Postgraduate Course: Next Generation Genomics (BILG11004)
Course Outline
| School | School of Biological Sciences |
College | College of Science and Engineering |
| Credit level (Normal year taken) | SCQF Level 11 (Postgraduate) |
Availability | Not available to visiting students |
| SCQF Credits | 10 |
ECTS Credits | 5 |
| Summary | This course will introduce and explore the novel algorithms and applications required for next-generation genomics analysis. The explosion in second and third generation sequencing technologies has led to a matching revolution in the bioinformatics methods of analysis of the vast quantities of raw data produced, and the new challenges of mining these data for biological insight. This course will introduce next-generation genomics technologies, and guide students through the bioinformatics analyses of data across a wide range of applications. There will be a particular focus on building understanding of the algorithms used in the bioinformatics analyses, and of the interplays between genetic variability, genome complexity and experimental and statistical noise. The course emphasizes the need for appropriate bioinformatic tools for analyzing complex genomes, and uses a series of practical sessions to demonstrate the utility of these methods for studying non-model systems. |
| Course description |
The course will cover the following topic areas, through a combination of delivered lectures, class discussion and tutorials, and hands-on practicals;
- Introduction to second and third generation sequencing technologies, including single-molecule sequencing
- Investigating genome variability, gene expression, gene regulation and genome structure by mapping sequences to a reference genome
- Identifying genetic variants from sequence data aligned to a reference genome
- Assembling genome, metagenome and transcriptome sequences de novo from next-generation sequencing data
|
Entry Requirements (not applicable to Visiting Students)
| Pre-requisites |
It is RECOMMENDED that students have passed
Bioinformatics Programming and System Management (PGBI11095)
|
Co-requisites | |
| Prohibited Combinations | |
Other requirements | (a) for biological science students undertaking a Biology MSc, have completed the 'Bioinformatics Programming & System Management' course or other core programming course, or
(b) for computer science or informatics students undertaking an Informatics (Bioinformatics) MSc, have completed the Bioinformatics 1 course. |
Course Delivery Information
|
| Academic year 2020/21, Not available to visiting students (SS1)
|
Quota: 48 |
| Course Start |
Semester 2 |
Timetable |
Timetable |
| Learning and Teaching activities (Further Info) |
Total Hours:
100
(
Lecture Hours 30,
Summative Assessment Hours 3,
Programme Level Learning and Teaching Hours 2,
Directed Learning and Independent Learning Hours
65 )
|
| Assessment (Further Info) |
Written Exam
50 %,
Coursework
50 %,
Practical Exam
0 %
|
| Additional Information (Assessment) |
The course will be assessed by:
(a) an in-course assessment essay of 4,000 words (based on literature review of a selected topic in next-generation genomics bioinformatics) which will account for 50% of the overall course mark.
(b) an essay-based exam paper, which will also account for 50% of the course mark. (May/June Exam diet)
|
| Feedback |
Formative / summative feedback will be provided for all assessments.
|
| Exam Information |
| Exam Diet |
Paper Name |
Hours & Minutes |
|
| Main Exam Diet S2 (April/May) | Next Generation Genomics | 2:00 | |
Learning Outcomes
On completion of this course, the student will be able to:
- To demonstrate an understanding of the molecular and technical underpinnings of second and third generation sequencing technologies and critically evaluate next-generation technologies in terms of their utility for a specific biological research question.
- To be conversant with the core algorithms used in data analyses and be able to choose in an informed way the best analytical solutions for particular problem. 3. To understand how genome assembly algorithms achieve their task.
- To understand how genome assembly algorithms achieve their task.
- To use popular quality control methods such as FastQC, emerging genome assembly softwares such as Wtdb2/Redbean, and data visualisation software such as IGV to analyse second and third generation sequencing data.
- To understand how sequence data of individuals and populations can elucidate underlying biological processes.
|
Additional Information
| Graduate Attributes and Skills |
Not entered |
| Keywords | NGG |
Contacts
| Course organiser | Dr Alex Twyford
Tel: (0131 6)50 5455
Email: Alex.Twyford@ed.ac.uk |
Course secretary | Ms Louise Robertson
Tel: (0131 6)50 5988
Email: Louise.K.M.Robertson@ed.ac.uk |
|
|
University Homepage