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Statistical Genomics (MAST30033)
Undergraduate level 3Points: 12.5On Campus (Parkville)
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About this subject
- Overview
- Eligibility and requirements
- Assessment
- Dates and times
- Further information
- Timetable(opens in new window)
Contact information
Semester 2
Email: kimanh.lecao@unimelb.edu.au
Please refer to the LMS for up-to-date subject information, including assessment and participation requirements, for subjects being offered in 2020.
Overview
Availability | Semester 2 |
---|---|
Fees | Look up fees |
This subject introduces the biology and technology underlying modern genomics data, features of the resulting data types including the frequency and patterns of error and missingness, and the statistical methods used to analyse them. It will include hands-on data analysis using R software. The material covered will evolve as genomics technology and practice change, and will span the following four areas: introduction to genomics technology and the resulting data, population genetics, association analysis including tests of association and major sources of confounding, heritability and prediction both in human genetics and for animal and plant breeding, and analysis of expression quantitative trait loci.
Intended learning outcomes
- Ability to explain the key genomics assays, their purpose and the strengths and limitations of the data generated.
- An understanding of the role of population genetics theory in interpreting genomics data
- Ability to perform a range of association analyses using SNP and sequence data
- An understanding of the strengths and weaknesses of SNP-based heritability relative to traditional measures of heritability
- Awareness of the major problems in association analyses that can lead to false inferences
- Ability to explain the use of statistical models in predicting phenotype from genomic data, and the uses and limitations of genomic prediction
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 (students are expected to have some skills at entry but the subject will take them to a higher level)
- ability to read, understand, modify and use short computer programs
- time-management: completing assignments according to deadlines while making judgments about time required for different pars of the assignment.
Last updated: 13 April 2024
Eligibility and requirements
Prerequisites
Undergraduate students:
Code | Name | Teaching period | Credit Points |
---|---|---|---|
GENE20001 | Foundations of Genetics and Genomics | Semester 1 (On Campus - Parkville) |
12.5 |
(or have an equivalent knowledge of genetics)
Master of Computational Biology students:
Code | Name | Teaching period | Credit Points |
---|---|---|---|
GENE90019 | Genes Molecules and Cells | Semester 1 (On Campus - Parkville) |
25 |
All students must also complete one of the following subject sets (A, or B):
Set A:
One of
Code | Name | Teaching period | Credit Points |
---|---|---|---|
MAST20005 | Statistics |
Semester 2 (On Campus - Parkville)
Summer Term (On Campus - Parkville)
|
12.5 |
MAST30032 | Biological Modelling and Simulation | Semester 1 (On Campus - Parkville) |
12.5 |
Set B:
One of
Code | Name | Teaching period | Credit Points |
---|---|---|---|
MAST10006 | Calculus 2 |
Semester 1 (On Campus - Parkville)
Summer Term (On Campus - Parkville)
Semester 2 (On Campus - Parkville)
|
12.5 |
MAST10021 | Calculus 2: Advanced | Semester 2 (On Campus - Parkville) |
12.5 |
AND
Code | Name | Teaching period | Credit Points |
---|---|---|---|
MAST20031 | Analysis of Biological Data | Semester 1 (On Campus - 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: 13 April 2024
Assessment
Due to the impact of COVID-19, assessment may differ from that published in the Handbook. Students are reminded to check the subject assessment requirements published in the subject outline on the LMS
Description | Timing | Percentage |
---|---|---|
Four computer-based assignments (12.5% per assignment) handed out and discussed during computer lab classes, completed in students' own time, and due at regular intervals during the semester (week 3, 6, 9 and 12). Submissions will include computer code, results generated (numerical and graphical) plus sections of text interpreting the results (total 10 pages per assignment). | Throughout the teaching period | 50% |
A written exam
| During the examination period | 50% |
Additional details
This Dual-Delivery subject has On Campus assessment components.
Last updated: 13 April 2024
Dates & times
- Semester 2
Principal coordinator Kim-Anh Le Cao Mode of delivery On Campus (Parkville) Contact hours 48 hours: 24 x one-hour lectures (2 lectures per week), 12 x two-hour practice classes (1 per week). Teaching period 3 August 2020 to 1 November 2020 Last self-enrol date 14 August 2020 Census date 21 September 2020 Last date to withdraw without fail 16 October 2020 Assessment period ends 27 November 2020 Semester 2 contact information
Email: kimanh.lecao@unimelb.edu.au
Additional delivery details
This Dual-Delivery subject has On Campus assessment components.
Last updated: 13 April 2024
Further information
- Texts
Prescribed texts
There are no specifically prescribed or recommended texts for this subject.
- Related Handbook entries
This subject contributes to the following:
Type Name Informal specialisation Science-credited subjects - new generation B-SCI Major Computational Biology - 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.
Last updated: 13 April 2024