Quality Control
Quality Control
Keywords
FASTQ, RNA-Seq, Pre-processing, QC
Authors
- Nicolas Delhomme (@delhomme)
- Bastian Schiffthaler (@bastian)
Type
- Lecture
Description
This is an introduction to the tools available for performing the technical QA of RNA-Seq data and to their results, singling out possible common caveats.
Aims
Understand the principles of an RNA-Seq analysis. Learn about data pre-processing and Quality Assessment.
Prerequisites
- HTS-introduction
- Unix
Target audience
From undergrade on, provided that the prerequisites above are fulfilled
Learning objectives
- Learn the principle of an RNA-Seq QA analysis
- Learn about the existing solutions to perform such an analysis
- Learn about the shortcomings about these solutions
Materials
- Lecture PDF and associated R examples in the corresponding folder
Data
- The data availability is described in the Dataset section
- and in the corresponding course
Timing
1h (lecture) + 2h (practical)
Content stability
Stable
Technical requirements
- Best is to use our Docker (a self contained environment) based on the Bioconductor NGS Docker that can be used to setup the course machines (physical or in the cloud)
- Otherwise:
- a UNIX OS
- FastQC
- SortMeRna (>= 1.9)
- Trimmomatic (>=0.32)
Literature references
- Robinson, Delhomme et al.
- SortMeRna
- Trimmomatic
Keywords: FASTQ, RNA-Seq, Pre-processing, QC
Scientific topics: RNA-Seq
Activity log