Expression estimation

Keywords

GFF3, BAM, Populus-tremula, RNA-Seq, Expression-estimation

Authors

• Nicolas Delhomme (@delhomme)
• Bastian Schiffthaler (@bastian)

Type

• Lecture

Description

This introduces how to summarise short read alignments by the annotation of interest to obtain a count-table; i.e. the structure necessary to most downstream expression based analyses. Here, the focus is put on gene-expression, but the aspects of transcript-expression are briefly addressed.

Aims

Understand how to combine alignments and annotation information to generate a count table; Learn about the common pitfalls of this process

Prerequisites

• HTS-Introduction
• R-programming
• Unix

Target audience

From undergrade on, provided that the prerequisites above are fulfilled

Learning objectives

• Understand the principles of expression estimation
• Learn how to create an expression count-table from a set of alignments and annotation
• Learn about common pitfalls
• Awake the awareness about expression estimation caveats and limitations and their influence on downstream analyses

Materials

• Lecture PDF in the corresponding folder

Data

• The data availability is described in the Dataset section
• and in the corresponding course

Timing

1h (lecture)

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
• R (>=3.1), Bioconductor(>=3.0)

Literature references

• Robinson, Delhomme et al.
• Bioconductor