LQN202 Genomics Analysis
To view more information for this unit, select Unit Outline from the list below. Please note the teaching period for which the Unit Outline is relevant.
| Unit code: | LQN202 |
|---|---|
| Credit points: | 12 |
| Timetable | Details in HiQ, if available |
| Availabilities |
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| Domestic tuition unit fee | $3,744 |
| International unit fee | $5,148 |
Unit Outline: Semester 2 2025, Online
| Unit code: | LQN202 |
|---|---|
| Credit points: | 12 |
| Coordinator: | Fiona Rae | f.rae@qut.edu.au |
Overview
This unit covers the application of array technology and massively parallel sequencing data processing to identify variants. In addition, the tools available to assist with variant interpretation and classification are examined. Not only do genomic scientists need in-depth knowledge of these platforms, but so do clinicians requesting and receiving results of genetic tests in order to advise and manage patients.
Learning Outcomes
On successful completion of this unit you will be able to:
- Critique the theoretical assumptions of methodologies designed to identify causative variants and polymorphisms associated with common disease.
- Evaluate the different types of array, long read and massively parallel sequencing technologies, explain their methodologies and their ability to detect genetic aberrations.
- Accurately apply the ACMG/AMP guidelines to classify genetic variants, interpret evidence categories and critically evaluate the clinical significance of genomic findings in a diagnostic or research setting.
- Generate scientific reports interpreting the results massively parallel sequencing technologies addressing and explaining the significance of findings.
Content
- Heritability of simple and complex traits in relation to disease
- Key polymorphic concepts including variants, mutations, SNP, CNV, haplotype, genotype
- Genome-wide association study arrays and diagnostic SNP arrays (both for linkage and mutation detection)
- How SNPs and CNVs are measured and detected using diagnostic arrays
- The processing of MPS data including the demultiplexing of samples, alignment of sequence data, variant calling data annotation (minor allele frequency, mutational consequence using in silico prediction tools), using variant web-based databases to determine the presence of the variant in control and disease populations
- Interpreting novel sequence variants using in silico analysis (Polyphen, SIFT, Align-GVGD, splice prediction algorithms), population frequency databases (gnomAD), variant databases, published literature and how to classify variants using the ACMG/AMP Class 1-5 system of pathogenicity
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Applied training using industry-standard variant interpretation software
Learning Approaches
This unit is designed to introduce you to the core concepts of genomics analysis. The online delivery is through Canvas. The unit is developed around the principles of adult learning, theory and practice and open learning guidelines. This predominantly, asynchronous learning environment allows you to go through lectures, materials and exercises at your own pace.
The Canvas site will provide you with resources including pre-recorded lectures, research papers, media articles and videos. You will also be able to access online meetings, interactive exercises and online message boards. There will be at least one webinar or video-conferencing in which a concept is explained and students will be expected to solve a problem or discuss approaches to a case during the virtual class.
Canvas will facilitate your ongoing conversations with other students and with academic staff. Guidance will be provided for you in terms of appropriate self-pacing of your study during the semester. You will be expected to engage in online discussions and complete formative assessment tasks to consolidate your learning.
You will be encouraged to read widely and to think critically about the nature and scope of how genomics analysis relates to the field of diagnostic genomics.
Feedback on Learning and Assessment
The online webinars and discussion boards are the key places you can ask for and receive feedback on your understanding of course materials. Feedback on assessment 1 and assessment 2 will be given regarding your analytical skills, ability to identify resources, reasoning and ability to interpret and summarise your findings. Each assessment item will include individual feedback on your progress as stated above and feedback will be offered to the group through the Announcements page on the Canvas site.
Assessment
Overview
There are two summative assessment items in LQN202. Assessment 1 is a literature review task for you to synthesise the knowledge gained during this unit and translate it into a critical analysis. Assessment 2 is a report which requires you to use a variety of online tools and software and write reports on the interpretation of variants identified using high-throughput genomic technologies.
Unit Grading Scheme
7- point scale
Assessment Tasks
Assessment: Literature Review
This assessment is based upon a case of an undiagnosed genetic disease. You will be asked to write a literature review reviewing the merits of using different types of massively parallel sequencing, and the probability of identifying a diagnosis using each technology.
This assignment is eligible for the 48-hour late submission period and assignment extensions.
Assessment: Report
In this assessment, you are a laboratory scientist and have been given a number of variants which have been identified using whole-exome sequencing in known disease-associated genes. You will need to use in silico analysis, control and variant databases, along with the published literature to classify the pathogenicity of the variant using the ACMG-AMP guidelines and industry software. You are to write a report for your supervisor outlining your classification of the variants and your reasoning behind assigning such a classification.
This assignment is eligible for the 48-hour late submission period and assignment extensions.
Academic Integrity
Academic integrity is a commitment to undertaking academic work and assessment in a manner that is ethical, fair, honest, respectful and accountable.
The Academic Integrity Policy sets out the range of conduct that can be a failure to maintain the standards of academic integrity. This includes, cheating in exams, plagiarism, self-plagiarism, collusion and contract cheating. It also includes providing fraudulent or altered documentation in support of an academic concession application, for example an assignment extension or a deferred exam.
You are encouraged to make use of QUT’s learning support services, resources and tools to assure the academic integrity of your assessment. This includes the use of text matching software that may be available to assist with self-assessing your academic integrity as part of the assessment submission process.
Breaching QUT’s Academic Integrity Policy or engaging in conduct that may defeat or compromise the purpose of assessment can lead to a finding of student misconduct (Code of Conduct – Student) and result in the imposition of penalties under the Management of Student Misconduct Policy, ranging from a grade reduction to exclusion from QUT.
Resources
In addition to online lecture notes, a selection of online textbooks, journal articles, and internet resources will be made available each week through the QUT Library.
Risk Assessment Statement
There are no out of the ordinary risks associated with this unit.
Course Learning Outcomes
This unit is designed to support your development of the following course/study area learning outcomes.LS72 Graduate Diploma in Diagnostic Genomics
- Apply scientific knowledge and skills, focused on current genomic trends in practice and research, utilising digital capabilities.
Relates to: ULO1, ULO2 - Critically evaluate scientific findings and locate solutions to solve complex genomics problems, employing high order cognitive skills, clinical reasoning, and reflective practice.
Relates to: ULO2, ULO3, ULO4 - Develop and apply professional oral and written communication skills that inform effective collaboration and digital interactions with colleagues and other stakeholders across the medical and scientific contexts.
Relates to: ULO4 - Practise within a framework of personal accountability, collegiality and ethical judgment, while valuing cultural safety and sensitivity in professional practice, clinical decision-making and research.
Relates to: ULO3, ULO4
LS81 Master of Diagnostic Genomics
- Apply scientific knowledge and skills, focused on current genomic trends in practice and research, utilising digital capabilities.
Relates to: ULO1, ULO2, Literature Review, Report - Critically evaluate scientific findings and locate solutions to solve complex genomics problems, employing high order cognitive skills, clinical reasoning, and reflective practice.
Relates to: ULO2, ULO3, ULO4, Literature Review, Report - Develop and apply professional oral and written communication skills that inform effective collaboration and digital interactions with colleagues and other stakeholders across the medical and scientific contexts.
Relates to: ULO4, Report - Practise within a framework of personal accountability, collegiality and ethical judgement, drawing upon Indigenous perspectives, cultural safety and sensitivity in professional practice, clinical decision-making and research.
Relates to: ULO3, ULO4