Statistical genetics is about using data and quantitative methods to understand how differences in DNA relate to traits, diseases, and human variation. Modern studies measure millions of genetic markers, and this field focuses on tools that help clean, explore, and make sense of large datasets and biobanks. A key idea is that most traits are influenced by many genetic variants, each contributing a small amount. Statistical genetics offers methods to detect these signals, quantify the contributions of these variants, and elucidate how ancestry affects patterns of inheritance.
Overall, this field connects biology with data science, offering practical approaches to interpret genetic variation and its impact on public health and diseases using big data techniques and modelling.
General information
| Course dates | 27 July - 7 August, 2026 (two-week course, 10 study days) |
|---|---|
| Course fee | 750 EUR |
| Course format | summer course |
| Study field | Statistical Genetics, Genetic Epidemiology, Personalised Medicine and Risk Prediction |
| Language | English |
| Study group | master's, PhD students |
| Assessment / ECTS | Graded / 3ECTS |
| Location | Tartu University of Tartu Delta Centre, Narva mnt 18 |
Course description
This hands-on summer course introduces modern genomic data analysis and is organised within the framework of the Horizon Europe TeamPerMed – Centre for Data-Enriched Medicine (project 101060011). It directly supports TeamPerMed WP2 and WP4 by building capacity in genomic risk prediction methods (GWAS, PRS) and reproducible analysis pipelines that underpin our pilot studies and future clinical decision support tools. Starting from raw genotype-phenotype datasets, we will explore how to clean, visualise, and interpret complex biological patterns. Along the way, students will learn practical skills that underpin today’s genetic research, including running exploratory analyses (EDA), applying quality control (QC), uncovering population structure, and conducting basic genome-wide association studies (GWAS).
Students will work in groups and learn to interpret findings from a biological perspective, understanding how ancestry influences the signals we detect. Students will build confidence in core computational methods, such as dimensionality reduction, clustering, and polygenic risk scoring, while maintaining a focus on clarity and reproducibility.
Course lecturers
| Course lecturer | Description |
|---|---|
| Prof. Andres Metspalu | Professor of Genomics and Biobanking (University of Tartu, Institute of Genomics), Professor of Biotechnology (University of Tartu, Institute of Molecular and Cell Biology) |
| Prof. Krista Fischer | Professor of Mathematical Statistics (University of Tartu, Institute of Mathematics and Statistics), Associate Professor in Biostatistics (University of Tartu, Institute of Genomics). |
| Prof. Märt Möls | Associate Professor in Mathematical Statistics (University of Tartu, Institute of Mathematics and Statistics) |
| Dr. Kristi Läll | Research Fellow (University of Tartu, Institute of Genomics) |
| Dr. Gabin Drouard | Research Fellow (University of Helsinki, Institute for Molecular Medicine Finland (FIMM)) |
| Linda Repetto | Research Fellow of Population Genetics at the University of Tartu Institute of Genomics |
| Elia Tiso | Junior Research Fellow of Population Genetics at the University of Tartu Institute of Genomics |
Study information about the course
- Basic knowledge of at least one scripting language between R and Python.
- Background in at least one area among Epidemiology / Biology, Statistics / Mathematics and Data Science / Computer Science.
- Basic knowledge of Unix / Bash is preferable
Day 1: Monday, 27 July
Introduction to Gen. Epi., SNPs, data formats
Day 2: Tuesday, 28 July
EDA, QC: missingness, MAF, HWE
Day 3: Wednesday, 29 July
PCA, UMAP, clustering, interpretation
Day 4: Thursday, 30 July
PCA, UMAP, clustering, interpretation
Day 5: Friday, 31 July
Small-scale GWAS; Manhattan and QQ plots
Saturday, 1 August: free day
Sunday, 2 August: free day
Day 6: Monday, 3 August
Small-scale GWAS; Manhattan and QQ plots
Day 7: Tuesday, 4 August
PRS basics, ethics and privacy
Day 8: Wednesday, 5 August
PRS and rare variants of high impact
Day 9: Thursday, 6 August
Context-specificity of PRS and interpretation
Day 10: Friday, 7 August
Integration of all course skills
Short tasks (plots, QC …) to practice the lecture’s material.
Final group project: combine data preprocessing, visualisation, clustering, PRS, and presentation to the class.
By the end of the course, students will be able to:
- perform exploratory data analysis (EDA) and visualise genotype-phenotype datasets;
- apply quality control (QC) procedures to genomic data;
- conduct dimensionality reduction and clustering to identify population structures and more;
- run simplified GWAS and interpret association signals;
- compute and interpret simple polygenic risk scores (PRS);
- integrate computational analysis with biological understanding of ancestry;
- understand where statistical genetics methods fit in the broader TeamPerMed research pipeline (data → models → trials → guidelines → socio-economic impact);
- collaborate effectively and maintain reproducible workflows;
- present findings in a clear, visually appealing, and scientifically rigorous manner.
Course registration info
- Application period: 20 March – 20 April
- Notification of acceptance: accepted participants will be informed after the application period, by 30 April at the latest
- Deadline for paying the course fee: 31 May
- Confirmation of courses taking place: 5 June
- UniTartu Summer School in Tartu: 27 July – 7 August
Only fully completed applications, including all required annexes, received by the deadline (20 April) will be considered for selection. Applicants must submit the following:
- online application form (application period: 20 March–20 April 2026);
- motivation letter (maximum 1 page), explaining:
- your motivation to participate,
- your expectations for the programme,
- how the summer course relates to your studies and interests,
- how you plan to use the knowledge and experience gained in the future
- transcript of academic records;
- copy of your passport;
- proof of the application fee payment (25 EUR).
The participants of the UniTartu Summer School courses are required to pay:
- The application fee of 25 EUR must be paid by the application deadline (20 April) at the latest.
The application fee is non-refundable. - The course fee is 750 EUR.
Includes: Study materials, academic work with lecturers, Certificate of completion, and cultural events in the evenings
Not included: meals, transportation and accommodation
Please note that the course fee is payable only after you have been accepted into the course. Once accepted, you will receive a confirmation of acceptance together with an invoice. The course fee can only be paid based on the invoice issued to you.
By paying the application fee, course fee and cultural events fee, you accept the terms and conditions information document. You are required to tick the box in the credit card payment form to confirm you have read and agree to terms and conditions. If you choose to pay by bank transfer, you will be informed of the same conditions.
Please note that by paying the fees, you are considered to have accepted the Terms and Conditions.
