Introduction to RNA-seq analysis 2014

Introduction to RNA-seq analysis 2014

Keywords

Alignment, Differential-expression, Feature-summarisation, Pre-processing, QC

Authors

Frederik Coppens (@frcop)

Type

  • Lecture

Description

This lecture gives an overview how to perform an RNA-seq experiment. A general RNA-seq workflow is outlined when a good quality genome sequence is available for your species.

Aims

The aim is that participants are aware of the general steps in an RNA-seq experiment and are able to identify appropriate tools for each step. For each step the most important features, some tools and things to be aware of are listed.

Prerequisites

  • None

Target audience

beginner, biologist

Learning objectives

  • list steps of an RNA-seq analysis
  • discuss QC of raw data
  • decide which alignment approach is appropriate for your use case
  • discuss quality of alignment
  • recognise the importance of appropriate statistical methods for differential expression

Materials

  • Slides in pdf.

Data

  • not applicable

Timing

2h

Content stability

Stable

Technical requirements

  • FastQC
  • FastX toolkit
  • Cutadapt
  • Trimmomatic
  • GSNAP
  • Bowtie
  • TopHat
  • Samtools
  • HTseq
  • edgeR
  • DESeq
  • Cufflinks

Literature references

  • to do

Changelog

  • 2015-08-25: Added links to tools
  • 2015-02-19: Upload to gitlab

Comments

  • I did not check if the use of all figures is allowed or properly acknowledged.
  • A license needs to be added

Keywords: Alignment, Differential-expression, Feature-summarisation, Pre-processing, QC

Authors: Frederik Coppens @frcop

Introduction to RNA-seq analysis 2014 https://tess.elixir-europe.org/materials/introduction-to-rna-seq-analysis-2014 This lecture gives an overview how to perform an RNA-seq experiment. A general RNA-seq workflow is outlined when a good quality genome sequence is available for your species. Alignment, Differential-expression, Feature-summarisation, Pre-processing, QC