Postgraduate Course: Credits Awarded for Taught Courses [University of Glasgow] Cancer Genomics - NGS and Functional Analysis Methods BIOL530 (MCLM11044)
Course Outline
| School | Deanery of Molecular, Genetic and Population Health Sciences |
College | College of Medicine and Veterinary Medicine |
| Credit level (Normal year taken) | SCQF Level 11 (Postgraduate) |
Availability | Not available to visiting students |
| SCQF Credits | 20 |
ECTS Credits | 10 |
| Summary | This is a placeholder course, designed to record marks for the University of Glasgow part of the programme, PRPHDISPME1F: Precision Medicine (PhD with Integrated Study)
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| Course description |
Please see [University of Glasgow] Cancer Genomics - NGS and Functional Analysis Methods BIOL5301
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Entry Requirements (not applicable to Visiting Students)
| Pre-requisites |
|
Co-requisites | |
| Prohibited Combinations | |
Other requirements | None |
Course Delivery Information
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| Academic year 2017/18, Not available to visiting students (SS1)
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Quota: None |
| Course Start |
Flexible |
Timetable |
Timetable |
| Learning and Teaching activities (Further Info) |
Total Hours:
200
(
Programme Level Learning and Teaching Hours 4,
Directed Learning and Independent Learning Hours
196 )
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| Assessment (Further Info) |
Written Exam
0 %,
Coursework
100 %,
Practical Exam
0 %
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| Additional Information (Assessment) |
Please see [University of Glasgow] Cancer Genomics - NGS and Functional Analysis Methods BIOL5301 for Components of Assessment
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| Feedback |
Not entered |
| No Exam Information |
Learning Outcomes
On completion of this course, the student will be able to:
- Creatively apply and critically discuss resequencing approaches in genomics and the use of genomic sequence subsets
- Creatively apply and critically discuss approaches used in NGS data management and quality control, including methodologies and requirements for efficient management of NGS data analysis workflows
- Creatively apply and critically discuss alternative approaches used in assembling and aligning NGS sequence data
- Execute, through the creative use of computing approaches, a variety of planned analyses of cancer-related genomic datasets, including assessment of coverage and identification of variants
- Critically evaluate and synthesise methods for benchmarking variant calls and issues concerning annotation of variants
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Additional Information
| Graduate Attributes and Skills |
Not entered |
| Keywords | Not entered |
Contacts
| Course organiser | Dr Elizabeth Elliot
Tel: (0131 6)51 7851
Email: |
Course secretary | Mr Fraser Pullar
Tel: (0131 6)51 7865
Email: |
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