Admission Requirements
Statistics and probability
Linear & generalized linear models and linear algebra
Statistical computing with R
Description
Statistical genetics plays an important role within the Life Sciences and impacts clinical research and decistion making, as well as food production and design.
The course covers models for genetic data, including dependencies arising from family data (pedigrees) and genetic transmission across generations (recombinations, linkage, linkage disequilibrium, heritability). These models form the basis for methods used in animal and plant breeding as well in genetic association studies. Methods covered include genome wide linkage and association studies, the analysis of candidate genes, Mendelian randomization studies, and gene expression data.
Data sets from human genetics and from animal and plant breeding studies will be analyzed.
Course objectives
After completion of the course the student is able to:
Part 1: Plant genetics
Principles of Plant Genetics:
1. understand experimental populations and their statistical properties
2. analyze data to evaluate experimental population
3. evaluate results from data analysis to draw conclusions on breeding experiments
Linkage analysis in Plants:
1. understand segregation in experimental populations
2. evaluate data to create genetic maps and investigate segregation
3. evaluate experimental designs with respect to map resolution
Quantitative trait loci (QTL) mapping:
1. understand the relationship between QTLs and genetic/phenotypic variation
2. analyze data and model output to judge presence of QTLs
3. evaluate designs and analysis strategies with respect to suitability for QTL analyses
Genotype by environment (GxE):
1. understand the importance of GxE analyses and corresponding designs
2. analyze GxE data and interpret the output,
3. evaluate interpretations of GxE analyses and corresponding conclusions
Part 2: Human genetics
Population Genetics:
1. model genetic transmission in human populations and model heritability
2. understand genetic drift
3. apply statistical methods to quantify population stratification
4. evaluate the consequences of population stratification in downstream analyses
Genetic association:
1. to create a Genome-wide association study (GWAS) analysis report and quality control analysis
2. critically appraise and evaluate a GWAS, by recognizing problematic results and improve the analysis
3. be able to perform genetic global testing and gene set enrichment (GSA) analyses
Mendelian Randomization (MR):
1. understand assumptions of MR
2. apply a MR analysis to data
3. evaluate results and recognize limitations
Gene Expression data:
1. perform differential gene expression (DE) analysis both for chip bases and next generation sequencing data
2. assess the quality of DE analyses
Timetable
In MyTimetable, you can find all course and programme schedules, allowing you to create your personal timetable. Activities for which you have enrolled via MyStudyMap will automatically appear in your timetable.
Additionally, you can easily link MyTimetable to a calendar app on your phone, and schedule changes will be automatically updated in your calendar. You can also choose to receive email notifications about schedule changes. You can enable notifications in Settings after logging in.
Questions? Watch the video, read the instructions, or contact the ISSC helpdesk.
Note: Joint Degree students from Leiden/Delft need to combine information from both the Leiden and Delft MyTimetables to see a complete schedule. This video explains how to do it.
Mode of Instruction
Lectures, practicals, and two assignments
Assessment method
Computer practicals (10% of the grade): Obligatory computer practicals
Examination (70%): The mode of examination (oral or written) will be announced in the first week of the course and depends on the number of participants
Assignments (20%): On the last day of each part an assignment will be held instead of the lectures/computer practicals. In these assignments the code developed in the computer practicals has to be used for a data analysis. Physical attendance is obligatory and conflicts with other courses have to be communicated to the tutors at the beginning of the course. A report has to be submitted together with R-code to complete the assignments.
Reading List
Book “The Fundamentals of Modern Statistical Genetics”, Laird and Lange, Springer 2011
Book “Phenotypes and Genotypes“, Frommlet, Bogdan, and Ramsey, Springer 2016
Registration
As a student, you are responsible for enrolling on time through MyStudyMap.
In this short video, you can see step-by-step how to enrol for courses in MyStudyMap.
Extensive information about the operation of MyStudyMap can be found here.
There are two enrolment periods per year:
Enrolment for the fall opens in July
Enrolment for the spring opens in December
See this page for more information about deadlines and enrolling for courses and exams.
Note:
It is mandatory to enrol for all activities of a course that you are going to follow.
Your enrolment is only complete when you submit your course planning in the ‘Ready for enrolment’ tab by clicking ‘Send’.
Not being enrolled for an exam/resit means that you are not allowed to participate in the exam/resit.
Contact
Stefan Böhringer, email: s.boehringer@lumc.nl
Remarks
Software
Starting from the 2024/2025 academic year, the Faculty of Science will use the software distribution platform Academic Software. Through this platform, you can access the software needed for specific courses in your studies. For some software, your laptop must meet certain system requirements, which will be specified with the software. It is important to install the software before the start of the course. More information about the laptop requirements can be found on the student website.
R will be used as the software package during practicals and the assignments.