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Course profile

Statistical Analysis of Genetic Data (STAT3306)

Study period
Sem 2 2024
Location
St Lucia
Attendance mode
In Person

Course overview

Study period
Semester 2, 2024 (22/07/2024 - 18/11/2024)
Study level
Undergraduate
Location
St Lucia
Attendance mode
In Person
Units
2
Administrative campus
St Lucia
Coordinating unit
Mathematics & Physics School

This course teaches the why and how of statistical methods and their computer applications to analyse genome-wide genetic data and phenotypes on large numbers of individuals. Genetic data sets are usually large comprising thousands of individuals. Examples of typical genetic data sets include phenotypic records with a recorded pedigree structure of relationships between individuals or disease cases and controls with DNA polymorphisms measured at millions of locations in the genome. Major topics include: linear mixed models for estimation and prediction, genome-wide association studies, multiple trait analyses. The course focusses on applications in human and livestock genetics and genomics. There is a strong element of hands-on analyses of real-world datasets using R and GCTA.

This course will introduce some key concepts for the statistical analysis of genome-wide genetic data. You will get an understanding of genetics and you will develop your statistical expertise and critical judgement, including an awareness of ethical issues in genetic research.ᅠ

Course requirements

Assumed background

The course pre-requisites highlight that students are expected to have quantitative skills. Students without these course pre-requisites should contact the course co-ordinator to determine if they are eligible.

Prerequisites

You'll need to complete the following courses before enrolling in this one:

STAT2004 or STAT2203 or a minimum grade of 5 in SCIE2100 or equivalent.

Incompatible

You can't enrol in this course if you've already completed the following:

STAT7306 (co-taught)

Jointly taught details

This course is jointly-taught with:

  • STAT7306 Statistical Analysis of Genetic Data

STAT3306 and STAT7306 are co-badged courses and will share learning activities. STAT7306 will have some differences in assessment to evaluate students at Level 9 (Masters) of the Australian Qualifications Framework.

Course contact

Course staff

Lecturer

Timetable

The timetable for this course is available on the UQ Public Timetable.

Additional timetable information

All classes will be conducted on campus – consult your personal timetable for times and locations. Students are expected to attend these sessions in person unless they have a valid reason for being unable to attend (such as illness). Alternative arrangements will be advised on Blackboard should the campus be closed for any reason.

Aims and outcomes

This course teaches the why and how of statistical methods and their computer applications to analyse genome-wide genetic data and phenotypes on large numbers of individuals. Genetic data sets are usually large comprising thousands of individuals. Examples of typical genetic data sets include phenotypic records with a recorded pedigree structure of relationships between individuals or disease cases and controls with DNA polymorphisms measured at millions of locations in the genome. Major topics include: linear mixed models for estimation and prediction, genome-wide association studies, multiple trait analyses. The course focusses on applications in human and livestock genetics and genomics. There is a strong element of hands-on analyses of real-world datasets using R and GCTA.

Learning outcomes

After successfully completing this course you should be able to:

LO1.

Understand the nature of genetic data, and understand how to apply key methods for the analysis of genetic data

LO2.

Recognise the advantages and limitations of key statistical models for the analysis of genetic data

LO3.

Generate genetic data through simulation

LO4.

Use the statistical packages R and GCTA appropriately for the analysis and graphical representation of data

LO5.

Make appropriate decisions about analyses to undertake on a genetic data set

LO6.

Communicate the results of statistical analysis of genetic data clearly and accurately

LO7.

Understand the ethical implications of working with genetic data

Assessment

Assessment summary

Category Assessment task Weight Due date
Project Genetic data analysis - Part 1 25%

4/10/2024 5:00 pm

Quiz Take-home Quiz 20%

30/08/2024 5:00 pm

Project Genetic data analysis - Part 2 15%

25/10/2024 5:00 pm

Tutorial/ Problem Set 24-hour document upload non-invigilated assignment 40%

To be advised - during the final examination period

Assessment details

Genetic data analysis - Part 1

Mode
Written
Category
Project
Weight
25%
Due date

4/10/2024 5:00 pm

Learning outcomes
L01, L02, L03, L04

Task description

Using the skills learned in the lectures and the practicals, each student will be provided with a unique genome-wide SNP data set to clean, analyse, interpret and write up.

Submission guidelines

Blackboard

Deferral or extension

You may be able to apply for an extension.

See ADDITIONAL ASSESSMENT INFORMATION for the extension and deferred examination information relating to this assessment item.

