Postgraduate Course: Quantitative Genetic Models (PGBI11085)
Course Outline
| School | School of Biological Sciences |
College | College of Science and Engineering |
| Course type | Standard |
Availability | Available to all students |
| Credit level (Normal year taken) | SCQF Level 11 (Postgraduate) |
Credits | 10 |
| Home subject area | Postgraduate |
Other subject area | None |
| Course website |
None |
Taught in Gaelic? | No |
| Course description | 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. |
Information for Visiting Students
| Pre-requisites | PGBI11001 |
| Displayed in Visiting Students Prospectus? | No |
Course Delivery Information
|
| Delivery period: 2013/14 Block 3 (Sem 2), Available to all students (SV1)
|
Learn enabled: Yes |
Quota: None |
|
Web Timetable |
Web Timetable |
| Course Start Date |
13/01/2014 |
| Breakdown of Learning and Teaching activities (Further Info) |
Total Hours:
100
(
Lecture Hours 14,
Supervised Practical/Workshop/Studio Hours 24,
Programme Level Learning and Teaching Hours 2,
Directed Learning and Independent Learning Hours
60 )
|
| Additional Notes |
|
| Breakdown of Assessment Methods (Further Info) |
Written Exam
0 %,
Coursework
40 %,
Practical Exam
60 %
|
| No Exam Information |
Summary of Intended Learning Outcomes
| On successfully completing the course students will have a thorough knowledge of statistical mixed models and their application to quantitative genetics and will be familiar with software available to perform such analyses. Students will understand how molecular data can be used to augment traditional approaches. |
Assessment Information
| One assignment (40%) and one class test (60%) |
Special Arrangements
| None |
Additional Information
| Academic description |
Not entered |
| Syllabus |
Session Topic
1 Introduction to mixed models for genetic problems
2 Generalising to the animal model incorporating information from all relatives
3 Parameter estimation: REML and variance estimation, BLUP and genetic evaluations
4 Practical analysis of real data
5 Extending the simple linear model to include common environment (repeat records), maternal effects, dominance and multivariate analysis.
6 Combining pedigree and molecular information to estimate relationships
7 Genomic relationships and their use in genetic evaluations
8 Practical issues and limitations with genomic data
9 Bayesian models incorporating molecular information
10 Future developments
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| Transferable skills |
Not entered |
| Reading list |
Not entered |
| Study Abroad |
Not entered |
| Study Pattern |
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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