Lecture: Systems Genetics 2020

Systems genetics 2020


Matthias HeinigJulien Gagneur
Tel.: +49 89 3187-2434
E-mail:  E-mail:


Date & Time:     Tuesday 2.00 pm - 5.00 pm (1.5h lecture, 1.5h applied exercise)
Target Group:Master's programs in Bioinformatics and Informatics  
Language:      English
Lecture Material:Moodle
Link:Module description, TUM


Intended Learning Outcomes: At the end of the module, students understand / are able to practically implement:

  • the challenges of complex trait genetics
  • statistical models for QTL mapping and GWAS
  • methods for adjustment for multiple testing
  • linear mixed models to deal with population structure
  • experimental techniques to measure gene expression
  • algorithms for transcriptome quantification from NGS
  • efficient algorithms for expression QTL analysis
  • methods of metabolome quantification
  • algorithms based on gene sets
  • statistical concepts for causal inference such as Mendelian randomization
  • regularized linear models and its applications in genetics
  • network inference methods such as Graphical Gaussian models
  • the application of graphical models for the integration of multiple OMICS data sets


  • Introduction to human genetics
  • Quantitative genetics / GWAS
  • Multiple hypothesis testing
  • Population structure
  • Transcriptomics
  • Metabolomics
  • Enrichment algorithms
  • Causal inference
  • Regularized linear models
  • Network models
  • Multi-OMICS data integration