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