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

Authors: Nicolas Delhomme @delhomme, Bastian Schiffthaler @bastian

Scientific topics: RNA-Seq


Activity log