Learning Objectives and Course Pre-requisites
Learning Objectives
Course participants will go through a series of experiences that utimately lead to create enhanced capabilities to:
- List broad characteristics of NGS technologies and choose adequate sequencing for your biological question
- Have a broad overview of the steps in the analysis of RNA-Seq differential expression experiments
- Assess the general quality of the raw data from the sequencing facility
- Do simple processing operations in the raw data to improve its quality
- Generate alignments against a reference genome
- Assess the general quality of the alignments and detect possible problems
- Generate tables of counts using the alignment and a reference gene annotation
- Generate lists of differentially expressed genes, at least for a simple pairwise comparison
- Understand specificies of differential gene expression in the case of single-cell RNAseq
- Perform simple functional enrichment analysis and understand the concepts behind them
For this, we are providing small example datasets and exercises that participants can use to learn.
Course Pre-requisites
Familiarity with elementary statistics and a few basics of scripting in R will be helpful.
Please have a look at the following resources and gauge your ability to use R in statitics at the basic level: Coursera videos; Introduction to r
Basic Unix command line skills, such as being able to navigate in a directory tree and copy files. See, for example, “Session 1” of the Software Carpentry training for a Unix introduction.
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