ANIM0001-2 : Quantitative genetics

University of Liege | Version française

Study programmes 2012-2013

Last update : 18/06/2013

ANIM0001-2

Quantitative genetics

Duration :

18h Th, 18h Pr

Number of credits :

Master in Statistics : Biostatistics, professional focus , 1st year		3

Lecturer :

Nicolas Gengler

Language(s) of instruction :

French language

Organisation and examination :

Teaching in the first semester, review in January

Course contents :

Course description This course will teach the methods, models and algorithms applied in the field in the context of quantitative genetics.
Table of contents
CHAPTER 1 Introduction and context CHAPTER 2 Selection index CHAPTER 3 Mixed Models CHAPTER 4 Estimation of parameters CHAPTER 5 Genomic prediction

Appendix 1: Basic of mathematics and statistics ; reminder of matrix algebra and introduction to linear models
Appendix 2: Quantitative and qualitative, monogenic and polygenic traits Appendix 3: Environmental and genetic variability of populations Appendix 4: Resemblance between relatives and measures of parentage Appendix 5: Effects of reproduction systems, heterosis and inbreeding Appendix 6: Covariance and correlation between traits Appendix 7: Basic of genomics

Learning outcomes of the course :

To teach the bases of and the most used methods in quantitative genetics. After completing the course the student is expected to

understand the bases of quantitative genetics ;
understand the most used computational methods in quantitative genetics ;
explain the results of these methods to different stakeholders in the field.

Finaly, the students will have acquired practical experience in the use of MATLAB.

Prerequisites and co-requisites/ Recommended optional programme components :

Génétique générale
Statistique fondamentale
Mathématique générale

Planned learning activities and teaching methods :

Close association of theory and solving of practical exercices using MATLAB, a fourth-generation programming language and a development environment that is used as a numerical computing tool.

Mode of delivery (face-to-face ; distance-learning) :

Lectures : 18h
Practical Works : 15h
Seminars : 1h
Field-study trip and visits : 2h