RNA-Seq analysis for differential expression

Goals

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

Summary

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
• STAR
• samtools
• Picard
• RSeQC
• HTSeq
• R - RStudio - Bioconductor - various packages
 

Requirements

 
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
 

Schedule

.Organised by the VIB Bioinformatics Core​
 
 
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Dates:

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

Location:

Leuven
Park Inn by Radisson Leuven
Martelarenlaan 36
3010 Leuven

Trainer:

Janick Mathys and Guy Bottu
Registration is closed.

Registration start date:

29 October 2018

Registration end date:

28 January 2019