Alignment
Alignment
Keywords
BAM, Populus-tremula, RNA-Seq, QC, Alignment
Authors
- Nicolas Delhomme (@delhomme)
- Bastian Schiffthaler (@bastian)
Type
- Lecture
Description
Introduction to short-read alignments, including a general overview of existing methods (Burrow-Wheeler-Transform, Maximum Mappable Prefix, etc.) and some cautionary tales.
Aims
Understand the principles of short read alignments; Learn about the shortcomings of such methods; Learn about how these might affect downstream analyses
Prerequisites
- HTS-Introduction
- R-programming
- Unix
Target audience
From undergrade on, provided that the prerequisites above are fulfilled
Learning objectives
- Learn the principles of short read alignment
- Learn about the different mainstream approaches to short read alignment
- Learn about the shortcomings and caveats of short read alignment
- Learn how to apply short read aligners to one own's data
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. The analysis has been conducted using the Populus trichocarpa sister species and might only get updated once the Populus tremula genome sequence and annotation are released, which may happen by the end of 2015.
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)
- STAR (>=2.4.0)
Literature references
- Robinson, Delhomme et al.
- SortMeRna
- Trimmomatic
- STAR
Keywords: BAM, Populus-tremula, RNA-Seq, QC, Alignment
Scientific topics: RNA-Seq
Activity log