Advanced Bioinformatics for Next-Generation Sequencing
Course content
The course covers advanced topics in Bioinformatics for analysis of data next-generation sequencing (NGS). The course is based mostly on scientific papers and texts. The topics include:
- Mapping algorithms
- Population genetic and medical genetic analysis based on NGS
- RNA-seq
- Cross-species comparative genomic analyses
- Other topics relating to high-throughput DNA sequencing
MSc Programme in Bioinformatics
Knowledge:
The student will know and understand the main methods used in the course. More specifically, the student will obtain knowledge of:
- Analysis of high-throughput sequencing data
- Genetic analyses
- Phylogenetic construction
- Genome evolutionary analyses
Skills:
The student will be able to:
- Do the types of data analyses covered in the course
- Interpret results of such analyses in a biological context
- Explain the methods covered in the course
- Select the appropriate methods and tools for a given problem covered in the course
Competences:
The student will obtain or improve these general competences:
- Will be able to discuss and explain methods in bioinformatics with researchers in bioinformatics and related sciences
- Will be able to contribute to interdisciplinary projects involving biological sequence analysis
- Will be able to read, understand, and discuss scientific literature in bioinformatics
Lectures and exercises (7 hours per week), and homework (4 in total).
See Absalon.
Competencies corresponding to 3 out of 4 of the mandatory
courses in the bioinformatics graduate programme or equivalent.
Students must be on their second year. The course builds on several
components that are taught in the first year, listed below, and is
thus recommended for second-year students.
- statistics
- mapping and alignment, incl. Burrows-Wheeler transformation
- R programming for visualization and data manipulation
- Working with expression data (RNAseq)
- experience with analysing short read NGS data
- population genetics, pop structure, admixture
- PCA
While it is of course possible to catch up by studying
independently, the course may become rather challenging and
time-consuming if all the expected qualifications are new to you.
Overall, unless you are fluent in Python, we recommend that you
sign up for NDAB24000U Python Programming for Data Science.
If you have solid python skills and the expected math background,
we recommend NDAK22000U Machine Learning A (MLA) or SHUA13043U
Course in Bioinformatics and Systems Biology – note that there are
detailed descriptions of the recommended qualifications, including
a self-assessment.
The course is identical to NBIK15022U Advanced Topics in
Bioinformatics.
It is not allowed to pass both courses.
The course is prepared for the bioinformatics graduate programme,
but it is open to third year BSc students and MSc students in
general.
- ECTS
- 7,5 ECTS
- Type of assessment
-
Continuous assessment
- Type of assessment details
- Mandatory homework assignments. Grade based on the average number of points obtained in the assignments.
- Aid
- All aids allowed
- Marking scale
- 7-point grading scale
- Censorship form
- No external censorship
Several internal examiners
- Re-exam
-
Renewed hand in of mandatory homework assignments.
Criteria for exam assessment
In order to obtain the grade 12 the student should convincingly and accurately demonstrate the knowledge, skills and competences described under Learning Outcome.
Single subject courses (day)
- Category
- Hours
- Lectures
- 40
- Preparation
- 122
- Practical exercises
- 24
- Exam
- 20
- English
- 206
Kursusinformation
- Language
- English
- Course number
- NBIK20004U
- ECTS
- 7,5 ECTS
- Programme level
- Full Degree Master
- Duration
-
1 block
- Placement
- Block 1
- Schedulegroup
-
C
- Capacity
- No limitation – unless you register in the late-registration period (BSc and MSc) or as a credit or single subject student.
- Studyboard
- Study Board for the Biological Area
Contracting department
- Department of Biology
- GLOBE Institute
Contracting faculty
- Faculty of Science
Course Coordinator
- Anders Albrechtsen (12-6969746a7a6d6b707c7b6d76486a717736737d366c73)
Er du BA- eller KA-studerende?
Kursusinformation for indskrevne studerende