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Advanced Statistical Genomics (MAST90126)
Graduate courseworkPoints: 12.5Dual-Delivery (Parkville)
Please refer to the return to campus page for more information on these delivery modes and students who can enrol in each mode based on their location.
About this subject
- Overview
- Eligibility and requirements
- Assessment
- Dates and times
- Further information
- Timetable(opens in new window)
Contact information
Semester 2
Overview
Availability | Semester 2 - Dual-Delivery |
---|---|
Fees | Look up fees |
The subject will cover statistical analysis of data arising from modern genomics, and their practical application using R and specialist software. RNA-seq, epigenomics and metagenomics assays will be introduced, together with properties of the resulting data, appropriate pre-analyses and advanced statistical methods and algorithms. Methods for biomarker discovery, including supervised learning and multivariate analysis techniques will also be covered, as will statistical models and techniques for phylogenetics.
Intended learning outcomes
On completion of this subject, students should have:
- Knowledge of available public data resources in genomics and the principles and practice of data access and (for human data) privacy
- Knowledge of key genomics assays for transcriptomics, epigenomics and metagenomics, the corresponding data analysis challenges and the principle approaches to inference
- An understanding of core techniques in multivariate statistics (including principal components analysis, partial least squares, factor analysis and multivariate regression analysis) and the ability to apply them to high-dimensional genomics data in a suitable software package
- An understanding of the principles of biomarker discovery, and the main machine learning/statistical techniques for biomarker discovery and validation
- Knowledge of the principal statistical/evolutionary models for DNA sequences, and their application in phylogenetics analyses
Generic skills
- In addition to learning specific skills that will assist students in their future careers in science, they will have the opportunity to develop generic skills that will assist them in any future career path. In particular: - computer-based data handling and statistical analysis of large data sets using the R software - ability to read, understand, modify and use computer programs for the manipulation of large data sets - time-management: completing assignments according to deadlines while making judgments about time required for different parts of the assessment
Last updated: 31 January 2024
Eligibility and requirements
Prerequisites
Code | Name | Teaching period | Credit Points |
---|---|---|---|
MAST30033 | Statistical Genomics | Semester 2 (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 |
---|---|---|
2 written assignments, maximum 10 pages each (equivalent to approximately 1000 words each), due early and mid semester
| First half of the teaching period | 40% |
Final project, maximum 15 pages with oral exam, project due week 12 and oral exam held in examination period
| End of the teaching period | 60% |
Additional details
This Dual-Delivery subject has On Campus assessment components.
Last updated: 31 January 2024
Dates & times
- Semester 2
Coordinator Heejung Shim Mode of delivery Dual-Delivery (Parkville) Contact hours 2 x 1-hour lectures each week and 6 x 2-hour practical (computer laboratory) classes (36 hours in total) Total time commitment 170 hours Teaching period 26 July 2021 to 24 October 2021 Last self-enrol date 6 August 2021 Census date 31 August 2021 Last date to withdraw without fail 24 September 2021 Assessment period ends 19 November 2021 Semester 2 contact information
Additional delivery details
This Dual-Delivery subject has On Campus assessment components.
Last updated: 31 January 2024
Further information
- Texts
Prescribed texts
There are no specifically prescribed or recommended texts for this subject.
- Available through the Community Access Program
About the Community Access Program (CAP)
This subject is available through the Community Access Program (also called Single Subject Studies) which allows you to enrol in single subjects offered by the University of Melbourne, without the commitment required to complete a whole degree.
Entry requirements including prerequisites may apply. Please refer to the CAP applications page for further information.
- Available to Study Abroad and/or Study Exchange Students
This subject is available to students studying at the University from eligible overseas institutions on exchange and study abroad. Students are required to satisfy any listed requirements, such as pre- and co-requisites, for enrolment in the subject.
Last updated: 31 January 2024