topics NOT covered

  • RNA-seq assembly
  • RNA-seq analysis for isoform detection
  • RNA-seq analysis for detection of short RNA species


.Organised by the VIB Bioinformatics Core​


11 and 18 February 2019, from 9h30 to 17h00


Park Inn by Radisson Leuven
Martelarenlaan 36
3010 Leuven


Janick Mathys and Guy Bottu
Registration is closed.

Registration start date:

29 October 2018

Registration end date:

28 January 2019