Welcome to

751-7602-00L Applied Statistical Methods in Animal Sciences

Topics for Master Theses

Topics for Master Theses at Qualitas AG together with ETH are listed here.

Information

  • Lecturer: Peter von Rohr
  • Date: Montag 8-10
  • Mode: hybrid - in person and via zoom
  • Room: LFW C11

Exercise Platform

  • The exercise platform can be found at: http://2-htz.quagzws.com:<PORT>
  • The number that you have to insert for <PORT> was sent by e-mail, as well as the password
  • The username is: rstudio

Exam

  • Written exam
  • Date: 30.05.2022 - 08:15 - 10:00
  • Room: LFW C 11

Description

The following descriptions are taken from the course catalog

Applied Statistical Methods in Animal Science

Genomic selection is currently the method of choice for improving the genetic potential of selection candidates in livestock breeding programs. This lecture introduces the reason why regression cannot be used in genomic selection. Alternatives to regression analysis that are suitable for genomic selection are presented. The concepts introduced are illustrated by excersises in R.

The students are familiar with the properties of multiple linear regression and they are able to analyse simple data sets using regression methods. The students know why multiple linear regression cannot be used for genomic selection. The students know the statistical methods used in genomic selection, such as BLUP-based approaches, Bayesian procedures and LASSO. The students are able to solve simple exercise problems using the statistical framework R.

Questions

Questions can be asked during the lecture and during the exercise hour or via e-mail:

  • Peter von Rohr (peter.vonrohr at usys.ethz.ch)

Lecture Program

Week Date Topic
1 21.02 Introduction to Applied Statistical Methods in Animal Science
2 28.02 Linear Regression Models
3 07.03 Linear Fixed Effect Models
4 14.03 Model Selection
5 21.03 Pedigree BLUP
6 28.03 Variance Components
7 04.04 GBLUP - Marker-Effects Models
8 11.04 GBLUP - Breeding Value Models
9 18.04 Easter Monday
10 25.04 Lasso
11 02.05 SVM
12 09.05 Bayesian Approaches in Linear Regression Models
13 16.05 Bayesian Approaches in Linear Mixed Effects Models
14 23.05 Questions, Test Exam
15 30.05 Exams

License

Creative Commons License
This work is licensed under a Creative Commons Attribution 4.0 International License.

Latest Changes: 2022-04-26 10:57:49 (pvr)