Postgraduate Course: Quantitative Genetic Models (PGBI11085)
Course Outline
| School | School of Biological Sciences |
College | College of Science and Engineering |
| Credit level (Normal year taken) | SCQF Level 11 (Postgraduate) |
Availability | Available to all students |
| SCQF Credits | 10 |
ECTS Credits | 5 |
| Summary | This course builds on lectures in quantitative genetics (in PGBI11001) and statistics (PGBI11003) and provides tools to analyse quantitative genetic data and interpret the results. Students will be introduced to statistical mixed models and the use of molecular data in quantitative genetic models. |
| Course description |
The course consists of 10 lectures and associated computer practicals.
1 Introduction to mixed models for genetic problems
2 Generalising to the animal model incorporating information from all relatives
3 Extending the simple linear model to include repeat records, common environment, maternal effects, and multivariate analysis.
4 Random effects
5 Estimating effects of loci
6 Estimating variance of a locus
7 Genomic relationships and their use in genetic evaluations
8 Genomic evaluation
9 Bayesian models incorporating molecular information
10 Accuracy of genomic evaluation
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Information for Visiting Students
| Pre-requisites | PGBI11001 |
| High Demand Course? |
Yes |
Course Delivery Information
|
| Academic year 2016/17, Available to all students (SV1)
|
Quota: None |
| Course Start |
Block 3 (Sem 2) |
Timetable |
Timetable |
| Learning and Teaching activities (Further Info) |
Total Hours:
100
(
Lecture Hours 20,
Programme Level Learning and Teaching Hours 2,
Directed Learning and Independent Learning Hours
78 )
|
| Assessment (Further Info) |
Written Exam
0 %,
Coursework
100 %,
Practical Exam
0 %
|
| Additional Information (Assessment) |
One assignment (40%) and one class test (60%) |
| Feedback |
Not entered |
| No Exam Information |
Learning Outcomes
On completion of this course, the student will be able to:
- On successfully completing the course students will have a thorough knowledge of statistical mixed models and their application to quantitative genetics.
- Students will be familiar with software available to perform such genetic analyses.
- Students will understand how molecular data can be used to augment traditional approaches.
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Additional Information
| Graduate Attributes and Skills |
Not entered |
| Keywords | QGM |
Contacts
| Course organiser | Dr Sara Knott
Tel: (0131 6)50 5444
Email: s.knott@ed.ac.uk |
Course secretary | Mrs Jennifer Morris
Tel: (0131 6)50 5513
Email: jennie.morris@ed.ac.uk |
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