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Summer course in analysis of high throughput data for population genetics
Provider: Faculty of Science

Activity no.: 5081-23-01-31 
Enrollment deadline: 12/08/2023
Date and time07.08.2023, at: 09:00 - 11.08.2023, at: 16:00
Regular seats40
ECTS credits5.00
Contact personIda Moltke    E-mail address: ida@bio.ku.dk
Enrolment Handling/Course OrganiserIda Moltke    E-mail address: ida@bio.ku.dk
Written languageEnglish
Teaching languageEnglish
Semester/BlockSummer
Block note1 week full time August 7-11, 2023
Exam formActive participation during the campus course
Exam aidsAll aids allowed
Grading scalePassed / Not passed
Course workload
Course workload categoryHours
Preparation85.00
Lectures40.00
Exercises20.00
Sum145.00
Content
THIS COURSE IS CLOSED FOR APPLICATIONS OTHER THAN THOSE ALREADY ACCEPTED IN JULY ON THE EXTERNAL WEB SITE OF THE COURSE

The course is a comprehensive introduction to a number of topics and common research tools used in analyses of genetic data. Topics include: genetic drift, natural selection, population structure, Fst, linkage disequilibrium, relatedness, association mapping, GWAS, IBD mapping, admixture mapping, genotyping data, next-generation sequencing (NGS) data, 1000 genomes project data. The main focus will be on humans but the methods are applicable for many other species as well. Lectures will be combined with hands-on computer exercises mostly using R and commandline based programs.

Aim and content
The course is a comprehensive introduction to a number of topics and common research tools used in analyses of genetic data. Topics include: genetic drift, natural selection, population structure, Fst, linkage disequilibrium, relatedness, association mapping, GWAS, IBD mapping, admixture mapping, genotyping data, next-generation sequencing (NGS) data, 1000 genomes project data. The main focus will be on humans but the methods are applicable for many other species as well. Lectures will be combined with hands-on computer exercises mostly using R and commandline based programs.

Formel requirements
Academic qualifications:
The students are expected to have knowledge about either population genetics or medical genetics and preferable they are actively working within these fields.

Learning outcome
After the course the student will be able to:

•Use population genetic theory to infer basic population genetics characteristics from genetic data, including Fst, population size, relatedness and linkage disequilibrium
•Be able to infer ancestry and population structure based on genetic data
•Select the optimal strategy for disease mapping based on the available data, the trait of interest, and the population genetics characteristics of the sample population, including taking population structure into account
•Perform disease mapping, including genome-wide association studies
•Interpret and discuss the results of own analyses and results in the scientific literature

Literature
Notes and articles for background reading prior to course start will be made available on the course webpage (password protected).

Additionally, handouts will be passed out during the course, but for each lecture there is one or two articles/notes that should be read in advance.

Teaching and learning methods
A mix of lectures, hands-on computer exercises and research talks.

Remarks
Lecturers:
Assistant professor Ida Moltke, University of Copenhagen
Associate professor Anders Albrechtsen, University of Copenhagen

Guest lectures by several international leaders in the field.


Academic qualifications:
The students are expected to have knowledge about either population genetics or medical genetics and preferable they are actively working within these fields.

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