Course overview
This course teaches the underlying theory and skills for design and analysis of transcriptome sequencing/assembly experiments and datasets. This will include differential gene expression and transcript assembly. Theoretical background will cover relevant computational, statistical, and network theory, as well as the key biological processes which are under investigation. Practical analysis will involve use of relevant assembly/expression analysis software, R Studio and Bash scripting and/or a compiled programming language in the context of an HPC environment.
Course learning outcomes
- Use modern literate programming tools such as R Studio Notebooks.
- Analyse a biological question in order to develop a research analysis pipeline.
- Use a variety of publicly available data resources and software tools to perform transcriptomic analyses.
- Implement approaches to ensure reproducibility of a research analysis.
- Use and communicate statistical concepts to establish and communicate the reliability of transcriptomic analyses.
- Employ effective techniques to communicate complex research results to a non-specialist audience.
- Produce a comprehensive analytical report on a transcriptomics research problem.