Postgraduate Course: Credits Awarded for Taught Courses [University of Glasgow] RNA-seq and Next Generation Transcriptomics BIOL5177 (MCLM11051)
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 | 10 |
ECTS Credits | 5 |
| 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] RNA-seq and Next Generation Transcriptomics BIOL5177
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Entry Requirements (not applicable to Visiting Students)
| Pre-requisites |
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Co-requisites | |
| Prohibited Combinations | |
Other requirements | None |
Course Delivery Information
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| Academic year 2022/23, 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:
100
(
Programme Level Learning and Teaching Hours 2,
Directed Learning and Independent Learning Hours
98 )
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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] RNA-seq and Next Generation Transcriptomics BIOL5177 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:
- Specialist integrative knowledge and critical understanding of the concepts underlying next generation sequencing-based transcriptomics data analysis
- Specialist integrative knowledge and critical understanding of the reasons for differences in the performance of different data analysis methods
- Practice, general cognitive skills, and ICT: in a creative way, the principal skills involved in analysing next generation sequencing data using a range of transcriptomics tools
- Practice, general cognitive skills, and ICT: the use of computer programs to visualize the results of a transcriptomics experiment
- Practice, general cognitive skills, and ICT: that they can critically evaluate and choose from a range of statistical approaches to transcriptomics data analysis and that they can interpret statistical data analysis results by mining annotation databases
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Additional Information
| Graduate Attributes and Skills |
Not entered |
| Keywords | Not entered |
Contacts
| Course organiser | Dr Susan Farrington
Tel: (0131) 332 2471
Email: |
Course secretary | Miss Susan Mitchell
Tel: (0131 6)51 7891
Email: |
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