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Statistical Genomics (POPH90124)
Graduate courseworkPoints: 12.5Online
About this subject
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 and function in many different scientific contexts, including: understanding biological mechanisms in health and disease and predicting outcomes. The course will also cover common statistical methods used to analyse whole-genome sequencing-based modern biological data, including genomics, transcriptomics, epigenomics and single-cell transcriptomics, as well as their application to population data to study causes of disease.
Intended learning outcomes
On completion of this subject students should be able to:
- Describe core mechanisms and central dogma of genetics
- Perform sequence analysis using hidden Markov models.
- Access genomic data from public databases
- Perform a genetic association analysis, including the assessment of possible confounding.
- Explain the concept of heritability and its estimation.
- Develop prediction models using genome-wide single nucleotide polymorphism (SNP) data.
- Explain key features of data, statistical models and methods used in the fields of transcriptomics, epigenetics and single-cell omics.
- Effectively communicate results of statistical analyses in genomics and related areas
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: 29 November 2024