This course will provide students with a holistic understanding of bioinformatics and how it can be used to analysis next generation sequencing data. The learnt skills will provide a good understand for future dry lab project or to understand bioinformatics analysis. Also the learnt skill set will be transferable, eg visualization and abstraction of data.

Lectures and tutorials will take place in semester 2.

None

None

1. Set exercise with short discussion of a genomic NGS dataset. (33.33%.) It will cover ILO 2-4

2. Analysis of transcriptomics NGS data in Linux and R. (66.66%), will cover ILO 1,2,4,5

The aim of this programme is to introduce the concepts of bioinformatics and give participants the opportunity to develop confidence and skills to perform basic bioinformatics analysis.

The students will have lectures of introduction to bioinformatics, Linux, Sequencing technologies, mapping & SNP calling, de novo assembly, bioinformatics databases, de novo assembly, metagenomics, Introduction to R and advanced R, transcriptomics (bulk/single cell), enrichment analysis, other omics technologies and introduction to machine learning in NGS. In parallel, the students will work through datasets from publication to realised how the analysis was performed. The exercise will be done in Jupyter notebooks and on a computer server.

By the end of this course students will be able to:

1. Justify and critically discuss the use bioinformatics in life sciences.

2. Use command line tools (Linux / R) to perform bioinformatics analysis

3. Critically evaluate the importance of quality control in next generation sequencing experiments

4. Critically understand the visualization possibilities of next generation sequencing results

5. Critically evaluate approaches to analyse genomic and transcriptomic experiments

Students must submit at least 75% by weight of the components (including examinations) of the course's summative assessment.