Genetic Statistics and Bioinformatics

10 Units

This course introduces students to Genetic Statistics and Bioinformatics. The course is designed to equip students with an understanding of the biological and molecular theory relevant to understanding DNA variation, its inheritance, and relation with measurable traits in humans. A major emphasis is on manipulating and analysing genetic data and correctly interpreting results. The course will provide a foundation for further theoretical and practical studies in this major field.

Faculty Faculty of Health and Medicine
School School of Medicine and Public Health

Not currently offered

Learning Outcomes

On successful completion of this course, students will be able to:

  1. Understand basic concepts of molecular genetics relevant to genetic epidemiology, including DNA structure, recombination, allelic variation, and mutation;
  2. Understand disease and quantitative phenotypes and describe their possible modes of inheritance;
  3. Define heritability and understand the different approaches to its estimation;
  4. Define and assess standard metrics for a range of genetic markers, with an emphasis on single nucleotide polymorphisms (SNPs);
  5. Design a genetic association study, including power and sample size calculations;

This course introduces students to the Genetic Statistics and Bioinformatics. Students will be exposed to basic concepts in molecular genetics that underpin this field. They will gain an understanding of the various response variable types that can be studied and major differences in their modes of inheritance. Students will learn to design a genetic association study, understand and manipulate data representing DNA sequence variation and study its association with disease states and quantitative traits. They will also gain an appreciation of important statistical challenges relating to multiple testing, and its impact on type I error rate and power in genome-wide association studies. There will be an emphasis on gaining practical experience with manipulating and analysing genetic data, and appropriate presentation of results.



  • Must be in G Dip Medical Biostatistics or M Medical Statistics. Pre-requisites: must have completed BIOS6010, BIOS6040, BIOS6050, BIOS6070 and BIOS6170. Anti-requisite: This course replaces BIOS6110. Can't take BIOS6111 if you've done BIOS6110.
Assessment Items
  • Written Assignment: Essays / Written Assignments

Contact Hours

WebLearn GradSchool

Self-Directed Learning

Self-Directed 6 hour(s) per Week for Full Term
Not relevant for distance learning mode.

Course Materials
  • Applied Statistical Genetics with R
  • The Fundamentslof Modern Statistical Genetics
Timetable 2017 Course Timetables for BIOS6111
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