Integrative OMICS

Details

Title

Integrative OMICS

Type

Stage One

Module code

HBI101

Requirement

Compulsory

Module objective

With the increase in the volume and types of data across medicine, more clinicians are looking to integrate data to generate hypotheses and clinical interpretations. For example, a clinician working in the field of metabolic medicine might want to integrate information on metabolic markers with SNP data to inform the diagnosis of a metabolic disorder. This may be public domain data (for example, public information on the phenotypic effects of variations stored in data resources such as OMIM, the Human Phenotype Ontology, Ensembl and UniProt) as well as data that the NHS has generated (for example, patient-specific genomic and metabolite data). This module will provide an overview of working with a number of -omics data types (genomic, transcriptomic, proteomic and metabolomics) in a more integrated manner, considering both their potential and caveats (for example, the dangers of over-interpretation). The module will focus on the use of different data resources and tools for enabling integrated working and data visualisation.

By the end of this module the Clinical Scientist in HSST will be able to analyse, synthesise and apply their knowledge and understanding of -omics data analysis to inform clinical decision making. They will be able to integrate public domain and patient data to associate variations in gene sequence, gene expression, regulation, or biomarker levels to inform diagnosis, predict prognosis, identify patients for clinical trials and manage therapy, in collaboration with other members of a multidisciplinary team. The Clinical Scientist in HSST will also be expected to consistently demonstrate the attitudes and behaviours necessary for the role of a CCS.

Knowledge and understanding

By the end of this module the Clinical Scientist in HSST will be able to analyse, synthesise, evaluate and critically apply their expert knowledge to integrative -omics, including:

• Ethical and governance concerns regarding data integration in the NHS.
• The minimum information standards used to capture -omics data.
• The importance of data standards and the collection of metadata in relation to genomic data.
• How to identify and critically evaluate public sources of data for integration of -omics data.
• How to devise, evaluate and use workflows to enable the appropriate capture of metadata from domain experts in a clinical setting.
• The advantages and limitations of different strategies for large-scale data integration.
• How to identify biological pathways in which genes, gene products and small molecules could participate using the published literature and bioinformatics resources.
• How to identify biological pathways that play a role in a specific disease process using the published literature and bioinformatics resources.
• How to evaluate strategies for determining whether a pathway is over-represented in a set of genes, gene products, or small molecules.

Technical and clinical skills

By the end of this module the Clinical Scientist in HSST will have a critical understanding of current evidence and its application to the performance and mastery of a range of technical skills and will:

• Devise, evaluate and use workflows to enable the appropriate capture of metadata from domain expertsi in a clinical setting.
• Compare the advantages and limitations of different strategies for large-scale data integration and apply these appropriately to different clinical scenarios.
• Critically evaluate the literature and bioinformatics resources to identify biological pathways in which genes, gene products and small molecules could participate, and use the outcome to inform diagnosis and/or patient management.
• Critically evaluate the literature and bioinformatics resources to identify biological pathways that play a role in a specific disease process and use the outcome to inform diagnosis and/or patient management.
• Master strategies for determining whether a pathway is over-represented in a set of genes, gene products, or small molecules and use this to inform diagnosis.
• Master the use of ontologies to improve the interoperability of data resources, with the goal of making better use of pre-existing data to inform clinical decision making.
• Apply and evaluate bioinformatics tools to integrate and visualise biological data, with the goal of creating more informative and intuitive tools and resources to aid clinical decision making.
• Identify a clinical bioinformatics requirement and develop, validate and deploy a bespoke workflow for clinical diagnostic analysis in the context of integrative -omics.
• Contribute to community annotation through ontology, and develop best practice guidelines in this area, identifying clinical specialists to inform this work as appropriate to the work.

By the end of this module the Clinical Scientist in HSST will be expected to critically reflect and apply in practice a range of clinical and communication skills with respect to clinically relevant – omics data. The Clinical Scientist will communicate effectively with the public, patients, clinicians, academics and other healthcare professionals and will:

• Drive discussion and strategy around use of -omics data to improve clinical management.
• Effectively communicate clinically applicable advances in the analysis, visualisation and interpretation of -omics data to the scientific and clinical community.
• Effectively communicate clinically applicable advances in the analysis, visualisation and interpretation of -omics data to patients, their families and the public.

In addition, Clinical Scientists in HSST will be aware of their own attitudes, values, professional capabilities and ethics, and critically reflect on: (i) their professional practice; and (ii) the challenges of applying research to practice in relation to these areas of practice, identifying opportunities to improve practice building on a critique of available evidence.