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Topics for Master Theses at Qualitas AG together with ETH are shown here.
The following descriptions are taken from the course catalog
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.
Swiss routine breeding value estimation/genetic evaluation systems of cattle, pig, sheep and goats are presented with methods and evaluated traits. Examples will be demonstrated using the statistical software R.
The students know the theoretical and practical application of breeding value estimation in Switzerland for cattle, pig, sheep and goats. The students are able to interpret estimated breeding values.
You can use the exercise platform to work on exercise problems. The platform is reachable at: http://r4tea.rteastem.org:8787/
The username corresponds to the part of your E-Mail address before the @-sign. The password is sent to you via a different E-Mail.
You can always ask questions during the lecture and the exercise hours or alternatively via e-mail at (peter.vonrohr at gmail.com).
| Week | Date | Topic |
|---|---|---|
| 1 | 18.02 | Introduction |
| 2 | 25.02 | Multiple Linear Regression |
| 3 | 04.03 | GBLUP - Marker-Effects Models |
| 4 | 11.03 | GBLUP - Breeding Value Models |
| 5 | 18.03 | Lasso |
| 6 | 25.03 | Bayesian Approaches |
| 7 | 01.04 | Introduction |
| 8 | 08.04 | Suisag and The Swiss Pig Breeding Program - Patrick Stratz (Suisag) |
| 9 | 15.04 | Model Selection |
| 10 | 22.04 | Easter Monday |
| 11 | 29.04 | Genetic Groups |
| 12 | 06.05 | Longitudinal Data |
| 13 | 13.05 | Braunvieh Schweiz and Qualitas AG |
| 14 | 20.05 | Questions and Test Exams |
| 15 | 27.05 | Final Exams |
The lecture notes, the slides, the exercises and the solutions can be downloaded from this site.
| Week | Date | Topic |
|---|---|---|
| 1 | 18.02 | Introduction |
| 2 | 25.02 | Fixed Linear Effects Model (Part 1), Part2 |
| 3 | 04.03 | GBLUP |
| 4 | 11.03 | LASSO |
| 5 | 18.03 | Bayes |
| 6 | 25.03 | Appendix |
| 7 | 01.04 | Introduction |
| 8 | 08.04 | Breeding Programs |
| 9 | 15.04 | Implementation of Breeding Programs |
| 10 | 22.04 | Easter Monday |
| 11 | 29.04 | Model Selection |
| 12 | 06.05 | Variance Components Estimation |
| 13 | 13.05 | Prediction of Breeding Values |
| 14 | 20.05 | |
| 15 | 27.05 | Final Exams |
| Week | Date | Topic |
|---|---|---|
| 1 | 18.02 | Introduction |
| 2 | 25.02 | Fixed Linear Effects Model |
| 3 | 04.03 | GBLUP |
| 4 | 11.03 | GRM, GBLUP II |
| 5 | 18.03 | LASSO |
| 6 | 25.03 | Bayes |
| 7 | 01.04 | Introduction |
| 8 | 08.04 | Suisag - Zuchtwertschätzung beim Schwein |
| 9 | 15.04 | Implementation of Breeding Program |
| 10 | 22.04 | Easter Monday |
| 11 | 29.04 | Model Selection |
| 12 | 06.05 | Variance Components |
| 13 | 13.05 | Braunvieh Schweiz, Qualitas AG |
| 14 | 20.05 | |
| 15 | 27.05 | Final Exams |
| Week | Date | Topic |
|---|---|---|
| 1 | 18.02 | |
| 2 | 25.02 | Breeding Values and Prediction of Effects |
| 3 | 04.03 | Fixed Linear Effect Model |
| 4 | 11.03 | Genomic Relationship Matrix |
| 5 | 18.03 | Genomic BLUP |
| 6 | 25.03 | GBLUP II |
| 7 | 01.04 | Bayes |
| 8 | 08.04 | |
| 9 | 15.04 | Model Selection |
| 10 | 22.04 | Easter Monday |
| 11 | 29.04 | |
| 12 | 06.05 | Variance Components Estimation |
| 13 | 13.05 | Prediction of Breeding Values |
| 14 | 20.05 | Applied Statistical Methods, |
| Genetic Evaluation | ||
| 15 | 27.05 | Final Exams |
| Week | Date | Topic |
|---|---|---|
| 1 | 18.02 | |
| 2 | 25.02 | Breeding Values and Prediction of Effects |
| 3 | 04.03 | Fixed Linear Effect Model |
| 4 | 11.03 | Genomic Relationship Matrix |
| 5 | 18.03 | Genomic BLUP |
| 6 | 25.03 | GBLUP II |
| 7 | 01.04 | Bayes |
| 8 | 08.04 | |
| 9 | 15.04 | |
| 10 | 22.04 | Easter Monday |
| 11 | 29.04 | Model Selection |
| 12 | 06.05 | Variance Components Estimation |
| 13 | 13.05 | Prediction of Breeding Values |
| 14 | 20.05 | Applied Statistical Methods, |
| Genetic Evaluation | ||
| 15 | 27.05 | Final Exams |
| Week | Date | Topic |
|---|---|---|
| 1 | 18.02 | |
| 2 | 25.02 | Genotype Data Exercise 1 |
| 3 | 04.03 | |
| 4 | 11.03 | |
| 5 | 18.03 | Data Analysis Protocol |
| 6 | 25.03 | |
| 7 | 01.04 | |
| 8 | 08.04 | |
| 9 | 15.04 | Dataset Model Selection |
| 10 | 22.04 | Easter Monday |
| 11 | 29.04 | |
| 12 | 06.05 | Dataset Variance Components, Dataset Sire Model |
| 13 | 13.05 | Bibliography |
| 14 | 20.05 | |
| 15 | 27.05 | Final Exams |
Latest Changes: 2019-05-20 15:29:58 (peter)