MSc Health Data Science / Course details

This module will engage students in an emerging area of biomedical/clinical research where data science skillsets can be applied in a healthcare setting. This module will offer unique training in 'multi-omics' in the context of health data science. 

This unit aims to

• Introduce students to the concept of ‘multi-omics’ (analysis of more than 1 ‘omic’ datasets) research, its potential benefits for future healthcare, particularly in personalised medicine, as well as the challenges of working with multi-omic data.
• Introduce the methods of integrating multi-modal datasets and key data sciences concepts that are applied in multi-omics research.
• Encourage students to understand the current research landscape in the multi-omics field and propose future health innovations with the application of multi-omic approaches.

Key themes

• Introduction to omic data and non-omic data (biomedical or health data) – systems biology/medicine. Purpose of multi-omic and multi-modal studies. Sample types/sources of biological data.
• Introduction to omic databases. Other non-omic datasets that can be analysed in combination with omic data e.g. clinical, pharmacological/toxicology data, histology, imaging data.
• Multi-omic study design - sample collection, cohort design, pairing of omic datasets. 
• Targeted vs non-targeted approaches.
• Methods of data integration – how to integrate multi-omics and multi-modal datasets for further analyses.
• Skills/tools for multi-omic data analyses - introduction to bioinformatics, statistical, ML and programming skills in the context of multi-omic analyses. R/Python packages, software/tools that can be used for multi-omic research.
• Omics for healthcare – case studies; role in personalised medicine
• Future innovations using multi-omic data and associated challenges – potential innovations/technologies in the near/long-term future.

This module will be delivered in a ‘blended’ format. Teaching material, including lectures, will be available online prior to face-to-face teaching sessions or online tutorials. Group activities (formative assessments with feedback from tutors and peers) will be facilitated during F2F sessions to consider and reflect on a range of topics in the ‘multi-omics’ field. All activities will help build knowledge towards the end of module final assessment.

A1 Describe different examples of ‘omics’ data and the term ‘multi-omics’

A2 Understand multi-omic study designs and how this can impact analysis approaches

A3 Identify examples of ‘omic’ databases and recognise the type of omic data they store

A4 Learn what data science approaches can be utilised in multi-omics studies

B1 Demonstrate an appreciation of the analysis approaches may be suitable in the context of different multi-omic studies

B2 Critically appraise multi-omic studies, technologies, software and approaches in the literature

Perform and communicate literature search in multi-omics health/biomedical research or data science/analysis approaches.

Application of data analysis skills on omic datasets via practical exercises. 

D1 Work collaboratively in a team

D2 Communicate and present ideas on 'health innovation' using multi-omic data

Books / Journals

https://www.ncbi.nlm.nih.gov/books/NBK202168/

Cavill, R., Jennen, D., Kleinjans, J., & Briedé, J. J. (2016). Transcriptomic and metabolomic data integration. Briefings in bioinformatics, 17(5), 891–901. https://doi.org/10.1093/bib/bbv090

Krassowski Michal, Das Vivek, Sahu Sangram K., Misra Biswapriya B. (2020). State of the Field in Multi-Omics Research: From Computational Needs to Data Mining and Sharing. Frontiers in Genetics, 11. https://www.frontiersin.org/article/10.3389/fgene.2020.610798

Subramanian, I., Verma, S., Kumar, S., Jere, A., & Anamika, K. (2020). Multi-omics Data Integration, Interpretation, and Its Application. Bioinformatics and biology insights, 14, 1177932219899051. https://doi.org/10.1177/1177932219899051

Websites

https://www.gov.uk/government/publications/genome-uk-the-future-of-healthcare/genome-uk-the-future-of-healthcare