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Statistical Genomics (POPH90124)
Graduate courseworkPoints: 12.5Online
About this subject
- Overview
- Eligibility and requirements
- Assessment
- Dates and times
- Further information
- Timetable (login required)(opens in new window)
Contact information
Semester 2
Melbourne School of Population and Global Health
OR
Currently enrolled students:
- General information: https://ask.unimelb.edu.au
- Email: Contact Stop 1
Future Students:
- Further Information: https://study.unimelb.edu.au/
Overview
| Availability | Semester 2 - Online |
|---|---|
| Fees | Look up fees |
Statistical genomics is the application of statistical methods to understand genomes, their structure, function and evolutionary history, in many different scientific contexts, including: understanding biological mechanisms in health and disease, predicting outcomes and identifying individuals and their relatedness. Bioinformatics is an overlapping term that suggests more emphasis on data management and software pipelines. The course will also cover aspects of Genomic epidemiology, an overlapping field in which statistical genomics methods are used with family or population data to study causes of disease.
Intended learning outcomes
Knowledge
Upon completion of this subject, students should be able to:
- Describe core mechanisms of genetics, including mutation, recombination and selection;
- Explain the concept of heritability and its estimation; and
- Explain key features of data and statistical models used in the fields of transcriptomics, epigenetics, microbiome analysis and phylogenetics.
Skills
Upon completion of this subject, students should be able to:
- Use the Wright-Fisher and coalescent models of population genetics for simulation and inference;
- Perform sequence analysis using hidden Markov models;
- Perform a genetic association analysis, including the assessment of possible confounding; and
- Access and interpret genomic data from public online resources.
Apply Knowledge & Skills
Upon completion of this subject, students should be able to:
- Use genome-wide SNP data to develop prediction models.
Generic skills
On completion students should have developed independent problem solving, facility with abstract reasoning, clarity of written expression, sound communication of technical concepts.
Last updated: 31 January 2024
Eligibility and requirements
Prerequisites
Prerequisites
| Code | Name | Teaching period | Credit Points |
|---|---|---|---|
| MAST90101 | Introduction to Statistical Computing | Semester 1 (Dual-Delivery - Parkville) |
12.5 |
| MAST90100 | Probability & Inference in Biostatistics | Semester 1 (Dual-Delivery - Parkville) |
12.5 |
| MAST90102 | Foundations of Regression | July (Dual-Delivery - Parkville) |
12.5 |
Corequisites
None
Non-allowed subjects
None
Inherent requirements (core participation requirements)
The University of Melbourne is committed to providing students with reasonable adjustments to assessment and participation under the Disability Standards for Education (2005), and the Assessment and Results Policy (MPF1326). Students are expected to meet the core participation requirements for their course. These can be viewed under Entry and Participation Requirements for the course outlines in the Handbook.
Further details on how to seek academic adjustments can be found on the Student Equity and Disability Support website: http://services.unimelb.edu.au/student-equity/home
Last updated: 31 January 2024
Assessment
| Description | Timing | Percentage |
|---|---|---|
Assignment 1. Mixture of short answer and simulation using R, with interpretation.
| Week 3 | 20% |
Assignment 2. Mixture of short answer, data analysis, simulation using R, with interpretation.
| Week 7 | 20% |
Assignment 3. Mixture of short answer, data analysis and/or simulation using R, with interpretation.
| Week 11 | 20% |
Take-home exam. Mixture of short essay, data analysis and/or simulation using R, with interpretation. Retrieval and interpretation of online genomics resources.
| During the examination period | 40% |
Last updated: 31 January 2024
Dates & times
- Semester 2 - Online
Coordinator Agus Salim Mode of delivery Online Contact hours Total time commitment 170 hours Teaching period 22 July 2024 to 20 October 2024 Last self-enrol date 2 August 2024 Census date 2 September 2024 Last date to withdraw without fail 20 September 2024 Assessment period ends 15 November 2024 Semester 2 contact information
Melbourne School of Population and Global Health
OR
Currently enrolled students:
- General information: https://ask.unimelb.edu.au
- Email: Contact Stop 1
Future Students:
- Further Information: https://study.unimelb.edu.au/
What do these dates mean
Visit this webpage to find out about these key dates, including how they impact on:
- Your tuition fees, academic transcript and statements.
- And for Commonwealth Supported students, your:
- Student Learning Entitlement. This applies to all students enrolled in a Commonwealth Supported Place (CSP).
Subjects withdrawn after the census date (including up to the ‘last day to withdraw without fail’) count toward the Student Learning Entitlement.
Last updated: 31 January 2024
Further information
- Texts
Prescribed texts
Recommended texts and other resources
The Handbook of Statistical Genomics, D Balding, J Marioni, I Moltke Eds, 4th edition, Wiley 2019. Available online or in print.
Special Computer Requirements: "R" (freeware - coordinator will give instructions on how to download)
Resources Provided to Students: Printed course notes and assignment material will be provided to students via post.
- Subject notes
This subject is delivered online via our partners in the Biostatistics Collaboration of Australia (www.bca.edu.au). It is not generally available in the Master of Public Health nor in any program outside the Melbourne School of Population and Global Health (MSPGH).
- Related Handbook entries
This subject contributes to the following:
Type Name Course Graduate Diploma in Biostatistics Course Master of Biostatistics - Links to additional information
Last updated: 31 January 2024