Late submission

A penalty of 10% of the maximum possible mark will be deducted per 24 hours from time submission is due for up to 7 days. After 7 days, you will receive a mark of 0.

You are required to submit assessable items on time. If you fail to meet the submission deadline for any assessment item then the listed penalty will be deducted per day for up to 7 calendar days, at which point any submission will not receive any marks unless an extension has been approved. Each 24-hour block is recorded from the time the submission is due.

Take-home Quiz

Mode
Written
Category
Quiz
Weight
20%
Due date

30/08/2024 5:00 pm

Learning outcomes
L01, L02

Task description

Students enrolling in the course were not required to have a background in biological sciences. In the first three weeks, students are exposed to the terminology and concepts of genetics. A solid foundation in this terminology is needed for understanding lectures in subsequent weeks, which will focus more on the genetic analysis of data. The quiz will comprise short answer questions and may include calculations.

Submission guidelines

Blackboard

Deferral or extension

You may be able to apply for an extension.

See ADDITIONAL ASSESSMENT INFORMATION for the extension and deferred examination information relating to this assessment item.

Late submission

A penalty of 10% of the maximum possible mark will be deducted per 24 hours from time submission is due for up to 7 days. After 7 days, you will receive a mark of 0.

You are required to submit assessable items on time. If you fail to meet the submission deadline for any assessment item then the listed penalty will be deducted per day for up to 7 calendar days, at which point any submission will not receive any marks unless an extension has been approved. Each 24-hour block is recorded from the time the submission is due.

Genetic data analysis - Part 2

Mode
Written
Category
Project
Weight
15%
Due date

25/10/2024 5:00 pm

Learning outcomes
L01, L02, L03, L04, L05, L06

Task description

Students will build upon the first project report and the skills learned in the lectures and the practicals to complete the analysis of a genome-wide SNP data set.

Submission guidelines

Blackboard

Deferral or extension

You may be able to apply for an extension.

See ADDITIONAL ASSESSMENT INFORMATION for the extension and deferred examination information relating to this assessment item.

Late submission

A penalty of 10% of the maximum possible mark will be deducted per 24 hours from time submission is due for up to 7 days. After 7 days, you will receive a mark of 0.

You are required to submit assessable items on time. If you fail to meet the submission deadline for any assessment item then the listed penalty will be deducted per day for up to 7 calendar days, at which point any submission will not receive any marks unless an extension has been approved. Each 24-hour block is recorded from the time the submission is due.

24-hour document upload non-invigilated assignment

Mode
Written
Category
Tutorial/ Problem Set
Weight
40%
Due date

To be advised - during the final examination period

Learning outcomes
L01, L02, L05, L06, L07

Task description

This final piece of assessment replaces the traditional final exam and is to be completed during the final exam period. It will be non-invigilated and in the form of a PDF file that you will download from Blackboard. The final assessment is a take-home, open-book assignment. Students have to solve the assessment by themselves, though they are allowed to use any written and online resources (excluding online student forums and generative AI). You can print the assignment and write in the places provided (where applicable), or write your answers on blank paper, or write electronically on a suitable device. You will then scan or photograph your work if necessary and upload your answers to Blackboard as a single pdf file. You will be advised of a 24-hour period during the examination period when you must complete this assessment item. You can access and submit your paper at any time within the 24 hours. Even though you have the entire 24 hours to complete and submit this assessment, the expectation is that it will take students around 2 hours to complete. Note that late penalties will be strictly applied as described below.


Note also that a deferred assignment will not be available. If you are unable to attempt the assessment item at the advertised time, then you must apply for an extension through the normal channels before accessing the question paper.

Submission guidelines

Blackboard

Deferral or extension

You may be able to apply for an extension.

A deferred final assignment will not be available. If you are unable to attempt the assessment item at the advertised time, then you must apply for an extension through the normal channels before accessing the question paper. If an extension is approved, then you must not access the question paper until the start of the revised 24-hour period allocated for you to complete the assessment.

 

Extension requests submitted after accessing the question paper will not be considered unless there are exceptional circumstances.

Late submission

A penalty of 10% of the maximum possible mark will be deducted per 24 hours from time submission is due for up to 7 days. After 7 days, you will receive a mark of 0.

You are required to submit the final assessment on time. If you fail to meet the submission deadline for this assessment item, then the listed penalty will be deducted per block of 30 minutes, up to 3 hours, at which point any submission will not receive any marks unless an extension has been approved. Each 30-minute block is recorded from the time the submission is due. 

