Coursebooks

Statistical genetics

MATH-438

Lecturer(s) :

Language:

English

Remarque

pas donné en 2020-21

Summary

This course will cover the major topics in statistical genetics.

Content

Topics will include (as time permits):

• Population genetics, Hardy-Weinberg Equilibrium
• Mendelian genetics
• Genetic epidemiology
• Gene mapping
• Pedigree analysis
• Segregation analysis
• Hidden Markov Model (HMM)
• Likelihoods on pedigrees - Elston-Steward and Lander-Green algorithms
• Lod scores and linkage analysis
• Linkage disequilibrium and association analysis
• Genome-wide association studies (GWAS)

Keywords

genetics, genetic epidemiology, pedigree analysis, gene mapping, pedigree analysis, HMM, linkage disequilibrium, GWAS

Learning Prerequisites

Required courses

A previous statistics course would be useful.

Recommended courses

A previous statistics course would be useful.

Important concepts to start the course

A good understanding of likelihood would be useful, although we can cover this in the course if necessary.

Learning Outcomes

By the end of the course, the student must be able to:

• Choose of analysis for a genetic problem
• Construct an appropriate genetic model
• Design a genetic study
• Compute necessary values for a genetic study
• Implement correct analysis methods
• Report results

Transversal skills

• Use a work methodology appropriate to the task.
• Set objectives and design an action plan to reach those objectives.

Teaching methods

Lectures plus handwritten as well as computer exercises.

Expected student activities

Class and exercises attendance and participation as well as report writing. Some group work will also be assigned.

Assessment methods

Assignments based on group exercises and an individual report on a genetic study.

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Supervision

Office hours	Yes
Assistants	Yes
Forum	Yes

Resources

Virtual desktop infrastructure (VDI)

No

Bibliography

To be provided during the course.