Overview

The rapidly development of Genomic technologies means that we are capable of producing vast quantities of data. Bioinformatics, a discipline that combines the skills of computer science and biology, is critical to converting this data into usable information. Such information can be used to develop targeted personalised therapies for such diseases as cancer, identify rare diseases and monitor infectious organisms as they as transmitted through populations. This module will introduce the bioinformatic approaches within genomics as applied to healthcare.

Topics will be presented via lectures, seminars, study groups work-based learning and tutorials. The syllabus will include topics such as:

• Genomic data flow from the patient through to the laboratory, to the clinician and then back to the patient.
• The assessment of data quality through application of quality control and statistical measures.
• How to align genome data to a reference sequence using up-to-date alignment algorithms.
• Measures to determine the analytical sensitivity and specificity of genomic tests.
• Tools to call sequence variants and annotate variant-call files using established resources.
• The use of multiple database sources, data integration tools, clinical literature and statistical evidence to prioritise variants for pathogenicity.
• Principles that apply to the integration of laboratory and clinical information, and the place of best practice guidelines for indicating the clinical significance of results.
• Approaches for assessing the functional effect of variants and basic statistical concepts, including probability and hypothesis testing.
• The relationship between data and information, and secure information exchange between professionals.

Assessment Strategy

-threshold -Pass (C- to C+) (range 50-59%)Primary criteriaA pass level demonstrates knowledge and comprehension of key areas & principles, with understanding of the main elements of the subject area, although gaps and weaknesses in the argument are evident. No real evidence of background study and wider reading is evident. Answers are focussed on questions but also with some irrelevant material and weaknesses in structure & argument. Answers have several factual/computational errors. Lack of originality and interpretation. No links between topics are described. Limited problem solving skills. Some weaknesses in presentation accuracy & delivery.Secondary CriteriaC+ Good within the class - Exceeds expectations for some primary criteria - Strong factual knowledge with some weaknesses in understanding - Ideas/arguments are limited but are well presentedC Mid-level - Matches all primary criteria - Moderate factual knowledge with some weaknesses in understanding - Ideas/arguments are limited presented with weaknesses in logic/presentationC- Meets requirements of class - Matches most but not all primary criteria - Moderate factual knowledge with several weaknesses in understanding - Ideas/arguments are limited presented with weaknesses in logic/presentation

-good -Merit (B- to B+) (range 60-69%)Primary criteriaGood students demonstrate strong knowledge & understanding of most but not all of the subject area. Limited evidence of background study. The answers are focussed with good structure. Arguments are presented coherently, mostly free of factual/computational errors. Some limited original interpretation. Well know links between topics are described. Problems are addressed by existing methods/approaches. Good presentation with accurate communicationSecondary CriteriaB+ Good - Exceeds expectations for most primary criteria - Command of subject but with gaps in knowledge - Some ideas/arguments originalB Mid-level - Meets all primary criteria - Strong factual knowledge and understanding - Ideas/arguments are well presented by few are originalB- Meets requirements of class - Meets most but not all primary criteria - Strong factual knowledge with minor weaknesses in understanding - Most but not all ideas/arguments are well presented and few are original

-excellent -Distinction (A- to A) (range 70-100%)Primary criteriaComprehensive knowledge & detailed understanding. Clear evidence of extensive background study & originality. Highly focussed, relevant and well structured answers. Arguments logically presented and defended with evidence and examples. Excellent presentation skills with very accurate communication.Secondary CriteriaA Outstanding - Exceeds expectations for most primary criteria - Complete command of subject and other relevant areas - Ideas/arguments are highly originalA+ Excellent - Exceeds expectations for some primary criteria - Complete command of subject - Ideas/arguments are highly originalA Good - Meets all primary criteria - Command of subject but with minor gaps in knowledge areas - Ideas/arguments are mostly originalA- Meets requirements of Class - Meets most but not all primary criteria - Complete command of subject but with some gaps in knowledge - Ideas/arguments are mostly original

Learning Outcomes

• Ability to use data integration tools and statistical concepts to understand clinical relevance of different forms of genomic data.

• Assess data quality using standard methodologies and appraise the importance of these methods in relation to genomic data.

• Demonstrate a critical understanding of the practical issues of genomic data transfer between laboratory and patient including the principles that apply to the integration of laboratory and clinical information.

• Successfully align genomic data and use tools to interpret clinically relevant data.