Course grading

Full criteria for each grade is available in the Assessment Procedure.

Grade Description
1 (Low Fail)

Absence of evidence of achievement of course learning outcomes.

Course grade description: You will be able to partially analyse very few data settings. Written reports will be poor and accuracy in graphical and numerical work will be low. To earn a Grade of 1, you must merit a mark between 0-19%.

2 (Fail)

Minimal evidence of achievement of course learning outcomes.

Course grade description: To earn a Grade of 2, you must merit a mark between 20-44% by demonstrating some knowledge of the basic concepts of the course. You will be able to partially analyse a few important data settings. Written reports may be poor and accuracy in graphical and numerical work may be low. A student will also be awarded a grade of 2 if they score above 45% for the course but receive a mark more than 20% but less than 30% for the final assignment.

3 (Marginal Fail)

Demonstrated evidence of developing achievement of course learning outcomes

Course grade description: To earn a Grade of 3, you must merit a mark between 45-49% by demonstrating some knowledge of the basic concepts of the course. You will be able to analyse important data settings. You will demonstrate the ability to write statistical reports and show accuracy in graphical and numerical work. A student will also be awarded a grade of 3 if they score above 50% for the course but receive a mark more than 30% but less than 40% for the final assignment.

4 (Pass)

Demonstrated evidence of functional achievement of course learning outcomes.

Course grade description: To earn a Grade of 4, you must merit a mark between 50-64% by demonstrating an understanding of the basic concepts of the course. You will be able to analyse the important data settings, identifying some key assumptions that might affect the analysis. You will demonstrate the ability to write statistical reports and show accuracy in graphical and numerical work. In order to achieve at least the minimum pass grade of 4, the student must achieve at least 40% in the final assignment.

5 (Credit)

Demonstrated evidence of proficient achievement of course learning outcomes.

Course grade description: To earn a Grade of 5, you must merit a final mark between 65-74% by demonstrating an adequate understanding of the course material. You will be able to analyse many data settings, identifying the key assumptions that might affect the analysis. You will demonstrate the ability to write statistical reports and show accuracy in graphical and numerical work.

6 (Distinction)

Demonstrated evidence of advanced achievement of course learning outcomes.

Course grade description: To earn a Grade of 6, you must merit a mark between 75-84% by demonstrating a comprehensive understanding of the course material. You will be able to analyse most data settings, identifying important assumptions and other factors that might affect the analysis. You will demonstrate proficiency in communicating statistical ideas in writing and a high level of accuracy in graphical and numerical work.

7 (High Distinction)

Demonstrated evidence of exceptional achievement of course learning outcomes.

Course grade description: To earn a Grade of 7, you must merit a mark between 85-100% by demonstrating an excellent understanding of the course material. You will be able to analyse a broad range of data settings, providing insight and thoroughness in the form of necessary assumptions and other factors that might affect the analysis. You will demonstrate excellent proficiency in communicating statistical ideas in writing and a high level of accuracy in graphical and numerical work.

Supplementary assessment

Supplementary assessment is available for this course.

Should you fail a course with a grade of 3, you may be eligible for supplementary assessment. Refer to my.UQ for information on supplementary assessment and how to apply. 

Supplementary assessment provides an additional opportunity to demonstrate you have achieved all the required learning outcomes for a course.  

If you apply and are granted supplementary assessment, the type of supplementary assessment set will consider which learning outcome(s) have not been met.  

Supplementary assessment in this course will be a 2-hour examination similar in style to the end-of-semester examination. To receive a passing grade of 3S4, you must obtain a mark of 50% or more on the supplementary assessment. 

Additional assessment information

Artificial Intelligence

The assessment tasks in this course evaluate students’ abilities, skills and knowledge without the aid of Artificial Intelligence (AI). Students are advised that the use of AI technologies to develop responses is strictly prohibited and may constitute misconduct under the Student Code of Conduct. 

Applications for Extensions to Assessment Due Dates

Extension requests are submitted online via my.UQ – applying for an extension. Extension requests received in any other way will not be approved. Additional details associated with extension requests, including acceptable and unacceptable reasons, may be found at my.UQ.

