Statistical genomics is the application of statistical methods to understand genomes, their structure, function and history, in many different scientific contexts, including understanding biological mechanisms in health and disease. Statistical genomics is characterised by large datasets, high-dimensional regression models, stochastic processes, and computationally-intensive statistical methods. The aim of this unit is to learn about relevant biology and terminology, to understand the most important mathematical models and inference methods in statistical genetics, to be able to test for association between genetic variants and outcomes of interest, and to use genome-wide statistical models to help understand the genetic mechanisms underlying a trait and to predict outcomes. The statistical package R will be used to perform regression-based analyses of genetic data.
Unit details and rules
Academic unit | Public Health |
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Credit points | 6 |
Prerequisites
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BSTA5004 and (BSTA5210 or BSTA5211 or BSTA5007) |
Corequisites
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None |
Prohibitions
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None |
Assumed knowledge
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None |
Available to study abroad and exchange students | No |
Teaching staff
Coordinator | Erin Cvejic, erin.cvejic@sydney.edu.au |
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