Please note:

  • Requests for an extension to an assessment due date must be submitted through your my.UQ portal and you must provide documentation of your circumstances, as soon as it becomes evident that an extension is needed. Your application must be submitted on or before the assessment item's due date and time.
  • Applications for extension can take time to be processed so you should continue to work on your assessment item while awaiting a decision. We recommend that you submit any completed work by the due date, and this will be marked if your application is not approved. Should your application be approved, then you will be able to resubmit by the agreed revised due date.
  • If an extension is approved, you will be notified via your my.UQ portal and the new date and time for submission provided. It is important that you check the revised date as it may differ from the date that you requested.
  • If the basis of the application is a medical condition, applications should be accompanied by a medical certificate dated prior to the assignment due date. If you are unable to provide documentation to support your application by the due date and time you must still submit your application on time and attach a written statement (Word document) outlining why you cannot provide the documentation. You must then upload the documentation to the portal within 24 hours.
  • If an extension is being sought on the basis of exceptional circumstances, it must be accompanied by supporting documentation (eg. Statutory declaration).
  • For extensions based on a SAP you may be granted a maximum of 7 days (if no earlier maximum timeframe applies). See the Extension or Deferral availability section of each assessment for details. Your SAP is all that is required as documentation to support your application. However, additional extension requests for the assessment item will require the submission of additional supporting documentation e.g., a medical certificate. All extension requests must be received by the assessment due date and time.
  • An extension for an assessment item due within the teaching period in which the course is offered, must not exceed four weeks in total. If you are incapacitated for a period exceeding four weeks of the teaching period, you are advised to apply for Removal of Course.
  • If you have been ill or unable to attend class for more than 14 days, you are advised to carefully consider whether you are capable of successfully completing your courses this semester. You might be eligible to withdraw without academic penalty - seek advice from the Faculty that administers your program.
  • Students may be asked to submit evidence of work completed to date. Lack of adequate progress on your assessment item may result in an extension being denied.
  • There are no provisions for exemption from an assessment item within UQ rules. If you are unable to submit an assessment piece then, under special circumstances, you may be granted an exemption, but may be required to submit alternative assessment to ensure all learning outcomes are met.

Applications to defer an exam

In certain circumstances you can apply to take a deferred examination for in-semester and end-of-semester exams. You'll need to demonstrate through supporting documentation how unavoidable circumstances prevented you from sitting your exam. If you can’t, you can apply for a one-off discretionary deferred exam.

Deferred Exam requests are submitted online via mySi-net. Requests received in any other way will not be approved. Additional details associated with deferred examinations, including acceptable and unacceptable reasons may be found at my.UQ.

Please note:

  • Applications can be submitted no later than 5 calendar days after the date of the original exam.
  • There are no provisions to defer a deferred exam. You need to be available to sit your deferred examination.
  • Your deferred examination request(s) must have a status of "submitted" in mySI-net to be assessed.
  • All applications for deferred in-semester examinations are assessed by the relevant school. Applications for deferred end-of-semester examinations are assessed by the Academic Services Division.
  • You’ll receive an email to your student email account when the status of your application is updated.
  • If you have a medical condition, mental health condition or disability and require alternative arrangements for your deferred exam you’ll need to complete the online alternative exam arrangements through my.UQ. This is in addition to your deferred examinations request. You need to submit this request on the same day as your request for a deferred exam or supplementary assessment. Contact Student Services if you need assistance completing your alternative exam arrangements request.

Learning resources

You'll need the following resources to successfully complete the course. We've indicated below if you need a personal copy of the reading materials or your own item.

Library resources

Find the required and recommended resources for this course on the UQ Library website.

Additional learning resources information

The Blackboard site for STAT3306 will provide the lecture recordings, notes and the course discussion board.ᅠ

Learning activities

The learning activities for this course are outlined below. Learn more about the learning outcomes that apply to this course.

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Learning period Activity type Topic
Multiple weeks

From Week 1 To Week 13
(22 Jul - 27 Oct)

Lecture

Lectures

Introduction to statistical modelling of genetic data, quantitative genetic models of complex genetic traits and disease, GWAS, BLUP, (G)REML, Mendelian Randomisation and LD Score regression

Learning outcomes: L01, L02, L05, L06, L07

Multiple weeks

From Week 2 To Week 13
(29 Jul - 27 Oct)

Tutorial

Tutorials

Practical application of methods taught in lectures to genetic data, methods for simulation of genetic data, discussion of ethical aspects of genetic data analysis, support for major project analysis.

Learning outcomes: L01, L02, L03, L04, L05, L06, L07

Policies and procedures

University policies and procedures apply to all aspects of student life. As a UQ student, you must comply with University-wide and program-specific requirements, including the:

Learn more about UQ policies on my.UQ and the Policy and Procedure Library.